├── .gitignore ├── R ├── SWD_2019-09_Uncertainty.Rmd ├── SWD_2019-09_Uncertainty_365.Rmd ├── SWD_2020_01_SmallMultiples.Rmd └── SWD_2020_03_Animation.Rmd ├── README.md ├── SWD.Rproj ├── data ├── D1.csv ├── produkt_klima_tag_18760101_19621231_00402_Dahlem.txt ├── produkt_klima_tag_19500101_20181231_00403_Dahlem.txt ├── produkt_klima_tag_20180307_20190907_00403_Dahlem.txt └── time-series-19-covid-combined_csv.csv └── plots ├── 2019_09 ├── README.md ├── SWD_2019_09_Uncertainty.png ├── SWD_2019_09_Uncertainty_365.png ├── SWD_2019_09_Uncertainty_98-08-18.png ├── SWD_2019_09_Uncertainty_Fahrenheit.png ├── SWD_2019_09_Uncertainty_decades.png └── SWD_2019_09_Uncertainty_ger.png ├── 2020_01 ├── README.md ├── SWD_2020_01_SmallMultiples_color.png └── SWD_2020_01_SmallMultiples_grey.png └── 2020_03 ├── README.md ├── corona_begin.gif ├── corona_begin.mp4 ├── corona_begin_latest_hq.png ├── corona_sum.gif ├── corona_sum.mp4 └── corona_sum_latest_hq.png /.gitignore: -------------------------------------------------------------------------------- 1 | # History files 2 | .Rhistory 3 | .Rapp.history 4 | 5 | # Session Data files 6 | .RData 7 | 8 | # Example code in package build process 9 | *-Ex.R 10 | 11 | # Output files from R CMD build 12 | /*.tar.gz 13 | 14 | # Output files from R CMD check 15 | /*.Rcheck/ 16 | 17 | # RStudio files 18 | .Rproj.user/ 19 | 20 | # produced vignettes 21 | vignettes/*.html 22 | vignettes/*.pdf 23 | 24 | # OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3 25 | .httr-oauth 26 | 27 | # knitr and R markdown default cache directories 28 | /*_cache/ 29 | /cache/ 30 | 31 | # Temporary files created by R markdown 32 | *.utf8.md 33 | *.knit.md 34 | 35 | # Shiny token, see https://shiny.rstudio.com/articles/shinyapps.html 36 | rsconnect/ 37 | 38 | # html files 39 | /html/ 40 | *.html 41 | 42 | # desktop.ini et al 43 | *.ini 44 | 45 | # pdf files 46 | *.pdf 47 | 48 | # _all png directory 49 | /plots/_all/ 50 | 51 | # images for corona series 52 | /plots/2020_03/series* 53 | -------------------------------------------------------------------------------- /R/SWD_2019-09_Uncertainty.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "SWD Challenge September 2019 - Visualizing Uncertainty" 3 | author: "Cedric Scherer" 4 | date: "8th of September 2019" 5 | output: 6 | html_document: 7 | theme: paper 8 | highlight: kate 9 | editor_options: 10 | chunk_output_type: console 11 | --- 12 | 13 | ```{r setup, include=FALSE} 14 | knitr::opts_chunk$set(echo = TRUE, warning=FALSE) 15 | ``` 16 | 17 | ```{r prep} 18 | library(tidyverse) 19 | library(tidybayes) 20 | library(patchwork) 21 | library(cowplot) 22 | library(extrafont) 23 | 24 | extrafont::loadfonts(device = "win", quiet = TRUE) 25 | 26 | theme_set(theme_minimal(base_family = "Bitter")) 27 | ``` 28 | 29 | 30 | ```{r data} 31 | ## Data source: DWD (Deutscher Wetterdienst) 32 | ## https://www.dwd.de/DE/leistungen/_config/leistungsteckbriefPublication.zip?view=nasPublication&nn=16102&imageFilePath=157242051950877752011408908330930139598321949458353665338080907323067407358570939094063695252196106887026681320814526060536595251033063153662108661981192575715848535028223489905255018373803265100435386215906807083067001006526258509883339654785117109676510167984069504119&download=true 33 | 34 | df_dwd_dahlem <- 35 | readr::read_delim( 36 | here::here("data", "produkt_klima_tag_19500101_20181231_00403_Dahlem.txt"), 37 | delim = ";" 38 | ) %>% 39 | dplyr::select( 40 | station_id = STATIONS_ID, 41 | date = MESS_DATUM, 42 | t_avg = " TMK", 43 | t_min = " TNK", 44 | t_max = " TXK" 45 | ) %>% 46 | mutate_all(as.numeric) %>% 47 | mutate( 48 | date = lubridate::ymd(date), 49 | year = lubridate::year(date), 50 | month = lubridate::month(date), 51 | t_max_f = t_max * (9/5) + 32 52 | ) 53 | ``` 54 | 55 | 56 | ```{r plot, fig.width = 13, fig.height = 8} 57 | plot <- 58 | df_dwd_dahlem %>% 59 | filter(year >= 2000) %>% 60 | ggplot(aes(t_max, month)) + 61 | stat_intervalh(.width = c(.1, .25, .5, .75, 1), 62 | height = 5, show.legend = F) + 63 | rcartocolor::scale_color_carto_d(palette = "Peach") + 64 | stat_halfeyeh(aes(t_max, month + 0.06), 65 | .width = 0, fill = "tan", alpha = 0.2, height = 0.7, 66 | size = 0.7, point_alpha = 1, point_color = "#590000") + 67 | coord_flip(ylim = c(0.5, 13)) + 68 | scale_x_continuous(expand = c(0, 0), limits = c(-13, 38), 69 | breaks = seq(-10, 35, by = 5), 70 | labels = glue::glue("{seq(-10, 35, by = 5)}°C")) + 71 | scale_y_continuous(expand = c(0, 0), breaks = 1:12, 72 | labels = c("January", 73 | "February", 74 | "March", 75 | "April", 76 | "May", 77 | "June", 78 | "July", 79 | "August", 80 | "September", 81 | "October", 82 | "November", 83 | "December")) + 84 | labs(x = "", y = "") + 85 | theme(panel.grid.minor = element_blank(), 86 | panel.grid.major.x = element_blank(), 87 | panel.grid.major.y = element_line(size = 0.1), 88 | axis.text.x = element_text(size = 11, face = "bold"), 89 | axis.text.y = element_text(size = 9, color = "grey65")) 90 | 91 | 92 | legend_text <- 93 | tibble( 94 | xt = c(5, 4.125, 3.125, 1.875, 0.625, 7.5), 95 | yt = rep(1.02, 6), 96 | text = c("10%", "25%", "50%", "75%", "100%", "of measured temperatures fall in this range") 97 | ) 98 | 99 | legend <- ggplot(data = tibble(x = 0:10, y = rep(1, 11)), aes(x, y)) + 100 | stat_intervalh(.width = c(.1, .25, .5, .75, 1), show.legend = F) + 101 | rcartocolor::scale_color_carto_d(palette = "Peach") + 102 | coord_cartesian(ylim = c(0.9, 1.1)) + 103 | geom_text(data = legend_text, aes(xt, yt, label = text), 104 | family = "Bitter", color = "grey65", size = 3) + 105 | theme_void() 106 | 107 | title <- ggplot(data.frame(x = 1:2, y = 1:10)) + 108 | labs(x = NULL, y = NULL, 109 | title = "Daily Temperatures in Berlin, Germany", 110 | subtitle = "Range and distribution of maximum daily temperatures in Celsius per month from 2000 to 2018 measured in Berlin-Dahlem, Germany") + 111 | theme(line = element_blank(), 112 | plot.title = element_text(size = 26, hjust = 0, face = "bold", family = "Bitter"), 113 | plot.subtitle = element_text(size = 13, hjust = 0, color = "grey65"), 114 | panel.background = element_rect(fill = "transparent", color = "transparent"), 115 | plot.background = element_rect(fill = "transparent", color = "transparent"), 116 | panel.border = element_rect(color = "transparent"), 117 | axis.text = element_blank()) 118 | 119 | caption <- ggplot(data.frame(x = 1:2, y = 1:10)) + 120 | labs(x = NULL, y = NULL, 121 | caption = "Visualization by Cédric Scherer | Data: DWD (Deutscher Wetterdienst)") + 122 | theme(line = element_blank(), 123 | plot.caption = element_text(size = 10, color = "grey65"), 124 | panel.background = element_rect(fill = "transparent", color = "transparent"), 125 | plot.background = element_rect(fill = "transparent", color = "transparent"), 126 | panel.border = element_rect(color = "transparent"), 127 | axis.text = element_blank()) 128 | 129 | plot_ins <- ggdraw(plot) + 130 | draw_plot(legend, .275, .01, .525, .3) 131 | 132 | title + plot_ins + caption + plot_layout(widths = c(0, 1, 0)) 133 | 134 | ggsave(here::here("plots", "2019_09", "SWD_2019_09_Uncertainty.pdf"), 135 | width = 13, height = 8, device = cairo_pdf) 136 | ``` 137 | 138 | ## Fahrenheit Version 139 | 140 | ```{r plot-fahrenheit, fig.width = 13, fig.height = 8} 141 | plot_f <- 142 | df_dwd_dahlem %>% 143 | filter(year >= 2000) %>% 144 | ggplot(aes(t_max_f, month)) + 145 | stat_intervalh(.width = c(.1, .25, .5, .75, 1), 146 | height = 5, show.legend = F) + 147 | rcartocolor::scale_color_carto_d(palette = "PurpOr") + 148 | stat_halfeyeh(aes(t_max_f, month + 0.06), 149 | .width = 0, fill = "#f0c6c3", alpha = 0.2, height = 0.7, 150 | size = 0.7, point_alpha = 1, point_color = "#3a004d") + 151 | coord_flip(ylim = c(0.5, 13)) + 152 | scale_x_continuous(expand = c(0, 0), limits = c(10, 105), 153 | breaks = seq(20, 100, by = 20), 154 | labels = glue::glue("{seq(20, 100, by = 20)}°F")) + 155 | scale_y_continuous(expand = c(0, 0), breaks = 1:12, 156 | labels = c("January", 157 | "February", 158 | "March", 159 | "April", 160 | "May", 161 | "June", 162 | "July", 163 | "August", 164 | "September", 165 | "October", 166 | "November", 167 | "December")) + 168 | labs(x = "", y = "") + 169 | theme(panel.grid.minor = element_blank(), 170 | panel.grid.major.x = element_blank(), 171 | panel.grid.major.y = element_line(size = 0.1), 172 | axis.text.x = element_text(size = 11, face = "bold"), 173 | axis.text.y = element_text(size = 9, color = "grey65")) 174 | 175 | legend_f <- ggplot(data = tibble(x = 0:10, y = rep(1, 11)), aes(x, y)) + 176 | stat_intervalh(.width = c(.1, .25, .5, .75, 1), show.legend = F) + 177 | rcartocolor::scale_color_carto_d(palette = "PurpOr") + 178 | coord_cartesian(ylim = c(0.9, 1.1)) + 179 | geom_text(data = legend_text, aes(xt, yt, label = text), 180 | family = "Bitter", color = "grey65", size = 3) + 181 | theme_void() 182 | 183 | title_f <- ggplot(data.frame(x = 1:2, y = 1:10)) + 184 | labs(x = NULL, y = NULL, 185 | title = "Daily Temperatures in Berlin, Germany", 186 | subtitle = "Range and distribution of maximum daily temperatures in Fahrenheit per month from 2000 to 2018 measured in Berlin-Dahlem, Germany") + 187 | theme(line = element_blank(), 188 | plot.title = element_text(size = 26, hjust = 0, face = "bold", family = "Bitter"), 189 | plot.subtitle = element_text(size = 13, hjust = 0, color = "grey65"), 190 | panel.background = element_rect(fill = "transparent", color = "transparent"), 191 | plot.background = element_rect(fill = "transparent", color = "transparent"), 192 | panel.border = element_rect(color = "transparent"), 193 | axis.text = element_blank()) 194 | 195 | plot_ins_f <- ggdraw(plot_f) + 196 | draw_plot(legend_f, .275, .03, .525, .35) 197 | 198 | title_f + plot_ins_f + caption + plot_layout(widths = c(0, 1, 0)) 199 | 200 | ggsave(here::here("plots", "2019_09", "SWD_2019_09_Uncertainty_Fahrenheit.pdf"), 201 | width = 13, height = 8, device = cairo_pdf) 202 | ``` 203 | 204 | ## German Version 205 | 206 | ```{r plot-german, fig.width = 13, fig.height = 8} 207 | plot_g <- 208 | df_dwd_dahlem %>% 209 | filter(year >= 2000) %>% 210 | ggplot(aes(t_max, month)) + 211 | stat_intervalh(.width = c(.1, .25, .5, .75, 1), 212 | height = 5, show.legend = F) + 213 | rcartocolor::scale_color_carto_d(palette = "Teal") + 214 | stat_halfeyeh(aes(t_max, month + 0.06), 215 | .width = 0, fill = "paleturquoise3", alpha = 0.2, height = 0.7, 216 | size = 0.7, point_alpha = 1, point_color = "#003537") + 217 | coord_flip(ylim = c(0.5, 13)) + 218 | scale_x_continuous(expand = c(0, 0), limits = c(-13, 38), 219 | breaks = seq(-10, 35, by = 5), 220 | labels = glue::glue("{seq(-10, 35, by = 5)}°C")) + 221 | scale_y_continuous(expand = c(0, 0), breaks = 1:12, 222 | labels = c("Januar", 223 | "Februar", 224 | "März", 225 | "April", 226 | "Mai", 227 | "Juni", 228 | "Juli", 229 | "August", 230 | "September", 231 | "Oktober", 232 | "November", 233 | "Dezember") 234 | ) + 235 | labs(x = "", y = "") + 236 | theme(panel.grid.minor = element_blank(), 237 | panel.grid.major.x = element_blank(), 238 | panel.grid.major.y = element_line(size = 0.1), 239 | axis.text.x = element_text(size = 11, face = "bold"), 240 | axis.text.y = element_text(size = 9, color = "grey65")) 241 | 242 | 243 | legend_text_g <- 244 | tibble( 245 | xt = c(5, 4.125, 3.125, 1.875, 0.625, 7.3), 246 | yt = rep(1.02, 6), 247 | text = c("10%", "25%", "50%", "75%", "100%", "der Temperaturen liegen in diesem Bereich") 248 | ) 249 | 250 | legend_g <- ggplot(data = tibble(x = 0:10, y = rep(1, 11)), aes(x, y)) + 251 | stat_intervalh(.width = c(.1, .25, .5, .75, 1), show.legend = F) + 252 | rcartocolor::scale_color_carto_d(palette = "Teal") + 253 | coord_cartesian(ylim = c(0.9, 1.1)) + 254 | geom_text(data = legend_text_g, aes(xt, yt, label = text), 255 | family = "Bitter", color = "grey65", size = 3) + 256 | theme_void() 257 | 258 | title_g <- ggplot(data.frame(x = 1:2, y = 1:10)) + 259 | labs(x = NULL, y = NULL, 260 | title = "Maximale Tagestemperaturen in Berlin", 261 | subtitle = "Verteilung der maximalen Tagestemperaturen in Berlin-Dahlem im Jahresverlauf von 1. Januar 2000 bis 31. Dezember 2018") + 262 | theme(line = element_blank(), 263 | plot.title = element_text(size = 26, hjust = 0, face = "bold", family = "Bitter"), 264 | plot.subtitle = element_text(size = 13, hjust = 0, color = "grey65"), 265 | panel.background = element_rect(fill = "transparent", color = "transparent"), 266 | plot.background = element_rect(fill = "transparent", color = "transparent"), 267 | panel.border = element_rect(color = "transparent"), 268 | axis.text = element_blank()) 269 | 270 | caption_g <- ggplot(data.frame(x = 1:2, y = 1:10)) + 271 | labs(x = NULL, y = NULL, 272 | caption = "Visualisierung: Cédric Scherer | Daten: DWD (Deutscher Wetterdienst)") + 273 | theme(line = element_blank(), 274 | plot.caption = element_text(size = 10, color = "grey65"), 275 | panel.background = element_rect(fill = "transparent", color = "transparent"), 276 | plot.background = element_rect(fill = "transparent", color = "transparent"), 277 | panel.border = element_rect(color = "transparent"), 278 | axis.text = element_blank()) 279 | 280 | plot_ins_g <- ggdraw(plot_g) + 281 | draw_plot(legend_g, .275, .01, .525, .3) 282 | 283 | title_g + plot_ins_g + caption_g + plot_layout(widths = c(0, 1, 0)) 284 | 285 | ggsave(here::here("plots", "2019_09", "SWD_2019_09_Uncertainty_ger.pdf"), 286 | width = 13, height = 8, device = cairo_pdf) 287 | ``` 288 | 289 | *** 290 | 291 | ```{r} 292 | sessionInfo() 293 | ``` 294 | -------------------------------------------------------------------------------- /R/SWD_2019-09_Uncertainty_365.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "SWD Challenge September 2019 - Visualizing Uncertainty" 3 | author: "Cedric Scherer" 4 | date: "8th of September 2019" 5 | output: 6 | html_document: 7 | theme: paper 8 | highlight: kate 9 | editor_options: 10 | chunk_output_type: console 11 | --- 12 | 13 | ```{r setup, include=FALSE} 14 | knitr::opts_chunk$set(echo = TRUE, warning=FALSE) 15 | ``` 16 | 17 | ```{r prep} 18 | library(tidyverse) 19 | library(tidybayes) 20 | library(patchwork) 21 | library(cowplot) 22 | library(extrafont) 23 | 24 | extrafont::loadfonts(device = "win", quiet = TRUE) 25 | 26 | theme_set(theme_minimal(base_family = "Bitter")) 27 | ``` 28 | 29 | 30 | ```{r data} 31 | ## Data source: DWD (Deutscher Wetterdienst) 32 | ## https://www.dwd.de/DE/leistungen/klimadatendeutschland/klarchivtagmonat.html 33 | 34 | df_dwd_dahlem <- 35 | readr::read_delim( 36 | here::here("data", "produkt_klima_tag_20180307_20190907_00403_Dahlem.txt"), 37 | delim = ";" 38 | ) %>% 39 | dplyr::select( 40 | station_id = STATIONS_ID, 41 | date = MESS_DATUM, 42 | t_avg = " TMK", 43 | t_min = " TNK", 44 | t_max = " TXK" 45 | ) %>% 46 | mutate_all(as.numeric) %>% 47 | mutate( 48 | date = lubridate::ymd(date), 49 | year = lubridate::year(date), 50 | month = lubridate::month(date) 51 | ) 52 | ``` 53 | 54 | 55 | ```{r plot, fig.width = 13, fig.height = 8} 56 | plot <- 57 | df_dwd_dahlem %>% 58 | filter(date %in% seq(as.Date("2018-09-08"), as.Date("2019-09-07"), by = 1)) %>% 59 | ggplot(aes(t_max, month)) + 60 | stat_intervalh(.width = c(.1, .25, .5, .75, 1), 61 | height = 5, show.legend = F) + 62 | rcartocolor::scale_color_carto_d(palette = "Peach") + 63 | stat_halfeyeh(aes(t_max, month + 0.06), 64 | .width = 0, fill = "tan", alpha = 0.2, 65 | size = 0.7, point_alpha = 1, height = 0.7) + 66 | coord_flip(ylim = c(0.5, 13)) + 67 | scale_x_continuous(expand = c(0, 0), limits = c(-13, 38), 68 | breaks = seq(-10, 35, by = 5), 69 | labels = glue::glue("{seq(-10, 35, by = 5)}°C")) + 70 | scale_y_continuous(expand = c(0, 0), breaks = 1:12, 71 | labels = c("January", 72 | "February", 73 | "March", 74 | "April", 75 | "May", 76 | "June", 77 | "July", 78 | "August", 79 | "September", 80 | "October", 81 | "November", 82 | "December") 83 | ) + 84 | labs(x = "", y = "") + 85 | theme(panel.grid.minor = element_blank(), 86 | panel.grid.major.x = element_blank(), 87 | panel.grid.major.y = element_line(size = 0.1), 88 | axis.text.x = element_text(size = 11, face = "bold"), 89 | axis.text.y = element_text(size = 9, color = "grey65")) 90 | 91 | 92 | legend_text <- 93 | tibble( 94 | xt = c(5, 4.125, 3.125, 1.875, 0.625, 7.5), 95 | yt = rep(1.02, 6), 96 | text = c("10%", "25%", "50%", "75%", "100%", "of measured temperatures fall in this range") 97 | ) 98 | 99 | legend <- ggplot(data = tibble(x = 0:10, y = rep(1, 11)), aes(x, y)) + 100 | stat_intervalh(.width = c(.1, .25, .5, .75, 1), show.legend = F) + 101 | rcartocolor::scale_color_carto_d(palette = "Peach") + 102 | coord_cartesian(ylim = c(0.9, 1.1)) + 103 | geom_text(data = legend_text, aes(xt, yt, label = text), 104 | family = "Bitter", color = "grey65", size = 3) + 105 | theme_void() 106 | 107 | title <- ggplot(data.frame(x = 1:2, y = 1:10)) + 108 | labs(x = NULL, y = NULL, 109 | title = "Temperatures during the last 365 Days in Berlin, Germany", 110 | subtitle = "Range and distribution of maximum daily temperatures in Celsius per month from 2018-09-08 to 2019-09-07 measured in Berlin-Dahlem, Germany") + 111 | theme(line = element_blank(), 112 | plot.title = element_text(size = 26, hjust = 0, face = "bold", family = "Bitter"), 113 | plot.subtitle = element_text(size = 13, hjust = 0, color = "grey65"), 114 | panel.background = element_rect(fill = "transparent", color = "transparent"), 115 | plot.background = element_rect(fill = "transparent", color = "transparent"), 116 | panel.border = element_rect(color = "transparent"), 117 | axis.text = element_blank()) 118 | 119 | caption <- ggplot(data.frame(x = 1:2, y = 1:10)) + 120 | labs(x = NULL, y = NULL, 121 | caption = "Visualization by Cédric Scherer | Data: DWD (Deutscher Wetterdienst)") + 122 | theme(line = element_blank(), 123 | plot.caption = element_text(size = 10, color = "grey65"), 124 | panel.background = element_rect(fill = "transparent", color = "transparent"), 125 | plot.background = element_rect(fill = "transparent", color = "transparent"), 126 | panel.border = element_rect(color = "transparent"), 127 | axis.text = element_blank()) 128 | 129 | plot_ins <- ggdraw(plot) + 130 | draw_plot(legend, .275, .01, .525, .3) 131 | 132 | title + plot_ins + caption + plot_layout(widths = c(0, 1, 0)) 133 | 134 | ggsave(here::here("plots", "2019_09", "SWD_2019_09_Uncertainty_365.pdf"), 135 | width = 13, height = 8, device = cairo_pdf) 136 | ``` 137 | 138 | *** 139 | 140 | ```{r} 141 | sessionInfo() 142 | ``` 143 | -------------------------------------------------------------------------------- /R/SWD_2020_01_SmallMultiples.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "SWDchallenge 2020/04 - Small Multiples" 3 | author: "Cedric Scherer" 4 | date: "27th of January 2020" 5 | output: 6 | html_document: 7 | theme: paper 8 | highlight: kate 9 | editor_options: 10 | chunk_output_type: console 11 | --- 12 | 13 | ```{r setup, include=FALSE} 14 | knitr::opts_chunk$set(echo = TRUE, warning=FALSE) 15 | ``` 16 | 17 | ```{r prep} 18 | library(tidyverse) 19 | library(cowplot) 20 | library(showtext) 21 | 22 | font_add_google("Oswald", "Oswald") 23 | 24 | ## fonts 25 | theme_set(theme_minimal(base_family = "Oswald")) 26 | 27 | theme_update(panel.grid.major = element_blank(), 28 | panel.grid.minor = element_blank()) 29 | ``` 30 | 31 | 32 | ```{r data} 33 | ## http://football-data.co.uk/germanym.php 34 | df_bl <- readr::read_csv(here::here("data", "D1.csv")) 35 | ``` 36 | 37 | ```{r data-prep} 38 | clubs <- 39 | c("RB Leipzig", 40 | "Borussia M'gladbach", 41 | "FC Bayern München", 42 | "Borussia Dortmund", 43 | "FC Schalke 04", 44 | "Bayer 04 Leverkusen", 45 | "TSG 1899 Hoffenheim", 46 | "SC Freiburg", 47 | "VfL Wolfsburg", 48 | "FC Augsburg", 49 | "1. FC Union Berlin", 50 | "Hertha BSC", 51 | "1. FSV Mainz 05", 52 | "Eintracht Frankfurt", 53 | "1. FC Köln", 54 | "Fortuna Düsseldorf", 55 | "Werder Bremen", 56 | "SC Paderborn 07") 57 | 58 | df_bl_days <- 59 | df_bl %>% 60 | mutate( 61 | Date = lubridate::dmy(Date), 62 | Match = glue::glue("{HomeTeam} - {AwayTeam}"), 63 | Result = glue::glue("{FTHG} - {FTAG}"), 64 | HT = HomeTeam, 65 | AT = AwayTeam 66 | ) %>% 67 | dplyr::select(Date, HomeTeam, AwayTeam, FTHG, FTAG, FTR, HS, AS, Match, Result, HT, AT) %>% 68 | gather(Team, Club, -c(Date, FTHG, FTAG, FTR, HS, AS, Match, Result, HT, AT)) %>% 69 | mutate( 70 | Goals = case_when( 71 | Team == "HomeTeam" ~ FTHG, 72 | Team == "AwayTeam" ~ FTAG 73 | ), 74 | Diff = case_when( 75 | Team == "HomeTeam" ~ FTHG - FTAG, 76 | Team == "AwayTeam" ~ FTAG - FTHG 77 | ), 78 | Score = case_when( 79 | FTR == "D" ~ 1, 80 | Team == "HomeTeam" & FTR == "H" ~ 3, 81 | Team == "AwayTeam" & FTR == "A" ~ 3, 82 | TRUE ~ 0 83 | ), 84 | Shots = case_when( 85 | Team == "HomeTeam" ~ HS, 86 | Team == "AwayTeam" ~ AS 87 | ), 88 | Opponent = case_when( 89 | Team == "HomeTeam" ~ AT, 90 | Team == "AwayTeam" ~ HT 91 | ) 92 | ) %>% 93 | dplyr::select(Date, Match, Result, Club, Score, Goals, Shots, Diff, Opponent) %>% 94 | group_by(Club) %>% 95 | arrange(Date) %>% 96 | mutate( 97 | Day = row_number(), 98 | Score_sum = cumsum(Score), 99 | Diff_sum = cumsum(Diff), 100 | Goals_sum = cumsum(Goals), 101 | ) %>% 102 | group_by(Day) %>% 103 | arrange(desc(Score_sum), desc(Diff_sum), desc(Goals_sum)) %>% 104 | mutate( 105 | Position = row_number(), 106 | Club = case_when( 107 | Club == "Augsburg" ~ "FC Augsburg", 108 | Club == "Bayern Munich" ~ "FC Bayern München", 109 | Club == "Dortmund" ~ "Borussia Dortmund", 110 | Club == "Ein Frankfurt" ~ "Eintracht Frankfurt", 111 | Club == "FC Koln" ~ "1. FC Köln", 112 | Club == "Fortuna Dusseldorf" ~ "Fortuna Düsseldorf", 113 | Club == "Freiburg" ~ "SC Freiburg", 114 | Club == "Hertha" ~ "Hertha BSC", 115 | Club == "Leverkusen" ~ "Bayer 04 Leverkusen", 116 | Club == "M'gladbach" ~ "Borussia M'gladbach", 117 | Club == "Mainz" ~ "1. FSV Mainz 05", 118 | Club == "Paderborn" ~ "SC Paderborn 07", 119 | Club == "Schalke 04" ~ "FC Schalke 04", 120 | Club == "Union Berlin" ~ "1. FC Union Berlin", 121 | Club == "Wolfsburg" ~ "VfL Wolfsburg", 122 | Club == "Hoffenheim" ~ "TSG 1899 Hoffenheim", 123 | TRUE ~ Club 124 | ), 125 | Opponent = case_when( 126 | Opponent == "Bayern Munich" ~ "Bayern", 127 | Opponent == "Ein Frankfurt" ~ "Frankfurt", 128 | Opponent == "FC Koln" ~ "1. FC Köln", 129 | Opponent == "Fortuna Dusseldorf" ~ "Fortuna", 130 | Opponent == "Wolfsburg" ~ "Wolfsburg", 131 | Opponent == "Hoffenheim" ~ "Hoffenheim", 132 | Opponent == "Werder Bremen" ~ "Bremen", 133 | TRUE ~ Opponent 134 | ), 135 | Top = if_else(!Club %in% c("RB Leipzig", "Borussia M'gladbach", "FC Bayern München", 136 | "Borussia Dortmund"), "0", "1"), 137 | #"Borussia Dortmund", "FC Schalke 04", "SC Freiburg"), "0", "1"), 138 | Club_fct = factor(Club, levels = clubs) 139 | ) %>% 140 | ungroup() %>% 141 | arrange(Day, Position) 142 | 143 | ## Colors for all teams 144 | cols_all <- c( 145 | "RB Leipzig" = "#294e88", 146 | "Borussia M'gladbach" = "#0ea50e", 147 | "FC Bayern München" = "#dc052d", 148 | "Borussia Dortmund" = "#e4ca00", 149 | "FC Schalke 04" = "#0000ca", 150 | "Bayer 04 Leverkusen" = "#e32221", 151 | "TSG 1899 Hoffenheim" = "#1c63b7", 152 | "SC Freiburg" = "#000000", 153 | "VfL Wolfsburg" = "#65b32e", 154 | "FC Augsburg" = "#46714d", 155 | "1. FC Union Berlin" = "#d4011d", 156 | "Hertha BSC" = "#004d93", 157 | "1. FSV Mainz 05" = "#ed1c24", 158 | "Eintracht Frankfurt" = "#000000", 159 | "1. FC Köln" = "#ef343b", 160 | "Fortuna Düsseldorf" = "#da251d", 161 | "Werder Bremen" = "#008064", 162 | "SC Paderborn 07" = "#005ca8" 163 | ) 164 | ``` 165 | 166 | ```{r efficiency, fig.width = 32, fig.height = 13.5} 167 | vbad <- tibble(x = 0:30, ymin = x * 0, ymax = x * .1) 168 | bad <- tibble(x = 0:30, ymin = x * .1, ymax = x * .2) 169 | medium <- tibble(x = 0:30, ymin = x * .2, ymax = x * .3) 170 | good <- tibble(x = 0:30, ymin = x * .3, ymax = x * .4) 171 | vgood <- tibble(x = 0:30, ymin = x * .4, ymax = x * .5) 172 | #### small multiples #### 173 | annotations <- 174 | tribble( 175 | ~Club_fct, ~Goals, ~Shots, ~label, 176 | "RB Leipzig", 11, 9.5, "Leipzig always had 10 chances\nor more and has shot the most\ngoals in a single match\n(8 vs 1. FSV Mainz 05)", 177 | "FC Bayern München", 13, 13, "FCB created the most shots\nat goal in a single match\n(29 vs SV Werder Bremen)", 178 | "Borussia Dortmund", 8.5, 5, "Dortmund had the least\nshots at goal of all teams\n(2 vs FC Bayern München)", 179 | "VfL Wolfsburg", 12.9, 10.2, "Wolfsburg has the worst goal:shot efficiency\nof all Bundesliga clubs (8%) – they also shot\n29 times in a single match but only\nscored once (remis vs FC Schalke 04)", 180 | "FC Augsburg", 9.5, 6, "Augsburg showed the highest\nefficiency in a single match\n(4 goals out of 6 shots vs\nTSG 1899 Hoffenheim)", 181 | "Hertha BSC", 11, 8.5, "Hertha never shot more\nthan 16 times on\na goal in a match", 182 | "Fortuna Düsseldorf", 8, 5, "Düsseldorf had the\nleast number of\nshots of all teams\n(2 vs Borussa Dortmund)" 183 | ) %>% 184 | mutate(Club_fct = factor(Club_fct, levels = clubs)) 185 | 186 | highlight_points <- 187 | tribble( 188 | ~Club_fct, ~Goals, ~Shots, 189 | "RB Leipzig", 8, 19, 190 | "FC Bayern München", 6, 29, 191 | "Borussia Dortmund", 0, 2, 192 | "VfL Wolfsburg", 1, 29, 193 | "FC Augsburg", 4, 6, 194 | "Fortuna Düsseldorf", 0, 2 195 | ) %>% 196 | mutate(Club_fct = factor(Club_fct, levels = clubs)) 197 | 198 | highlight_lines <- 199 | tribble( 200 | ~Club_fct, ~Goals, ~Shots, ~xend, ~yend, 201 | "RB Leipzig", 0, 10, 10, 5, 202 | "Hertha BSC", 0, 16, 16, 8 203 | ) %>% 204 | mutate(Club_fct = factor(Club_fct, levels = clubs)) 205 | 206 | highlight_arrows <- 207 | tribble( 208 | ~Club_fct, ~Goals, ~Shots, ~xend, ~yend, 209 | "RB Leipzig", 8, 17.9, 10.5, 9.2, 210 | "RB Leipzig", 4.5, 9.8, 9, 9.2, 211 | "FC Bayern München", 6.2, 27.9, 13, 11.5, 212 | "Borussia Dortmund", .5, 1.6, 4, 7.1, 213 | "VfL Wolfsburg", 1.2, 13, 11, 11, 214 | "VfL Wolfsburg", 1.1, 27.9, 12.3, 11, 215 | "FC Augsburg", 4.3, 5.6, 6, 7.7, 216 | "Hertha BSC", 7.2, 15.8, 8.5, 9.6, 217 | "Fortuna Düsseldorf", .5, 1.6, 4.6, 6.2 218 | ) %>% 219 | mutate(Club_fct = factor(Club_fct, levels = clubs)) 220 | 221 | facets_panel <- 222 | df_bl_days %>% 223 | ggplot(aes(Shots, Goals, 224 | color = Club_fct, 225 | fill = Club_fct)) + 226 | ## grey-shaded areas 227 | geom_ribbon(data = vgood, 228 | inherit.aes = F, 229 | aes(x = x, ymax = ymax, ymin = ymin), 230 | fill = "grey70", 231 | alpha = .4) + 232 | geom_ribbon(data = good, 233 | inherit.aes = F, 234 | aes(x = x, ymax = ymax, ymin = ymin), 235 | fill = "grey70", 236 | alpha = .55) + 237 | geom_ribbon(data = medium, 238 | inherit.aes = F, 239 | aes(x = x, ymax = ymax, ymin = ymin), 240 | fill = "grey70", 241 | alpha = .7) + 242 | geom_ribbon(data = bad, 243 | inherit.aes = F, 244 | aes(x = x, ymax = ymax, ymin = ymin), 245 | fill = "grey70", 246 | alpha = .85) + 247 | geom_ribbon(data = vbad, 248 | inherit.aes = F, 249 | aes(x = x, ymax = ymax, ymin = ymin), 250 | fill = "grey70", 251 | alpha = 1) + 252 | ## annotations 1/2 253 | geom_segment(data = highlight_lines, 254 | aes(xend = xend, 255 | yend = yend), 256 | color = "grey20", 257 | size = .3, 258 | linetype = "dashed") + 259 | geom_curve(data = highlight_arrows, 260 | aes(xend = xend, 261 | yend = yend), 262 | curvature = -.25, 263 | color = "grey35", ## turn off for colored version 264 | size = .45, 265 | linetype = "dotted") + 266 | ## data 267 | geom_point(data = df_bl_days %>% 268 | group_by(Club_fct) %>% 269 | summarize( 270 | avg_shots = mean(Shots), 271 | avg_goals = mean(Goals) 272 | ), 273 | aes(avg_shots, avg_goals), 274 | size = 7.5, 275 | shape = 23, 276 | color = "grey45") + 277 | geom_point(color = "white", 278 | shape = 21, 279 | alpha = .5, 280 | size = 3.5) + 281 | geom_segment(x = 30, xend = 30, 282 | y = .01, yend = 14.99, 283 | color = "grey50", 284 | size = .7) + 285 | ## annotations 2/2 286 | geom_text(data = annotations, 287 | aes(label = label), 288 | family = "Oswald", 289 | color = "grey45", ## turn off for colored version 290 | size = 3.7, 291 | lineheight = .9) + 292 | geom_point(data = highlight_points, 293 | color = "grey20", 294 | fill = NA, 295 | shape = 21, 296 | size = 4.5, 297 | stroke = .8) + 298 | facet_wrap(~ Club_fct, ncol = 6, 299 | strip.position = "bottom") + 300 | coord_cartesian(ylim = c(0, 15), clip = "off") + 301 | scale_x_continuous(breaks = seq(0, 30, by = 10), 302 | limits = c(0, NA), 303 | expand = c(0, 0)) + 304 | scale_y_continuous(breaks = seq(0, 15, by = 3), 305 | labels = glue::glue("{seq(0, 50, by = 10)}%"), 306 | limits = c(0, NA), 307 | expand = c(.01, .01), 308 | position = "right") + 309 | scale_color_manual(values = cols_all, 310 | guide = F) + 311 | scale_fill_manual(values = cols_all, 312 | guide = F) + 313 | labs(x = NULL, y = NULL) + 314 | theme(axis.text.x = element_blank(), 315 | axis.text.y = element_text(size = 12), 316 | axis.ticks = element_blank(), 317 | strip.text = element_text(color = "black", 318 | face = "bold", 319 | size = 18), 320 | panel.spacing.x = unit(40, "pt"), 321 | panel.spacing.y = unit(25, "pt"), 322 | plot.margin = margin(60, 60, 60, 10)) 323 | 324 | #### legend #### 325 | highlight <- 326 | tibble( 327 | Shots = c(14.45, 14.45, 2, 2, 9.8, 9.8, 20, 20), 328 | Goals = c(11.2, 10.9, 5, 4.7, 8.5, 8.2, 13.5, 13.2), 329 | x1 = c(NA, 14.45, NA, 2, NA, 10, NA, 20), 330 | x2 = c(NA, 14.45, NA, 2, NA, 10, NA, 20), 331 | y1 = c(NA, 9.8, NA, 4.2, NA, 7.7, NA, 12.7), 332 | y2 = c(NA, 2.41, NA, 0, NA, 5, NA, 1), 333 | face = rep(c("bold", "plain"), 4), 334 | label = c("Average Goal Efficiency", 335 | "Ratio of goals to shots based\non the mean of all 17 matches", 336 | "Low Efficiency Match", 337 | "few shots and no goals", 338 | "High Efficiency Match", 339 | "5 out of 10 shots were goals", 340 | "Low Efficiency Match", 341 | "many shots and few goals") 342 | ) 343 | 344 | legend <- 345 | df_bl_days %>% 346 | filter(Club == "Borussia Dortmund") %>% 347 | mutate( 348 | Goals = if_else(Opponent == "Leverkusen", 5, Goals), 349 | Shots = if_else(Opponent == "Leverkusen", 10, Shots), 350 | Shots = if_else(Opponent %in% c("1. FC Köln", "RB Leipzig"), 13, Shots) 351 | ) %>% 352 | ggplot(aes(Shots, Goals)) + 353 | geom_ribbon(data = vgood, 354 | inherit.aes = F, 355 | aes(x = x, ymax = ymax, ymin = ymin), 356 | fill = "grey70", 357 | alpha = .4) + 358 | geom_ribbon(data = good, 359 | inherit.aes = F, 360 | aes(x = x, ymax = ymax, ymin = ymin), 361 | fill = "grey70", 362 | alpha = .55) + 363 | geom_ribbon(data = medium, 364 | inherit.aes = F, 365 | aes(x = x, ymax = ymax, ymin = ymin), 366 | fill = "grey70", 367 | alpha = .7) + 368 | geom_ribbon(data = bad, 369 | inherit.aes = F, 370 | aes(x = x, ymax = ymax, ymin = ymin), 371 | fill = "grey70", 372 | alpha = .85) + 373 | geom_ribbon(data = vbad, 374 | inherit.aes = F, 375 | aes(x = x, ymax = ymax, ymin = ymin), 376 | fill = "grey70", 377 | alpha = 1) + 378 | geom_segment(data = highlight, 379 | aes(x = x1, xend = x2, 380 | y = y1, yend = y2)) + 381 | geom_text(data = highlight %>% filter(face == "bold"), 382 | aes(label = label), 383 | size = 5.3, 384 | family = "Oswald", 385 | fontface = "bold") + 386 | geom_text(data = highlight %>% filter(face == "plain"), 387 | aes(label = label), 388 | size = 5.3, 389 | family = "Oswald", 390 | vjust = 1, 391 | lineheight = .95) + 392 | geom_point(data = tibble(Shots = 14.45, Goals = 2.41), 393 | shape = 23, 394 | color = "grey40", 395 | fill = "grey20", 396 | size = 9) + 397 | geom_point(shape = 21, 398 | color = "white", 399 | fill = "grey40", 400 | size = 6) + 401 | geom_segment(x = 30, xend = 30, 402 | y = .01, yend = 14.99, 403 | color = "grey50", 404 | size = 1) + 405 | geom_text(data = tibble( 406 | Shots = rep(27.2, 6), 407 | Goals = c(seq(1.7, 12, length.out = 5), .7), 408 | label = c(as.character(glue::glue("{seq(0, 40, by = 10)}–{seq(10, 50, by = 10)}%")), 409 | "Goal\nEfficiency") 410 | ), 411 | aes(label = label), 412 | family = "Oswald", 413 | fontface = "bold", 414 | lineheight = .8, 415 | size = 5) + 416 | annotate("text", x = 3, y = 13.5, 417 | label = "How to Read:", 418 | family = "Oswald", 419 | size = 10, 420 | fontface = "bold") + 421 | coord_cartesian(ylim = c(0, 15), clip = "off") + 422 | scale_x_continuous(breaks = seq(0, 30, by = 5), 423 | limits = c(-1.5, 30.1), 424 | expand = c(0, 0)) + 425 | scale_y_continuous(breaks = seq(0, 15, by = 3), 426 | limits = c(-.05, NA), 427 | expand = c(.01, .01), 428 | position = "right") + 429 | scale_color_manual(values = cols_all, 430 | guide = F) + 431 | scale_fill_manual(values = cols_all, 432 | guide = F) + 433 | labs(x = "Shots", y = "Goals", 434 | caption = "Visualization by Cédric Scherer") + 435 | theme(axis.text = element_text(size = 16), 436 | axis.title = element_text(size = 20, 437 | face = "bold"), 438 | axis.ticks = element_blank(), 439 | plot.caption = element_text(size = 18, 440 | face = "bold", 441 | hjust = 0, 442 | margin = margin(120, 0, 0, 0)), 443 | plot.margin = margin(150, 80, 30, 120)) 444 | 445 | 446 | title <- ggplot(data.frame(x = 1:2, y = 1:10)) + 447 | labs(x = NULL, y = NULL, 448 | title = "RB Leipzig and Borussia Dortmund Make the Most of Their Opportunities", 449 | subtitle = "The small multiples show each club's goal:shot efficiency in the first season 2019/2020 of the 1. Bundesliga. However, while Borussia Dortmund also had very bad matches with only 2 chances,\nthe Autumn champion RB Leipzig always scored minimum one goal and shot at least ten times on the opponent's goal in all 17 matches! Of all Bundesliga clubs, RB Leipzig also shot the most goals – 8 against Mainz.") + 450 | theme(line = element_blank(), 451 | axis.text = element_blank(), 452 | axis.line.x = element_blank(), 453 | plot.title = element_text(size = 40, 454 | face = "bold", 455 | hjust = .5, 456 | margin = margin(t = 60, b = 15)), 457 | plot.subtitle = element_text(family = "Oswald", 458 | size = 22, 459 | color = "grey45", 460 | hjust = .5, 461 | lineheight = .95), 462 | plot.margin = margin(20, 100, 20, 100)) 463 | 464 | #### full panel #### 465 | bottom_row <- plot_grid(legend, facets_panel, ncol = 2, rel_widths = c(.35, .65)) 466 | plot_grid(title, bottom_row, nrow = 2, rel_heights = c(.1, .9)) 467 | 468 | ggsave(here::here("plots", "2020_01", "SWD_2020_01_SmallMultiples.pdf"), 469 | width = 32, height = 13.5, device = cairo_pdf) 470 | ``` 471 | 472 | *** 473 | 474 | ```{r session-info} 475 | sessionInfo() 476 | ``` 477 | 478 | -------------------------------------------------------------------------------- /R/SWD_2020_03_Animation.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Corona Animation" 3 | author: "Cedric Scherer" 4 | date: "29th of March 2020" 5 | output: 6 | html_document: 7 | theme: paper 8 | highlight: kate 9 | editor_options: 10 | chunk_output_type: console 11 | --- 12 | 13 | ```{r setup, include=FALSE} 14 | knitr::opts_chunk$set(echo = TRUE, warning = F) 15 | Sys.setlocale("LC_TIME", "C") 16 | ``` 17 | 18 | ```{r prep} 19 | library(tidyverse) 20 | library(lubridate) 21 | library(ggtext) 22 | library(pdftools) 23 | library(magick) 24 | library(showtext) 25 | 26 | font_add_google("Open Sans", "Open Sans") 27 | font_add_google("Overpass", "Overpass") 28 | font_add_google("Overpass Mono", "Overpass Mono") 29 | 30 | theme_set(theme_minimal(base_size = 16, base_family = "Open Sans")) 31 | theme_update(axis.text.x = element_text(size = 12), 32 | axis.text.y = element_text(size = 12, face = "bold", color = "black"), 33 | axis.ticks.x = element_line(color = "grey50", size = .4), 34 | axis.ticks.y = element_blank(), 35 | axis.ticks.length = unit(.3, "lines"), 36 | axis.title.y = element_text(face = "bold"), 37 | legend.position = "top", 38 | legend.title = element_text(size = 15, color = "grey20"), 39 | legend.text = element_text(family = "Overpass Mono", size = 10, color = "grey20"), 40 | legend.margin = margin(5, 0, 20, 0), 41 | panel.grid = element_blank(), 42 | plot.title = element_markdown(family = "Overpass", size = 34, face = "bold", 43 | color = "grey20", hjust = .5, margin = margin(20, 0, 25, 0)), 44 | plot.title.position = "plot", 45 | plot.caption = element_markdown(size = 11, color = "grey20", hjust = 1, margin = margin(35, 0, 0, 0)), 46 | plot.margin = margin(20, 50, 20, 30)) 47 | ``` 48 | 49 | 50 | ```{r data} 51 | df_corona <- readr::read_csv(here::here("data", "time-series-19-covid-combined_csv.csv")) ## first version 52 | #df_corona <- readr::read_csv("https://datahub.io/core/covid-19/r/time-series-19-covid-combined.csv") ## latest data 53 | 54 | df_corona_days <- 55 | df_corona %>% 56 | dplyr::select( 57 | date = Date, 58 | country = `Country/Region`, 59 | state = `Province/State`, 60 | deaths = Deaths 61 | ) %>% 62 | group_by(country, date) %>% 63 | summarize(deaths = sum(deaths, na.rm = T)) %>% 64 | group_by(country) %>% 65 | mutate( 66 | yday = yday(date), 67 | day = day(date), 68 | month = month(date, label = T) 69 | ) %>% 70 | arrange(country, yday) %>% 71 | mutate(daily = deaths - lag(deaths)) %>% 72 | mutate(daily = if_else(daily <= 0, NA_real_, daily)) %>% 73 | #filter(deaths > 0) %>% 74 | group_by(country) %>% 75 | mutate(n = sum(daily > 0, na.rm = T)) %>% 76 | ungroup() %>% 77 | mutate(country = case_when( 78 | country == "US" ~ "United States of America", 79 | country == "Korea, South" ~ "South Korea", 80 | TRUE ~ country 81 | )) 82 | 83 | df_corona_world <- 84 | df_corona_days %>% 85 | group_by(date, yday, day, month) %>% 86 | summarize_at( 87 | vars(c("deaths", "daily", "n")), sum, na.rm = T 88 | ) %>% 89 | mutate(country = "World") 90 | 91 | df_corona_fct <- 92 | df_corona_days %>% 93 | bind_rows(df_corona_world) %>% 94 | filter(n >= 10) %>% 95 | group_by(country) %>% 96 | mutate( 97 | max = max(daily, na.rm = T), 98 | rel = daily / max, 99 | day_first = min(yday[which(rel > 0)]) 100 | ) %>% 101 | ungroup() %>% 102 | mutate( 103 | country = factor(country), 104 | country = fct_reorder(country, -day_first) 105 | ) %>% 106 | filter(yday > min(yday)) 107 | 108 | first_day <- min(df_corona_fct$yday) 109 | latest_day <- max(df_corona_fct$yday) 110 | n_countries <- n_distinct(df_corona_fct$country) 111 | dates <- c(23, 32, 46, 61, 75, 89) 112 | dates_labs <- c("Jan 23", "Feb 1", "Feb 15", "Mar 1", "Mar 15", "Mar 29") 113 | ``` 114 | 115 | ```{r animation-ranked-by-death-toll} 116 | for(i in first_day:latest_day) { 117 | print(i) 118 | 119 | df <- 120 | df_corona_fct %>% 121 | filter(yday <= i) %>% 122 | group_by(country) %>% 123 | mutate( 124 | max = max(daily, na.rm = T), 125 | rel = daily / max, 126 | day_max = max(yday[which(rel == 1)]), 127 | sum = sum(daily, na.rm = T), 128 | lab = format(sum, big.mark = ","), 129 | lab = if_else(country == "World", glue::glue("**{lab}**"), glue::glue("{lab}")) 130 | ) %>% 131 | ungroup() %>% 132 | mutate(country = fct_reorder(country, sum)) 133 | 134 | df_dots <- 135 | df_corona_fct %>% 136 | filter(yday %in% dates) %>% 137 | mutate(country = factor(country, levels = levels(df$country))) 138 | 139 | g <- 140 | ggplot(df, 141 | aes(country, 142 | yday, 143 | group = yday, 144 | fill = rel)) + 145 | geom_point(data = df_dots, 146 | aes(country, yday), 147 | color = "grey50", 148 | shape = 20, 149 | size = .1) + 150 | geom_tile(aes(color = rel), 151 | size = .1) + 152 | geom_richtext(data = df %>% filter(yday == i), 153 | aes(country, 154 | 22, 155 | label = lab), 156 | family = "Overpass Mono", 157 | size = 3.8, 158 | fill = NA, 159 | label.color = NA, 160 | hjust = 1, 161 | vjust = .6) + 162 | geom_segment(aes(x = n_countries - .5, 163 | xend = n_countries - .5, 164 | y = 19.1, 165 | yend = i + .5), 166 | color = "grey40", 167 | size = .2) + 168 | coord_flip() + 169 | scale_x_discrete(expand = c(.001, .001)) + 170 | scale_y_continuous(expand = c(.001, 0.01), 171 | limits = c(19.1, latest_day + .5), 172 | sec.axis = dup_axis(), 173 | breaks = dates, 174 | labels = dates_labs) + 175 | rcartocolor::scale_color_carto_c(palette = "PinkYl", 176 | na.value = "#badad0", 177 | limits = c(0, 1), 178 | guide = F) + 179 | rcartocolor::scale_fill_carto_c(palette = "PinkYl", 180 | na.value = "#badad0", 181 | name = "COVID-19 death cases relative to each country's highest daily death toll so far", 182 | limits = c(0, 1), 183 | breaks = c(.01, seq(.1, 1, by = .1)), 184 | labels = scales::percent_format(accuracy = 1)) + 185 | guides(fill = guide_colorbar(title.position = "top", 186 | title.hjust = .5, 187 | label.position = "bottom", 188 | label.hjust = .5, 189 | barwidth = unit(45, "lines"), 190 | barheight = unit(.6, "lines"))) + 191 | labs(x = NULL, y = NULL, 192 | title = "The Worst Days: Peaks in Confirmed Daily Deaths Due to COVID-19 So Far", 193 | caption = "**Note:** The animation shows **countries with at least 10 deaths** due to the corona virus disease 2019 (COVID-19). The color intensity
for each day and country is estimated as the number of deaths on this particular day divided by the highest daily death toll so far.

**Visualization: Cédric Scherer • Data: Johns Hopkins University Center for Systems Science and Engineering (CSSE) via datahub.io**") 194 | 195 | g_daily <- 196 | g + 197 | geom_text(data = df %>% filter(yday == i), 198 | aes(country, 199 | yday, 200 | label = daily), 201 | family = "Overpass Mono", 202 | color = "black", 203 | fontface = "bold", 204 | size = 1.9, 205 | hjust = .5) 206 | 207 | ggsave(here::here("plots", "2020_03", "series_sum", glue::glue("corona_yday_{i}.pdf")), 208 | width = 18.2, height = 12.2, device = cairo_pdf) 209 | 210 | if(i == latest_day) { 211 | g_latest <- 212 | g + 213 | geom_tile(data = df %>% filter(rel == 1), 214 | color = "black", 215 | fill = NA, 216 | size = .5) + 217 | geom_text(data = df %>% filter(yday == i), 218 | aes(country, 219 | yday, 220 | label = daily), 221 | family = "Overpass Mono", 222 | color = "grey40", 223 | size = 1.9, 224 | hjust = .5) + 225 | geom_text(data = df %>% filter(rel == 1), 226 | aes(country, 227 | yday, 228 | label = daily), 229 | family = "Overpass Mono", 230 | fontface = "bold", 231 | size = 1.9, 232 | hjust = .5) 233 | 234 | ggsave(here::here("plots", "2020_03", "series_sum", glue::glue("corona_yday_latest.pdf")), 235 | width = 18.2, height = 12.2, device = cairo_pdf) 236 | } 237 | } 238 | 239 | ## convert pdf's to png's 240 | setwd(here::here("plots", "2020_03", "series_sum")) 241 | pdfs <- list.files(here::here("plots", "2020_03", "series_sum"), pattern = "*.pdf") 242 | 243 | for(pdf in pdfs) { 244 | pdf_convert(pdf = here::here("plots", "2020_03", "series_sum", pdf), 245 | format = "png", dpi = 200) 246 | } 247 | 248 | ## convert png's to gif 249 | system("magick.exe -delay 70 *.png -delay 700 *latest_1.png -loop 0 corona_series_sum.gif") 250 | ``` 251 | 252 | 253 | ```{r animation-ranked-by-begin} 254 | for(i in first_day:latest_day) { 255 | print(i) 256 | 257 | df <- 258 | df_corona_fct %>% 259 | filter(yday <= i) %>% 260 | group_by(country) %>% 261 | mutate( 262 | max = max(daily, na.rm = T), 263 | rel = daily / max, 264 | day_max = max(yday[which(rel == 1)]), 265 | sum = sum(daily, na.rm = T), 266 | lab = format(sum, big.mark = ","), 267 | lab = if_else(country == "World", glue::glue("**{lab}**"), glue::glue("{lab}")) 268 | ) %>% 269 | ungroup() 270 | 271 | g <- 272 | ggplot(df, 273 | aes(country, 274 | yday, 275 | group = yday, 276 | fill = rel)) + 277 | geom_point(data = df_corona_fct %>% filter(yday %in% dates), 278 | aes(country, yday), 279 | color = "grey50", 280 | shape = 20, 281 | size = .01) + 282 | geom_tile(aes(color = rel), 283 | size = .1) + 284 | geom_richtext(data = df %>% filter(yday == i), 285 | aes(country, 286 | 22, 287 | label = lab), 288 | family = "Overpass Mono", 289 | size = 3.8, 290 | fill = NA, 291 | label.color = NA, 292 | hjust = 1, 293 | vjust = .6) + 294 | geom_segment(aes(x = n_countries - .5, 295 | xend = n_countries - .5, 296 | y = 19.1, 297 | yend = i + .5), 298 | color = "black", 299 | size = .2) + 300 | coord_flip() + 301 | scale_x_discrete(expand = c(.001, 0.01)) + 302 | scale_y_continuous(expand = c(.001, 0.01), 303 | limits = c(19.1, latest_day + .5), 304 | sec.axis = dup_axis(), 305 | breaks = dates, 306 | labels = dates_labs) + 307 | rcartocolor::scale_color_carto_c(palette = "PinkYl", 308 | na.value = "#badad0", 309 | limits = c(0, 1), 310 | guide = F) + 311 | rcartocolor::scale_fill_carto_c(palette = "PinkYl", 312 | na.value = "#badad0", 313 | name = "COVID-19 death cases relative to each country's highest daily death toll so far", 314 | limits = c(0, 1), 315 | breaks = c(.01, seq(.1, 1, by = .1)), 316 | labels = scales::percent_format(accuracy = 1)) + 317 | guides(fill = guide_colorbar(title.position = "top", 318 | title.hjust = .5, 319 | label.position = "bottom", 320 | label.hjust = .5, 321 | barwidth = unit(45, "lines"), 322 | barheight = unit(.6, "lines"))) + 323 | labs(x = NULL, y = NULL, 324 | title = "The Worst Days: Peaks in Confirmed Daily Deaths Due to COVID-19 So Far", 325 | caption = "**Note:** The animation shows **countries with at least 10 deaths** due to the corona virus disease 2019 (COVID-19). The color intensity
for each day and country is estimated as the number of deaths on this particular day divided by the highest daily death toll so far.

**Visualization: Cédric Scherer • Data: Johns Hopkins University Center for Systems Science and Engineering (CSSE) via datahub.io**") 326 | 327 | g_daily <- 328 | g + 329 | geom_text(data = df %>% filter(yday == i), 330 | aes(country, 331 | yday, 332 | label = daily), 333 | family = "Overpass Mono", 334 | color = "black", 335 | fontface = "bold", 336 | size = 1.9, 337 | hjust = .5) 338 | 339 | ggsave(here::here("plots", "2020_03", "series_begin", glue::glue("corona_yday_{i}.pdf")), 340 | width = 18.2, height = 12.2, device = cairo_pdf) 341 | 342 | if(i == latest_day) { 343 | g_latest <- 344 | g + 345 | geom_tile(data = df %>% filter(rel == 1), 346 | color = "black", 347 | fill = NA, 348 | size = .5) + 349 | geom_text(data = df %>% filter(yday == i), 350 | aes(country, 351 | yday, 352 | label = daily), 353 | family = "Overpass Mono", 354 | color = "grey20", 355 | size = 1.9, 356 | hjust = .5) + 357 | geom_text(data = df %>% filter(rel == 1), 358 | aes(country, 359 | yday, 360 | label = daily), 361 | family = "Overpass Mono", 362 | fontface = "bold", 363 | size = 1.9, 364 | hjust = .5) 365 | 366 | ggsave(here::here("plots", "2020_03", "series_begin", glue::glue("corona_yday_latest.pdf")), 367 | width = 18.2, height = 12.2, device = cairo_pdf) 368 | } 369 | } 370 | 371 | 372 | ## convert pdf's to png's 373 | setwd(here::here("plots", "2020_03", "series_begin")) 374 | pdfs <- list.files(here::here("plots", "2020_03", "series_begin"), pattern = "*.pdf") 375 | 376 | for(pdf in pdfs) { 377 | pdf_convert(pdf = here::here("plots", "2020_03", "series_begin", pdf), 378 | format = "png", dpi = 200) 379 | } 380 | 381 | ## convert png's to gif 382 | system("magick.exe -delay 70 *.png -delay 700 *latest_1.png -loop 0 corona_series_begin.gif") 383 | ``` 384 | 385 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 |

2 |  #SWDchallenge Contributions  3 |

4 | 5 |
6 | 7 |     8 | Blog    9 | Email    10 | Twitter    11 | Behance    12 | LinkedIn    13 | BuyMeACoffee    14 | 15 | My contributions to the [#SWDchallenge](http://www.storytellingwithdata.com/swdchallenge). Feedback is very welcome via [Twitter](https://twitter.com/cedscherer) or [email](mailto:cedricphilippscherer@gmail.com). 16 | 17 |
18 | 19 | *** 20 | 21 | ### March 2020 - [Get Animated!](https://github.com/Z3tt/SWDchallenge/tree/master/plots/2020_03) 22 | ![./plots/2020_03/corona_begin.mp4](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2020_03/corona_begin.gif) 23 | 24 | *** 25 | 26 | ### January 2020 - [Small Multiples](https://github.com/Z3tt/SWDchallenge/tree/master/plots/2020_01) 27 | ![./plots/2020_01/SWD_2020_01_SmallMultiples_grey.png](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2020_01/SWD_2020_01_SmallMultiples_grey.png) 28 | 29 | *** 30 | 31 | ### September 2019 - [Visualizing Uncertainty](https://github.com/Z3tt/SWDchallenge/tree/master/plots/2019_09) 32 | ![./plots/2019_09/SWD_2019_09_Uncertainty.png](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2019_09/SWD_2019_09_Uncertainty.png) 33 | 34 | *** 35 | 36 |
37 |

Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

38 |
39 | 40 |
41 |
42 | Buy Me A Coffee 43 |

44 |
45 | -------------------------------------------------------------------------------- /SWD.Rproj: -------------------------------------------------------------------------------- 1 | Version: 1.0 2 | 3 | RestoreWorkspace: Default 4 | SaveWorkspace: Default 5 | AlwaysSaveHistory: Default 6 | 7 | EnableCodeIndexing: Yes 8 | UseSpacesForTab: Yes 9 | NumSpacesForTab: 2 10 | Encoding: UTF-8 11 | 12 | RnwWeave: Sweave 13 | LaTeX: pdfLaTeX 14 | -------------------------------------------------------------------------------- /data/D1.csv: -------------------------------------------------------------------------------- 1 | Div,Date,Time,HomeTeam,AwayTeam,FTHG,FTAG,FTR,HTHG,HTAG,HTR,HS,AS,HST,AST,HF,AF,HC,AC,HY,AY,HR,AR,B365H,B365D,B365A,BWH,BWD,BWA,IWH,IWD,IWA,PSH,PSD,PSA,WHH,WHD,WHA,VCH,VCD,VCA,MaxH,MaxD,MaxA,AvgH,AvgD,AvgA,B365>2.5,B365<2.5,P>2.5,P<2.5,Max>2.5,Max<2.5,Avg>2.5,Avg<2.5,AHh,B365AHH,B365AHA,PAHH,PAHA,MaxAHH,MaxAHA,AvgAHH,AvgAHA,B365CH,B365CD,B365CA,BWCH,BWCD,BWCA,IWCH,IWCD,IWCA,PSCH,PSCD,PSCA,WHCH,WHCD,WHCA,VCCH,VCCD,VCCA,MaxCH,MaxCD,MaxCA,AvgCH,AvgCD,AvgCA,B365C>2.5,B365C<2.5,PC>2.5,PC<2.5,MaxC>2.5,MaxC<2.5,AvgC>2.5,AvgC<2.5,AHCh,B365CAHH,B365CAHA,PCAHH,PCAHA,MaxCAHH,MaxCAHA,AvgCAHH,AvgCAHA 2 | D1,16/08/2019,19:30,Bayern Munich,Hertha,2,2,D,1,2,A,17,6,7,3,6,17,12,0,3,3,0,0,1.14,8,15,1.18,7,16,1.25,6.1,11,1.19,7.73,15.3,1.18,7.5,15,1.18,8,15,1.25,8.3,17.5,1.18,7.55,15.04,1.33,3.4,1.36,3.35,1.4,3.4,1.34,3.24,-2,1.8,2,1.85,2.07,2.1,2.11,1.84,2.04,1.14,8,15,1.18,8,13,1.25,6.1,11,1.18,8.49,17.38,1.15,8.5,17,1.17,8,18,1.25,9.1,19.25,1.17,8,15.67,1.3,3.5,1.32,3.62,1.4,3.62,1.31,3.4,-2.25,2.03,1.9,1.99,1.93,2.04,1.93,1.98,1.91 3 | D1,17/08/2019,14:30,Dortmund,Augsburg,5,1,H,1,1,D,23,5,10,1,8,6,10,0,0,0,0,0,1.2,7,13,1.22,6.5,12.5,1.25,6.1,11,1.23,6.76,13.52,1.2,6.5,15,1.22,6.5,15,1.25,7.15,17,1.22,6.62,13.38,1.44,2.75,1.44,2.95,1.46,2.95,1.43,2.79,-2,2.02,1.77,2.03,1.88,2.1,1.9,2.02,1.85,1.12,8,26,1.16,8,16.5,1.2,6.5,15,1.16,8.37,20.11,1.2,6.5,15,1.15,8.5,20,1.2,8.8,26,1.16,8.1,18.29,1.3,3.5,1.33,3.5,1.4,3.6,1.32,3.31,-2.25,1.92,2.01,1.92,2,1.98,2.04,1.91,1.97 4 | D1,17/08/2019,14:30,Freiburg,Mainz,3,0,H,0,0,D,19,19,8,5,6,15,5,5,1,3,0,0,2.25,3.25,3.4,2.2,3.3,3.4,2.15,3.4,3.35,2.23,3.45,3.44,2.2,3.3,3.4,2.2,3.4,3.4,2.26,3.49,3.65,2.2,3.37,3.36,1.9,1.9,1.95,1.95,2,1.95,1.93,1.88,-0.25,1.94,1.99,1.93,2,1.94,2.01,1.91,1.98,2.55,3.3,2.7,2.5,3.3,2.85,2.6,3.3,2.7,2.74,3.3,2.77,2.2,3.3,3.4,2.63,3.3,2.8,2.74,3.38,2.96,2.61,3.29,2.78,1.9,1.9,1.98,1.92,2.01,1.96,1.93,1.89,0,1.92,2.01,1.94,1.97,1.97,2.06,1.9,1.99 5 | D1,17/08/2019,14:30,Leverkusen,Paderborn,3,2,H,2,2,D,13,11,4,6,8,9,6,6,2,0,0,0,1.25,6,12,1.3,5.5,10,1.27,5.8,10.5,1.29,6.07,10.57,1.27,5.8,11,1.29,6,10.5,1.31,6.4,12.25,1.28,5.97,10.27,1.36,3.2,1.39,3.2,1.45,3.25,1.38,3.03,-1.75,1.98,1.95,1.97,1.94,1.99,1.97,1.95,1.93,1.22,6.5,11,1.25,6.25,11,1.27,5.8,10.5,1.27,6.69,10.45,1.25,6,12,1.25,6.5,11,1.29,7.05,13,1.25,6.52,10.7,1.28,3.75,1.3,3.73,1.35,3.85,1.29,3.58,-2,2.07,1.86,2.05,1.86,2.15,1.91,2.03,1.85 6 | D1,17/08/2019,14:30,Werder Bremen,Fortuna Dusseldorf,1,3,A,0,1,A,23,12,10,7,8,13,14,5,0,2,0,0,1.75,3.75,4.75,1.75,4,4.4,1.7,4,4.7,1.75,4.05,4.68,1.73,3.9,4.75,1.75,4,4.6,1.8,4.05,4.95,1.74,3.93,4.57,1.66,2.2,1.72,2.22,1.72,2.28,1.67,2.21,-0.75,1.99,1.94,1.99,1.93,1.99,1.95,1.96,1.92,1.66,4.2,4.5,1.7,4,4.75,1.65,4.1,5,1.7,4.15,4.9,1.7,4,4.75,1.7,4.2,4.8,1.76,4.32,5.1,1.69,4.07,4.79,1.66,2.2,1.68,2.3,1.69,2.38,1.65,2.26,-0.75,1.92,2.01,1.92,2,1.95,2.11,1.89,2 7 | D1,17/08/2019,14:30,Wolfsburg,FC Koln,2,1,H,1,0,H,14,11,5,2,14,18,2,6,1,3,0,0,1.95,3.5,4,1.91,3.6,4,1.9,3.8,3.85,1.91,3.96,3.98,1.88,3.8,3.9,1.9,3.9,3.9,1.97,3.96,4.1,1.91,3.74,3.91,1.66,2.2,1.69,2.28,1.72,2.29,1.67,2.21,-0.5,1.92,2.01,1.91,2.01,1.95,2.01,1.9,1.98,2.05,3.4,3.6,2.05,3.5,3.6,2.1,3.6,3.45,2.17,3.52,3.51,1.91,3.75,3.9,2.15,3.7,3.4,2.17,3.7,4.1,2.07,3.53,3.56,1.72,2.1,1.73,2.21,1.73,2.31,1.68,2.19,-0.5,2.11,1.82,2.17,1.77,2.17,1.86,2.09,1.81 8 | D1,17/08/2019,17:30,M'gladbach,Schalke 04,0,0,D,0,0,D,16,8,4,1,8,10,8,3,3,2,0,0,2,3.5,3.75,2.1,3.5,3.5,2.05,3.45,3.65,2.09,3.51,3.76,2.05,3.4,3.7,2.1,3.5,3.6,2.11,3.6,3.76,2.06,3.49,3.6,1.8,2,1.82,2.08,1.83,2.11,1.78,2.04,-0.5,2.08,1.85,2.09,1.83,2.09,1.86,2.06,1.82,2.15,3.6,3.2,2.15,3.4,3.4,2,3.6,3.6,2.31,3.41,3.37,2.15,3.5,3.3,2.25,3.6,3.2,2.31,3.68,3.7,2.2,3.43,3.35,1.9,1.9,1.9,2,1.92,2.12,1.84,1.97,-0.25,1.99,1.94,1.98,1.94,2.02,2.13,1.93,1.95 9 | D1,18/08/2019,14:30,Ein Frankfurt,Hoffenheim,1,0,H,1,0,H,17,10,8,1,16,9,10,5,3,1,0,0,2.25,3.6,3,2.35,3.5,2.95,2.3,3.75,2.9,2.33,3.72,3.01,2.3,3.6,3,2.3,3.7,2.9,2.45,3.8,3.04,2.32,3.65,2.92,1.53,2.5,1.58,2.51,1.58,2.6,1.54,2.46,-0.25,2.04,1.89,2.04,1.88,2.06,1.91,2.02,1.86,2.05,3.75,3.3,2.2,3.75,3,2.1,3.7,3.25,2.13,3.81,3.36,2.05,3.6,3.5,2.15,3.8,3.3,2.2,3.85,3.76,2.12,3.74,3.25,1.5,2.62,1.53,2.64,1.53,2.88,1.5,2.57,-0.25,1.88,2.05,1.86,2.06,1.9,2.2,1.86,2.03 10 | D1,18/08/2019,17:00,Union Berlin,RB Leipzig,0,4,A,0,3,A,13,14,2,8,14,5,3,6,1,0,0,0,5,3.8,1.7,4.4,4.1,1.72,4.65,4,1.7,4.77,4.21,1.71,4.75,4,1.7,4.6,4.1,1.73,5,4.21,1.76,4.63,4.02,1.72,1.72,2.1,1.75,2.18,1.76,2.23,1.71,2.13,0.75,1.98,1.95,1.98,1.93,1.99,1.97,1.96,1.92,4.5,4,1.72,4.75,4,1.7,5,3.8,1.7,4.54,4.02,1.78,4.75,3.9,1.73,4.5,4,1.8,5.1,4.15,1.82,4.54,3.95,1.75,1.66,2.2,1.66,2.32,1.69,2.37,1.64,2.25,0.75,1.92,2.01,1.91,2.01,2.08,2.04,1.92,1.97 11 | D1,23/08/2019,19:30,FC Koln,Dortmund,1,3,A,1,0,H,13,14,1,6,11,10,7,8,2,1,0,0,6.5,4.75,1.44,6.5,4.75,1.42,6.5,4.3,1.5,6.44,4.79,1.5,6,4.6,1.5,6.25,4.8,1.5,6.6,5,1.53,6.18,4.74,1.48,1.44,2.75,1.46,2.86,1.48,2.86,1.45,2.73,1.25,1.92,2.01,1.87,2.05,1.92,2.07,1.86,2.02,5.5,4.75,1.5,6,4.75,1.48,6.5,4.3,1.5,6.21,4.57,1.55,6,4.6,1.5,5.75,4.6,1.55,6.5,4.88,1.57,5.87,4.61,1.52,1.44,2.75,1.45,2.9,1.48,3.05,1.42,2.83,1,2.06,1.87,2.03,1.88,2.09,1.89,2.05,1.84 12 | D1,24/08/2019,14:30,Augsburg,Union Berlin,1,1,D,0,0,D,12,13,4,1,16,19,3,4,3,1,0,1,2.2,3.4,3.3,2.2,3.3,3.2,2.2,3.4,3.25,2.31,3.34,3.37,2.25,3.3,3.3,2.25,3.4,3.3,2.31,3.45,3.45,2.24,3.32,3.31,1.9,1.9,2.03,1.87,2.03,1.92,1.95,1.86,-0.25,1.97,1.96,1.98,1.93,1.99,1.97,1.95,1.93,2.3,3.4,3,2.35,3.4,3,2.2,3.4,3.3,2.5,3.35,3.02,2.35,3.4,3,2.4,3.4,3,2.52,3.54,3.32,2.37,3.38,3.03,1.8,2,1.86,2.04,1.92,2.15,1.83,1.99,-0.25,2.08,1.85,2.14,1.79,2.16,1.94,2.06,1.83 13 | D1,24/08/2019,14:30,Fortuna Dusseldorf,Leverkusen,1,3,A,0,3,A,11,11,6,7,14,10,1,5,3,2,0,0,4.75,4,1.7,4.25,4,1.72,4.35,4.25,1.7,4.45,4.32,1.74,4.33,4.2,1.73,4.3,4.4,1.73,4.75,4.4,1.78,4.36,4.2,1.72,1.44,2.75,1.47,2.84,1.5,2.84,1.46,2.69,0.75,2,1.93,1.98,1.94,2.01,1.94,1.96,1.91,5,4.33,1.61,4.75,4.5,1.62,4.3,4,1.75,4.8,4.59,1.65,5.25,4.33,1.6,5,4.5,1.62,5.45,4.65,1.75,4.8,4.43,1.63,1.44,2.75,1.47,2.84,1.49,2.9,1.45,2.72,1,1.87,2.06,1.86,2.06,1.96,2.28,1.83,2.05 14 | D1,24/08/2019,14:30,Hoffenheim,Werder Bremen,3,2,H,0,1,A,10,18,3,6,13,15,3,6,2,5,0,1,1.85,3.6,4.2,1.85,3.75,3.75,1.87,4,3.75,1.9,4.09,3.88,1.85,3.9,3.9,1.9,4,3.9,1.92,4.1,4.2,1.88,3.92,3.83,1.5,2.62,1.49,2.78,1.53,2.78,1.49,2.62,-0.5,1.88,2.05,1.9,2.02,1.9,2.06,1.87,2.01,2,3.6,3.6,2.1,3.6,3.4,2,3.6,3.6,2.15,3.65,3.43,2.1,3.5,3.5,2.2,3.6,3.2,2.22,3.9,3.75,2.11,3.6,3.4,1.57,2.37,1.57,2.51,1.6,2.58,1.54,2.45,-0.25,1.8,2,1.87,2.04,1.93,2.28,1.86,2.03 15 | D1,24/08/2019,14:30,Mainz,M'gladbach,1,3,A,1,1,D,21,15,4,6,12,14,3,5,2,2,0,0,2.9,3.4,2.4,2.85,3.4,2.35,2.85,3.45,2.45,2.85,3.48,2.56,2.8,3.4,2.5,2.8,3.4,2.55,3.25,3.55,2.59,2.86,3.42,2.46,1.8,2,1.85,2.05,1.85,2.09,1.8,2.03,0,2.07,1.86,2.07,1.85,2.1,1.87,2.06,1.83,2.62,3.4,2.7,2.65,3.4,2.65,2.8,3.4,2.5,2.67,3.56,2.67,2.62,3.5,2.62,2.63,3.5,2.63,3.25,3.6,2.74,2.68,3.47,2.6,1.72,2.1,1.76,2.15,1.86,2.19,1.76,2.07,0,1.98,1.95,1.96,1.96,2.01,1.99,1.96,1.92 16 | D1,24/08/2019,14:30,Paderborn,Freiburg,1,3,A,1,2,A,15,9,2,4,20,6,9,5,3,1,0,0,2.37,3.5,2.9,2.35,3.5,2.75,2.6,3.3,2.7,2.38,3.7,2.95,2.35,3.6,2.88,2.38,3.7,2.88,2.69,3.75,2.95,2.38,3.6,2.84,1.57,2.37,1.61,2.44,1.8,2.44,1.61,2.31,-0.25,2.07,1.86,2.07,1.85,2.13,1.87,2.05,1.83,2.3,3.75,2.75,2.35,3.7,2.8,2.5,3.3,2.85,2.37,3.82,2.88,2.35,3.7,2.8,2.45,3.75,2.75,2.69,3.86,3,2.37,3.7,2.83,1.44,2.75,1.52,2.67,1.8,2.75,1.51,2.55,-0.25,2.13,1.81,2.08,1.84,2.13,1.86,2.08,1.82 17 | D1,24/08/2019,17:30,Schalke 04,Bayern Munich,0,3,A,0,1,A,9,10,2,6,11,10,3,4,0,0,0,0,9,4.75,1.36,7.75,4.75,1.36,6.5,4.3,1.5,8.69,5.05,1.39,8.5,5,1.36,8,5,1.4,9,5.3,1.5,8.12,4.93,1.38,1.57,2.37,1.63,2.39,1.66,2.41,1.59,2.35,1.25,2.06,1.87,2.09,1.83,2.09,1.89,2.06,1.83,11,5.25,1.3,9,5.25,1.33,6.5,4.3,1.5,10.41,5.56,1.33,10,5.5,1.3,10,5.5,1.33,11,5.75,1.5,9.57,5.32,1.33,1.44,2.75,1.49,2.76,1.63,2.85,1.48,2.65,1.5,2.05,1.88,2.06,1.85,2.07,2.35,1.98,1.9 18 | D1,25/08/2019,14:30,RB Leipzig,Ein Frankfurt,2,1,H,1,0,H,13,11,5,5,10,13,4,1,2,3,0,0,1.5,4.5,6,1.45,4.6,6,1.5,4.7,5.9,1.51,4.75,6.28,1.5,4.6,6,1.5,4.6,6.25,1.55,4.9,6.6,1.49,4.63,6.06,1.5,2.62,1.52,2.68,1.53,2.69,1.5,2.59,-1,1.83,2.1,1.83,2.09,1.85,2.12,1.81,2.07,1.4,4.75,7,1.44,4.75,7,1.5,4.6,6,1.43,5.13,7.1,1.42,5,7,1.44,5,7,1.5,5.15,7.5,1.43,4.9,6.85,1.4,3,1.44,2.95,1.5,3,1.43,2.81,-1.25,1.91,2.02,1.92,2,2.08,2.02,1.93,1.96 19 | D1,25/08/2019,17:00,Hertha,Wolfsburg,0,3,A,0,1,A,8,9,2,4,15,11,2,5,1,0,0,0,2.4,3.4,2.9,2.4,3.5,2.7,2.5,3.4,2.75,2.49,3.49,2.93,2.4,3.5,2.88,2.45,3.5,2.9,2.5,3.72,3.05,2.42,3.46,2.87,1.72,2.1,1.78,2.13,1.79,2.17,1.75,2.09,-0.25,2.11,1.82,2.14,1.79,2.14,1.84,2.1,1.8,2.4,3.4,2.9,2.45,3.5,2.8,2.5,3.4,2.75,2.57,3.47,2.88,2.4,3.5,2.88,2.55,3.5,2.8,2.64,3.5,2.97,2.5,3.43,2.81,1.72,2.1,1.77,2.15,1.82,2.19,1.75,2.09,0,1.87,2.06,1.85,2.07,1.9,2.08,1.85,2.04 20 | D1,30/08/2019,19:30,M'gladbach,RB Leipzig,1,3,A,0,1,A,11,14,3,6,17,19,9,5,3,2,0,0,3.2,4,2.05,3.2,3.8,2.1,3.4,3.5,2.1,3.31,3.81,2.15,3.25,3.75,2.1,3.25,3.8,2.15,3.45,4,2.17,3.28,3.76,2.11,1.57,2.37,1.63,2.4,1.65,2.45,1.6,2.35,0.25,2.03,1.9,2.03,1.88,2.06,1.91,2.02,1.87,3.1,3.6,2.2,3.2,3.8,2.1,3.3,3.7,2.1,3.1,3.72,2.28,3,3.8,2.2,3,3.8,2.3,3.3,4.06,2.3,3.1,3.71,2.2,1.53,2.5,1.57,2.53,1.63,2.58,1.56,2.42,0.25,1.93,2,1.93,2,2.03,2.02,1.92,1.97 21 | D1,31/08/2019,14:30,Bayern Munich,Mainz,6,1,H,2,1,H,19,7,10,4,16,12,10,1,3,3,0,0,1.08,11,26,1.09,10.5,26,1.12,9,20,1.1,11.84,28.11,1.07,11,34,1.06,12,36,1.12,12.75,38,1.09,11.05,28.84,1.25,4,1.24,4.34,1.27,4.34,1.24,3.93,-2.75,1.9,2.03,1.9,2.02,1.92,2.03,1.89,1.99,1.08,11,26,1.09,10.5,26,1.12,9,20,1.11,11.6,25.42,1.08,11,26,1.1,12,23,1.12,12.25,31,1.1,10.73,24.26,1.22,4.33,1.22,4.61,1.27,4.75,1.21,4.32,-2.75,2.05,1.88,2.03,1.88,2.11,1.9,2.02,1.86 22 | D1,31/08/2019,14:30,Freiburg,FC Koln,1,2,A,1,0,H,14,9,1,3,6,15,5,6,0,2,0,0,2.37,3.5,3,2.45,3.5,2.8,2.45,3.5,2.8,2.46,3.48,2.97,2.45,3.4,2.88,2.45,3.5,2.9,2.54,3.55,3,2.45,3.45,2.87,1.72,2.1,1.79,2.12,1.8,2.19,1.73,2.11,-0.25,2.05,1.75,2.12,1.8,2.17,1.83,2.12,1.78,2.6,3.4,2.62,2.55,3.5,2.7,2.6,3.45,2.65,2.68,3.54,2.68,2.62,3.5,2.62,2.63,3.5,2.63,2.68,3.55,2.85,2.59,3.46,2.68,1.66,2.2,1.71,2.23,1.75,2.26,1.69,2.17,0,1.97,1.96,1.96,1.96,2.02,1.98,1.93,1.95 23 | D1,31/08/2019,14:30,Leverkusen,Hoffenheim,0,0,D,0,0,D,20,6,2,1,7,11,19,0,2,2,0,0,1.53,4.75,5.25,1.55,5,5,1.57,4.75,5,1.56,5.08,5.12,1.53,4.8,5.25,1.55,4.8,5.25,1.58,5.1,5.45,1.55,4.88,5.08,1.36,3.2,1.38,3.22,1.38,3.4,1.35,3.17,-1,1.9,2.03,1.89,2.02,1.92,2.03,1.87,2,1.45,5,6.5,1.55,5,5,1.57,4.6,5,1.5,4.96,6.07,1.5,4.8,5.8,1.5,5,6,1.57,5.25,6.5,1.5,4.93,5.63,1.4,3,1.42,3.03,1.42,3.25,1.38,3,-1.25,2.01,1.92,2.01,1.91,2.1,1.94,2.02,1.87 24 | D1,31/08/2019,14:30,Schalke 04,Hertha,3,0,H,1,0,H,9,9,2,3,13,9,5,3,1,1,0,0,2.1,3.6,3.4,2.1,3.5,3.5,2.1,3.5,3.45,2.16,3.46,3.59,2.15,3.4,3.5,2.15,3.5,3.5,2.19,3.6,3.7,2.12,3.45,3.51,1.9,1.9,1.87,2.03,1.9,2.04,1.83,1.98,-0.25,1.86,2.07,1.86,2.05,1.88,2.08,1.84,2.04,2,3.6,3.6,2.1,3.5,3.5,2.05,3.55,3.5,2.13,3.57,3.57,2.05,3.6,3.5,2.1,3.6,3.5,2.15,3.68,3.75,2.08,3.51,3.56,1.8,2,1.84,2.06,1.9,2.08,1.82,2,-0.25,1.84,2.09,1.84,2.08,1.86,2.11,1.81,2.08 25 | D1,31/08/2019,14:30,Wolfsburg,Paderborn,1,1,D,0,1,A,15,7,5,3,8,12,8,3,0,3,0,0,1.44,5,6,1.42,5,6.75,1.45,4.8,6.5,1.47,4.85,6.77,1.44,4.8,6.5,1.45,5,6.5,1.49,5.05,7,1.46,4.85,6.46,1.36,3.2,1.4,3.14,1.43,3.2,1.39,2.96,-1.25,2,1.93,2,1.93,2.02,1.95,1.97,1.91,1.44,4.75,6,1.42,5,6.75,1.45,4.8,6.5,1.48,4.8,6.73,1.47,4.75,6.5,1.5,4.8,6.25,1.5,5.05,7,1.46,4.83,6.41,1.36,3.2,1.44,2.95,1.44,3.2,1.4,2.94,-1.25,2.01,1.92,2,1.92,2.04,2.06,1.97,1.91 26 | D1,31/08/2019,17:30,Union Berlin,Dortmund,3,1,H,1,1,D,15,13,7,2,13,2,7,4,0,0,0,0,10,5.75,1.28,9.75,5.75,1.3,9.1,5.7,1.3,8.57,5.56,1.35,9,5.5,1.32,9.5,5.5,1.33,10,6,1.36,8.99,5.56,1.32,1.44,2.75,1.49,2.75,1.49,2.88,1.46,2.7,1.5,1.94,1.99,1.94,1.98,2.02,1.99,1.96,1.92,8,5,1.36,7.5,5,1.4,9.1,5.7,1.3,8.01,5.4,1.4,8,5,1.38,7.5,5.25,1.4,9.1,5.7,1.43,7.6,5.17,1.38,1.44,2.75,1.45,2.89,1.47,2.96,1.44,2.77,1.5,1.72,2.07,1.81,2.11,1.93,2.16,1.81,2.06 27 | D1,01/09/2019,14:30,Werder Bremen,Augsburg,3,2,H,2,1,H,15,12,5,6,9,11,4,2,1,4,0,1,1.72,4,4.5,1.65,4.1,5,1.7,4.15,4.55,1.72,4.02,4.98,1.7,4,4.8,1.7,4.1,4.8,1.74,4.25,5,1.7,4.03,4.77,1.61,2.3,1.61,2.44,1.67,2.45,1.59,2.36,-0.75,1.91,2.02,1.94,1.97,1.96,2.03,1.9,1.98,1.5,4.2,6.5,1.53,4.5,5.75,1.7,3.9,4.8,1.57,4.49,5.72,1.5,4.33,6.5,1.55,4.6,5.75,1.7,4.6,7.2,1.54,4.41,5.85,1.44,2.75,1.47,2.84,1.55,2.84,1.47,2.66,-1,1.9,2.03,1.91,2.01,2.15,2.05,1.89,1.99 28 | D1,01/09/2019,17:00,Ein Frankfurt,Fortuna Dusseldorf,2,1,H,0,1,A,15,14,8,4,13,15,4,1,2,4,0,0,1.66,4,4.75,1.7,4,4.75,1.7,4.15,4.5,1.69,4.18,4.97,1.7,4,4.8,1.7,4.2,4.75,1.73,4.25,5.05,1.69,4.08,4.77,1.57,2.37,1.57,2.52,1.58,2.55,1.55,2.43,-0.75,1.88,2.05,1.88,2.03,1.9,2.07,1.87,2.01,1.57,4.2,5.25,1.57,4.25,5.5,1.6,4,5.5,1.62,4.29,5.5,1.57,4.2,5.8,1.6,4.4,5.5,1.63,4.45,5.95,1.59,4.25,5.43,1.5,2.62,1.51,2.69,1.56,2.76,1.51,2.53,-1,2.02,1.91,2.02,1.9,2.03,2,1.99,1.89 29 | D1,13/09/2019,19:30,Fortuna Dusseldorf,Wolfsburg,1,1,D,1,1,D,12,15,3,6,7,14,3,8,0,2,0,0,3.1,3.5,2.25,2.95,3.6,2.3,3.05,3.4,2.3,3.08,3.69,2.3,3,3.7,2.25,3,3.7,2.3,3.17,3.8,2.35,3.03,3.62,2.28,1.66,2.2,1.67,2.31,1.7,2.35,1.65,2.24,0.25,1.92,2.01,1.91,2.01,1.95,2.03,1.9,1.98,3.1,3.6,2.2,3.1,3.7,2.2,3.05,3.4,2.3,3.18,3.78,2.22,3.1,3.7,2.2,3.1,3.75,2.2,3.2,3.8,2.3,3.09,3.68,2.22,1.66,2.2,1.7,2.25,1.72,2.35,1.67,2.22,0.25,1.96,1.97,1.97,1.94,1.98,1.98,1.94,1.94 30 | D1,14/09/2019,14:30,Augsburg,Ein Frankfurt,2,1,H,2,0,H,9,23,6,3,8,8,2,11,2,1,0,0,3.5,3.6,2.05,3.5,3.75,2,3.4,3.5,2.1,3.6,3.8,2.05,3.5,3.6,2.05,3.3,3.8,2.1,3.65,3.85,2.2,3.48,3.69,2.05,1.61,2.3,1.64,2.37,1.66,2.4,1.61,2.32,0.25,2.05,1.75,2.15,1.78,2.16,1.87,2.1,1.79,4,3.8,1.83,3.7,3.9,1.91,3.7,3.5,2,3.91,4.02,1.91,3.8,3.9,1.88,3.75,4.1,1.9,4,4.1,2,3.78,3.94,1.89,1.44,2.75,1.52,2.68,1.55,2.85,1.48,2.66,0.5,2.03,1.9,2.01,1.91,2.04,1.95,1.98,1.9 31 | D1,14/09/2019,14:30,Dortmund,Leverkusen,4,0,H,1,0,H,11,22,9,12,9,11,3,3,0,3,0,0,1.8,4,4,1.75,4.1,4.25,1.75,4.1,4.2,1.87,3.99,4.1,1.83,4,4,1.83,4.2,3.9,1.89,4.2,4.3,1.82,4.01,4.04,1.44,2.75,1.46,2.87,1.46,3,1.43,2.81,-0.5,1.8,2,1.87,2.05,1.88,2.1,1.83,2.04,1.8,3.9,4.2,1.87,3.9,3.8,1.75,4.1,4.2,1.84,4.11,4.11,1.83,3.9,4,1.85,4,4,1.89,4.15,4.2,1.83,3.98,4.03,1.44,2.75,1.45,2.92,1.47,3,1.44,2.78,-0.75,2,1.8,2.07,1.85,2.09,1.91,2.05,1.84 32 | D1,14/09/2019,14:30,FC Koln,M'gladbach,0,1,A,0,1,A,14,15,7,4,22,17,4,7,2,2,0,0,2.5,3.5,2.7,2.6,3.4,2.7,2.6,3.5,2.6,2.61,3.6,2.72,2.55,3.6,2.62,2.55,3.6,2.7,2.7,3.7,2.75,2.57,3.53,2.66,1.66,2.2,1.68,2.3,1.71,2.33,1.65,2.24,0,1.91,2.02,1.92,2,1.95,2.02,1.9,1.98,2.1,3.6,3.3,2.2,3.6,3.1,2.4,3.5,2.85,2.22,3.77,3.19,2.2,3.6,3.2,2.25,3.6,3.13,2.4,3.8,3.3,2.21,3.64,3.14,1.57,2.37,1.59,2.48,1.75,2.49,1.61,2.33,-0.25,1.95,1.98,1.94,1.98,1.98,2.02,1.93,1.95 33 | D1,14/09/2019,14:30,Mainz,Hertha,2,1,H,1,0,H,14,16,5,8,16,11,6,3,2,2,0,0,2.3,3.4,3.1,2.4,3.5,2.9,2.4,3.4,2.9,2.36,3.55,3.09,2.35,3.4,3,2.4,3.5,3,2.5,3.56,3.1,2.38,3.44,2.98,1.72,2.1,1.79,2.12,1.82,2.15,1.78,2.05,-0.25,2.07,1.86,2.05,1.87,2.15,1.88,2.06,1.83,2.37,3.3,3,2.4,3.5,2.9,2.4,3.4,2.9,2.41,3.55,3,2.38,3.5,2.9,2.4,3.5,2.9,2.5,3.64,3.03,2.38,3.49,2.93,1.66,2.2,1.72,2.22,1.75,2.23,1.71,2.15,-0.25,2.1,1.83,2.09,1.83,2.15,1.87,2.07,1.82 34 | D1,14/09/2019,14:30,Union Berlin,Werder Bremen,1,2,A,1,1,D,12,16,5,7,23,10,7,4,3,4,1,1,2.87,3.5,2.4,2.9,3.5,2.4,2.75,3.4,2.5,2.8,3.55,2.56,2.75,3.5,2.5,2.8,3.5,2.5,2.9,3.6,2.6,2.79,3.5,2.48,1.66,2.2,1.67,2.32,1.72,2.32,1.67,2.21,0,2.07,1.86,2.05,1.87,2.08,1.87,2.05,1.84,2.3,3.6,2.87,2.4,3.5,2.85,2.5,3.4,2.75,2.38,3.85,2.86,2.35,3.7,2.8,2.38,3.8,2.8,2.55,3.89,2.95,2.38,3.68,2.83,1.57,2.37,1.55,2.58,1.65,2.58,1.56,2.43,-0.25,2.1,1.83,2.09,1.83,2.15,1.85,2.08,1.81 35 | D1,14/09/2019,17:30,RB Leipzig,Bayern Munich,1,1,D,1,1,D,12,14,6,7,11,4,3,6,4,2,0,0,3.8,4,1.85,3.75,4.1,1.85,3.5,3.7,2,3.78,4.27,1.88,3.9,4,1.83,3.8,4.1,1.87,4.05,4.27,2,3.78,4.04,1.87,1.44,2.75,1.5,2.74,1.52,2.79,1.47,2.68,0.5,2.05,1.88,2.03,1.88,2.06,1.95,2.01,1.87,4,4.2,1.75,4.4,4.25,1.7,3.6,3.6,2,4.64,4.5,1.68,4.33,4.2,1.73,4.4,4.33,1.73,4.7,4.56,2,4.3,4.3,1.73,1.4,3,1.44,2.95,1.49,3,1.43,2.8,0.75,2.05,1.88,2.06,1.86,2.09,2.01,2,1.89 36 | D1,15/09/2019,14:30,Hoffenheim,Freiburg,0,3,A,0,2,A,22,16,5,8,10,6,12,4,0,2,0,0,1.7,4.2,4.5,1.7,4.2,4.5,1.7,4,4.7,1.7,4.32,4.7,1.67,4.2,4.75,1.7,4.2,4.75,1.75,4.4,4.9,1.69,4.2,4.6,1.57,2.37,1.58,2.51,1.58,2.55,1.55,2.45,-0.75,1.9,2.03,1.9,2.02,1.93,2.04,1.88,1.99,1.85,3.8,3.8,1.91,3.7,3.9,1.85,3.6,4.3,2,3.66,3.93,1.91,3.6,4,1.95,3.8,3.8,2.05,3.9,4.3,1.93,3.69,3.9,1.72,2.1,1.73,2.21,1.73,2.38,1.67,2.2,-0.5,1.98,1.95,2,1.92,2.02,2.01,1.95,1.93 37 | D1,15/09/2019,17:00,Paderborn,Schalke 04,1,5,A,1,1,D,9,18,1,11,17,12,3,5,2,1,0,0,3.1,3.5,2.25,3,3.75,2.2,3.2,3.5,2.2,3.05,3.67,2.33,3,3.7,2.25,3,3.7,2.3,3.2,3.8,2.33,3.04,3.64,2.26,1.53,2.5,1.56,2.56,1.63,2.6,1.54,2.45,0.25,1.92,2.01,1.88,2.03,1.96,2.03,1.89,1.98,3,3.6,2.3,3.1,3.5,2.25,3,3.5,2.3,3.09,3.7,2.29,3.1,3.6,2.25,3,3.6,2.3,3.15,3.8,2.33,3.06,3.62,2.26,1.57,2.37,1.57,2.51,1.63,2.55,1.56,2.42,0.25,1.92,2.01,1.91,2.01,1.95,2.04,1.9,1.98 38 | D1,20/09/2019,19:30,Schalke 04,Mainz,2,1,H,1,0,H,19,14,6,3,7,15,5,5,1,1,0,0,1.61,4.2,5,1.65,3.9,5.25,1.67,4.1,4.9,1.65,4.16,5.33,1.65,4,5.25,1.65,4.2,5,1.7,4.22,5.4,1.66,4.07,5.11,1.66,2.2,1.68,2.3,1.72,2.3,1.67,2.22,-0.75,1.86,2.07,1.84,2.08,1.93,2.08,1.84,2.04,1.61,4.2,5,1.67,3.9,5.25,1.67,4,4.9,1.68,4.1,5.24,1.63,4,5.25,1.67,4.2,4.8,1.7,4.25,5.4,1.66,4.08,5.06,1.57,2.37,1.6,2.47,1.67,2.47,1.6,2.35,-1,2.07,1.72,2.17,1.77,2.2,1.81,2.14,1.76 39 | D1,21/09/2019,14:30,Bayern Munich,FC Koln,4,0,H,1,0,H,24,16,5,2,15,20,12,4,4,0,0,1,1.11,10,21,1.13,9,19.5,1.12,9.3,18.5,1.13,9.47,23.05,1.11,9,23,1.11,10,21,1.14,10.5,31,1.12,9.25,21.04,1.25,4,1.27,4.01,1.27,4.05,1.25,3.83,-2.5,1.98,1.95,1.99,1.93,1.99,1.96,1.95,1.92,1.11,9.5,21,1.1,10.5,21,1.12,9.3,18.5,1.12,10.38,25.44,1.1,9.5,26,1.1,10,26,1.15,11,28,1.11,9.89,22.41,1.22,4.33,1.23,4.5,1.26,4.51,1.23,4.07,-2.5,1.86,2.07,1.86,2.06,1.9,2.08,1.86,2.02 40 | D1,21/09/2019,14:30,Freiburg,Augsburg,1,1,D,1,1,D,17,12,5,2,13,13,7,4,1,1,0,0,1.9,3.75,3.8,1.87,3.75,4,2,3.5,3.7,1.9,3.88,4.1,1.88,3.7,4,1.9,3.8,3.9,2.05,3.9,4.2,1.9,3.77,3.92,1.66,2.2,1.67,2.31,1.72,2.31,1.67,2.21,-0.5,1.91,2.02,1.9,2.02,2.05,2.03,1.9,1.98,1.9,3.75,3.8,1.87,3.75,4,2,3.5,3.7,1.98,3.77,3.89,1.91,3.7,3.9,1.95,3.9,3.6,2.01,3.95,4.58,1.91,3.78,3.87,1.57,2.37,1.63,2.38,1.67,2.5,1.62,2.31,-0.5,1.98,1.95,1.98,1.94,2,2.01,1.94,1.94 41 | D1,21/09/2019,14:30,Hertha,Paderborn,2,1,H,1,0,H,6,17,4,8,13,15,1,8,4,4,0,0,1.7,4,4.75,1.7,4,4.75,1.8,3.9,4.1,1.74,4.05,4.76,1.73,4,4.6,1.73,4.2,4.33,1.8,4.2,4.95,1.73,4.02,4.54,1.44,2.75,1.49,2.78,1.55,2.78,1.48,2.64,-0.75,1.95,1.98,1.95,1.97,1.96,2,1.93,1.95,1.6,4.2,5.25,1.62,4.25,5,1.75,3.9,4.4,1.63,4.64,4.93,1.57,4.4,5.25,1.62,4.6,4.8,1.75,4.78,5.8,1.62,4.45,4.91,1.33,3.4,1.37,3.27,1.5,3.48,1.37,3.12,-0.75,1.7,2.1,1.78,2.15,1.8,2.27,1.76,2.15 42 | D1,21/09/2019,14:30,Leverkusen,Union Berlin,2,0,H,2,0,H,20,4,7,0,10,10,8,1,0,1,0,1,1.36,5.5,7.5,1.36,5.25,8,1.35,5.3,8,1.36,5.44,8.6,1.36,5.25,7.5,1.36,5.5,7.5,1.41,5.7,8.6,1.36,5.31,7.82,1.44,2.75,1.46,2.86,1.52,2.88,1.44,2.74,-1.5,2.06,1.87,2.06,1.86,2.07,1.91,2.02,1.86,1.33,5,8,1.36,5.25,7.75,1.43,5,6.5,1.37,5.53,8.11,1.35,5.25,8,1.36,5.5,7.5,1.43,5.7,9,1.36,5.33,7.83,1.36,3.2,1.41,3.08,1.45,3.2,1.39,2.96,-1.5,1.99,1.94,1.96,1.96,2.05,1.97,1.97,1.91 43 | D1,21/09/2019,17:30,Werder Bremen,RB Leipzig,0,3,A,0,2,A,11,14,1,7,11,13,4,7,0,3,0,1,4.2,4.2,1.72,4.33,4.2,1.72,4.2,4.1,1.75,4.24,4.35,1.77,4.2,4.2,1.75,4,4.3,1.8,4.55,4.5,1.8,4.19,4.25,1.75,1.44,2.75,1.48,2.79,1.49,2.83,1.46,2.69,0.75,1.91,2.02,1.93,1.99,1.93,2.04,1.9,1.97,4.2,4.2,1.72,4.1,4.25,1.75,4.2,4.1,1.75,4.26,4.28,1.78,4.2,4.2,1.75,4.1,4.3,1.75,4.45,4.45,1.8,4.16,4.23,1.76,1.5,2.62,1.52,2.66,1.52,2.86,1.47,2.67,0.75,1.92,2.01,1.91,2.01,1.95,2.03,1.9,1.97 44 | D1,22/09/2019,14:30,M'gladbach,Fortuna Dusseldorf,2,1,H,0,1,A,23,18,11,4,14,11,10,4,2,3,0,0,1.66,4,5,1.67,4,5,1.67,4.15,4.55,1.71,4.07,4.95,1.67,4.2,4.75,1.7,4.2,4.75,1.74,4.34,5.2,1.69,4.09,4.77,1.53,2.5,1.57,2.53,1.57,2.6,1.54,2.46,-0.75,1.91,2.02,1.91,2.01,1.92,2.04,1.88,2,1.72,3.8,4.5,1.75,3.9,4.5,1.75,3.9,4.4,1.79,3.94,4.6,1.73,3.9,4.6,1.73,4,4.6,1.84,4.1,4.8,1.76,3.89,4.54,1.61,2.3,1.65,2.36,1.65,2.45,1.6,2.35,-0.75,2,1.93,2.02,1.9,2.05,1.97,1.98,1.9 45 | D1,22/09/2019,17:00,Ein Frankfurt,Dortmund,2,2,D,1,1,D,17,15,3,7,18,10,5,8,2,2,0,0,4.33,4,1.75,4.4,4.25,1.7,4.2,4.1,1.75,4.37,4.27,1.76,4.33,4.2,1.73,4.2,4.3,1.75,4.5,4.4,1.79,4.29,4.22,1.74,1.44,2.75,1.49,2.78,1.53,2.86,1.46,2.7,0.75,1.94,1.99,1.93,1.98,1.96,2,1.92,1.95,5.25,4.2,1.57,5,4.25,1.62,4.2,3.9,1.8,5.29,4.6,1.6,5.25,4.33,1.6,4.8,4.6,1.62,5.4,4.68,1.8,4.96,4.42,1.62,1.4,3,1.44,2.93,1.47,3,1.43,2.81,1,1.89,2.04,1.93,2,2.02,2.3,1.86,2.02 46 | D1,23/09/2019,19:30,Wolfsburg,Hoffenheim,1,1,D,1,1,D,12,11,4,5,11,18,4,6,2,4,0,0,1.95,3.75,3.75,1.95,3.9,3.5,1.93,3.9,3.6,1.97,3.82,3.9,1.95,3.75,3.75,2,3.9,3.6,2,3.95,3.92,1.95,3.81,3.7,1.53,2.5,1.58,2.51,1.6,2.63,1.53,2.48,-0.5,1.97,1.96,1.97,1.95,1.97,1.97,1.95,1.93,2,3.75,3.4,2.1,3.6,3.4,2.1,3.6,3.35,2.13,3.78,3.37,2.05,3.7,3.4,2.1,3.8,3.3,2.18,3.87,3.53,2.09,3.73,3.35,1.61,2.3,1.64,2.37,1.66,2.47,1.62,2.32,-0.25,1.85,2.08,1.87,2.05,1.87,2.1,1.83,2.06 47 | D1,27/09/2019,19:30,Union Berlin,Ein Frankfurt,1,2,A,0,0,D,12,14,5,6,11,12,4,5,1,1,0,0,3,3.5,2.3,3,3.6,2.3,3,3.5,2.3,3.03,3.71,2.32,3,3.6,2.3,2.9,3.7,2.3,3.19,3.75,2.38,2.99,3.64,2.3,1.57,2.37,1.61,2.43,1.65,2.55,1.58,2.39,0.25,1.9,2.03,1.88,2.03,1.91,2.04,1.87,2,2.8,3.6,2.37,2.9,3.5,2.4,2.85,3.5,2.4,2.99,3.53,2.43,2.9,3.5,2.38,2.8,3.6,2.45,3.06,3.7,2.48,2.9,3.52,2.39,1.66,2.2,1.7,2.25,1.71,2.4,1.64,2.27,0.25,1.81,2.13,1.82,2.1,1.84,2.16,1.8,2.09 48 | D1,28/09/2019,14:30,Augsburg,Leverkusen,0,3,A,0,1,A,8,11,1,5,16,9,1,3,4,0,0,0,5,4.5,1.6,5,4.5,1.6,4.55,4.5,1.63,4.79,4.65,1.65,4.75,4.4,1.63,4.5,4.6,1.65,5,4.7,1.68,4.71,4.52,1.63,1.4,3,1.41,3.09,1.45,3.2,1.39,2.99,1,1.85,2.08,1.87,2.05,1.88,2.09,1.84,2.03,4.5,4.2,1.7,4.33,4.2,1.72,4.3,4,1.75,4.32,4.25,1.78,4.33,4.2,1.73,4.2,4.33,1.73,4.58,4.4,1.79,4.29,4.21,1.74,1.53,2.5,1.53,2.65,1.55,2.85,1.49,2.6,0.75,1.95,1.98,1.93,1.98,2.07,2,1.94,1.94 49 | D1,28/09/2019,14:30,Hoffenheim,M'gladbach,0,3,A,0,1,A,17,11,4,5,10,11,2,5,2,2,0,0,2.5,3.5,2.75,2.45,3.5,2.8,2.6,3.5,2.6,2.43,3.69,2.88,2.4,3.6,2.8,2.45,3.6,2.8,2.6,3.75,2.89,2.43,3.61,2.79,1.57,2.37,1.6,2.46,1.67,2.5,1.58,2.38,-0.25,2.1,1.83,2.12,1.81,2.2,1.84,2.1,1.79,2.7,3.4,2.55,2.6,3.6,2.55,2.5,3.5,2.75,2.82,3.53,2.55,2.62,3.5,2.6,2.75,3.6,2.5,2.85,3.7,2.75,2.71,3.55,2.53,1.66,2.2,1.68,2.3,1.68,2.4,1.62,2.3,0,2.08,1.85,2.06,1.85,2.09,1.93,2.03,1.86 50 | D1,28/09/2019,14:30,Mainz,Wolfsburg,0,1,A,0,1,A,15,4,5,3,9,15,10,1,2,3,0,0,2.9,3.5,2.37,2.8,3.5,2.45,2.9,3.55,2.35,2.96,3.58,2.42,2.88,3.6,2.35,2.88,3.6,2.4,3,3.72,2.5,2.89,3.52,2.4,1.72,2.1,1.76,2.15,1.78,2.2,1.73,2.1,0.25,1.82,2.11,1.83,2.1,1.83,2.15,1.8,2.08,2.87,3.5,2.4,2.75,3.5,2.5,2.8,3.5,2.45,2.87,3.58,2.49,2.8,3.5,2.45,2.88,3.5,2.45,2.93,3.61,2.6,2.82,3.49,2.46,1.72,2.1,1.76,2.17,1.82,2.19,1.74,2.1,0.25,1.72,2.07,1.78,2.15,1.82,2.19,1.77,2.12 51 | D1,28/09/2019,14:30,Paderborn,Bayern Munich,2,3,A,0,1,A,10,18,5,6,7,6,11,5,1,1,0,0,15,10,1.14,17,8.25,1.15,15.5,9,1.15,15.7,9.17,1.15,15,9,1.14,17,10,1.13,18.5,10.5,1.18,15.89,9.07,1.14,1.2,4.5,1.19,4.97,1.21,5,1.19,4.65,2.5,1.95,1.98,1.93,1.97,1.96,1.99,1.92,1.95,15,10,1.14,21,9.75,1.11,17,8,1.15,20.69,11.4,1.12,23,11,1.1,26,11,1.09,28,12,1.15,20.74,10.52,1.11,1.14,5.5,1.14,6.27,1.2,6.5,1.14,5.5,2.75,2.1,1.83,2.1,1.83,2.21,1.9,2.05,1.84 52 | D1,28/09/2019,14:30,RB Leipzig,Schalke 04,1,3,A,0,2,A,17,13,6,8,13,11,8,4,1,1,0,0,1.53,4.33,6,1.55,4.25,6,1.57,4.45,5.3,1.59,4.41,5.68,1.57,4.4,5.5,1.57,4.5,5.4,1.62,4.65,6.05,1.56,4.41,5.57,1.53,2.5,1.53,2.64,1.53,2.69,1.5,2.56,-1,1.95,1.98,1.94,1.97,1.96,1.99,1.92,1.94,1.53,4.33,5.5,1.57,4.33,5.5,1.57,4.3,5.5,1.59,4.32,5.77,1.57,4.2,5.8,1.57,4.4,5.5,1.62,4.5,5.9,1.57,4.31,5.59,1.57,2.37,1.61,2.43,1.62,2.55,1.57,2.41,-1,2,1.93,1.99,1.93,2.04,2.04,1.96,1.92 53 | D1,28/09/2019,17:30,Dortmund,Werder Bremen,2,2,D,2,1,H,19,11,7,5,8,10,9,2,1,0,0,0,1.25,6.5,11,1.26,6.25,10.5,1.27,6,10,1.28,6.5,9.9,1.27,6,10,1.25,6.5,11,1.3,6.75,11.25,1.27,6.3,10.09,1.3,3.5,1.33,3.53,1.35,3.6,1.32,3.36,-1.75,1.91,2.02,1.9,2.02,1.92,2.04,1.89,1.99,1.33,5.75,8.5,1.3,6,8.5,1.27,6,10,1.32,5.81,9.44,1.3,5.5,10,1.33,6,8,1.35,6,10,1.32,5.74,8.68,1.33,3.4,1.34,3.47,1.36,3.66,1.33,3.33,-1.5,1.93,2,1.93,1.99,1.95,2.05,1.89,1.99 54 | D1,29/09/2019,14:30,Fortuna Dusseldorf,Freiburg,1,2,A,1,1,D,17,9,7,3,9,9,5,1,2,2,0,0,2.37,3.4,2.87,2.4,3.5,2.9,2.45,3.55,2.75,2.5,3.68,2.79,2.45,3.6,2.75,2.45,3.6,2.8,2.52,3.7,3.05,2.44,3.58,2.78,1.66,2.2,1.65,2.35,1.69,2.35,1.64,2.26,0,1.86,2.07,1.85,2.07,1.87,2.09,1.84,2.05,2.5,3.4,2.7,2.55,3.5,2.7,2.6,3.35,2.7,2.6,3.48,2.79,2.55,3.5,2.7,2.55,3.5,2.7,2.63,3.6,2.99,2.55,3.45,2.74,1.8,2,1.81,2.09,1.86,2.25,1.77,2.07,-0.25,2.15,1.67,2.24,1.72,2.28,1.83,2.21,1.72 55 | D1,29/09/2019,17:00,FC Koln,Hertha,0,4,A,0,1,A,8,10,3,6,11,13,8,4,1,0,1,0,2.15,3.6,3.3,2.15,3.6,3.25,2.1,3.7,3.2,2.16,3.71,3.35,2.15,3.6,3.25,2.15,3.7,3.3,2.28,3.8,3.35,2.15,3.66,3.23,1.61,2.3,1.65,2.35,1.66,2.43,1.61,2.32,-0.25,1.9,2.03,1.88,2.03,1.95,2.04,1.87,2,2.05,3.6,3.4,2.15,3.5,3.3,2.25,3.4,3.2,2.15,3.6,3.48,2.1,3.6,3.4,2.15,3.6,3.3,2.25,3.7,3.5,2.13,3.57,3.37,1.66,2.2,1.71,2.24,1.73,2.4,1.66,2.24,-0.25,1.88,2.05,1.87,2.05,1.89,2.07,1.86,2.02 56 | D1,04/10/2019,19:30,Hertha,Fortuna Dusseldorf,3,1,H,2,1,H,16,9,3,3,17,18,9,2,3,3,0,0,1.65,4,4.75,1.67,4.2,4.75,1.8,3.7,4.4,1.68,4.17,5.12,1.67,4,5,1.67,4.2,4.8,1.8,4.25,5.2,1.68,4.09,4.88,1.57,2.37,1.61,2.43,1.73,2.45,1.6,2.35,-0.75,1.86,2.07,1.86,2.06,1.95,2.08,1.84,2.04,1.61,4,5,1.67,4.2,4.75,1.7,3.8,5,1.67,4.29,5,1.63,4,5.25,1.65,4.2,5,1.73,4.33,5.6,1.66,4.17,4.89,1.53,2.5,1.54,2.61,1.65,2.61,1.55,2.46,-0.75,1.83,2.1,1.85,2.07,1.9,2.16,1.83,2.06 57 | D1,05/10/2019,14:30,Bayern Munich,Hoffenheim,1,2,A,0,0,D,20,8,4,5,8,12,9,3,2,0,0,0,1.11,9,26,1.12,10,18.5,1.11,10,20,1.1,10.81,26.13,1.1,10,23,1.1,10.5,26,1.13,11.5,30,1.11,10.03,23.32,1.22,4.33,1.21,4.64,1.25,4.64,1.21,4.31,-2.75,2.01,1.92,2.01,1.89,2.02,1.95,1.98,1.89,1.1,9.5,26,1.12,9.75,18,1.12,9,20,1.11,11.32,23.47,1.1,11,23,1.09,12,22,1.13,12,29,1.1,10.34,22.35,1.16,5,1.16,5.69,1.22,5.75,1.17,4.91,-2.75,1.94,1.99,1.92,2,1.98,2.03,1.93,1.95 58 | D1,05/10/2019,14:30,Freiburg,Dortmund,2,2,D,0,1,A,6,8,1,4,10,8,3,11,0,3,0,0,5.75,4.2,1.57,5.25,4.5,1.57,4.8,4.2,1.65,5.5,4.28,1.62,5.25,4.2,1.6,5.2,4.4,1.6,5.75,4.5,1.66,5.3,4.32,1.59,1.44,2.75,1.48,2.79,1.49,2.83,1.45,2.72,1,1.92,2.01,1.93,2,1.95,2.01,1.9,1.97,5.5,4,1.6,5,4.25,1.62,4.7,4,1.7,5.26,4.29,1.64,5.5,4.2,1.6,5.2,4.3,1.62,5.9,4.31,1.7,5.19,4.13,1.64,1.66,2.2,1.68,2.28,1.73,2.55,1.66,2.23,1,1.77,2.02,1.83,2.09,1.89,2.19,1.8,2.09 59 | D1,05/10/2019,14:30,Leverkusen,RB Leipzig,1,1,D,0,0,D,11,11,8,5,11,12,4,0,2,2,0,0,2.25,3.5,3.1,2.3,3.8,2.85,2.5,3.7,2.6,2.36,3.8,2.91,2.3,3.7,2.88,2.3,3.8,2.88,2.5,3.85,3.1,2.33,3.73,2.86,1.53,2.5,1.55,2.59,1.55,2.72,1.51,2.56,-0.25,2.06,1.87,2.07,1.85,2.15,1.88,2.04,1.84,2.3,3.6,2.87,2.4,3.7,2.75,2.3,3.7,2.85,2.43,3.68,2.89,2.4,3.6,2.8,2.38,3.75,2.8,2.51,3.85,2.96,2.41,3.69,2.77,1.53,2.5,1.53,2.64,1.54,2.7,1.51,2.55,-0.25,2.05,1.75,2.11,1.81,2.19,1.84,2.12,1.77 60 | D1,05/10/2019,14:30,Paderborn,Mainz,1,2,A,1,2,A,16,18,7,7,8,18,7,10,1,4,0,0,2.5,3.5,2.8,2.55,3.6,2.65,2.6,3.5,2.6,2.53,3.87,2.67,2.5,3.75,2.62,2.45,3.8,2.7,2.6,3.9,2.8,2.49,3.75,2.64,1.44,2.75,1.45,2.89,1.5,2.9,1.44,2.76,0,1.9,2.03,1.9,2.01,1.91,2.04,1.88,1.99,2.45,3.6,2.75,2.45,3.9,2.6,2.6,3.5,2.6,2.49,3.95,2.67,2.5,3.9,2.55,2.45,3.9,2.63,2.6,4.1,2.8,2.47,3.85,2.62,1.36,3.2,1.37,3.28,1.5,3.3,1.36,3.12,-0.25,2.15,1.67,2.19,1.76,2.2,1.8,2.16,1.75 61 | D1,05/10/2019,17:30,Schalke 04,FC Koln,1,1,D,0,0,D,15,9,3,5,15,15,6,4,4,4,0,0,1.57,4.33,5.5,1.62,4.1,5.25,1.6,4.2,5.3,1.66,4.21,5.22,1.63,4.2,5,1.65,4.33,4.8,1.7,4.34,5.5,1.64,4.15,5.08,1.57,2.37,1.63,2.39,1.63,2.45,1.59,2.35,-1,2.13,1.81,2.12,1.81,2.15,1.83,2.1,1.79,1.6,4.33,5.25,1.6,4.25,5.25,1.7,4,4.7,1.62,4.42,5.34,1.62,4.2,5.25,1.6,4.4,5.2,1.7,4.51,5.45,1.63,4.29,5.04,1.57,2.37,1.6,2.46,1.61,2.55,1.57,2.42,-0.75,1.7,2.1,1.78,2.16,2,2.21,1.78,2.1 62 | D1,06/10/2019,12:30,M'gladbach,Augsburg,5,1,H,4,0,H,13,13,9,3,9,9,2,7,1,2,0,0,1.5,4.33,6.5,1.53,4.4,6,1.55,4.55,5.5,1.54,4.66,5.95,1.52,4.5,5.8,1.5,4.6,5.4,1.6,4.75,6.5,1.53,4.53,5.75,1.5,2.62,1.5,2.73,1.53,2.73,1.5,2.59,-1,1.89,2.04,1.86,2.06,1.93,2.06,1.86,2.01,1.53,4.2,6.5,1.53,4.4,6,1.57,4.2,5.6,1.56,4.58,5.79,1.5,4.33,6.5,1.55,4.6,5.5,1.58,4.65,7.3,1.54,4.46,5.77,1.44,2.75,1.48,2.8,1.5,2.85,1.46,2.7,-1,1.91,2.02,1.9,2.02,1.93,2.13,1.88,1.99 63 | D1,06/10/2019,14:30,Wolfsburg,Union Berlin,1,0,H,0,0,D,13,14,4,3,17,15,5,4,2,2,0,0,1.66,4,5,1.65,4,5.25,1.67,3.95,5,1.69,3.81,5.56,1.65,4,5.25,1.65,4,4.75,1.73,4.24,5.85,1.67,3.89,5.22,1.72,2.1,1.7,2.25,1.78,2.25,1.71,2.15,-0.75,1.89,2.04,1.89,2.03,1.9,2.08,1.86,2.02,1.9,3.6,4,1.83,3.6,4.4,1.8,3.6,4.5,2.01,3.4,4.24,1.91,3.5,4.2,2,3.6,3.75,2.02,3.66,4.5,1.95,3.44,4.1,1.9,1.9,1.93,1.97,1.93,2.15,1.84,1.98,-0.5,2.01,1.92,2.01,1.91,2.03,2,1.97,1.91 64 | D1,06/10/2019,17:00,Ein Frankfurt,Werder Bremen,2,2,D,0,1,A,24,11,7,5,12,8,10,1,2,1,0,0,2.1,3.6,3.4,2.15,3.7,3.2,2.2,3.75,3,2.19,3.66,3.35,2.15,3.6,3.25,2.1,3.8,3,2.25,3.8,3.4,2.17,3.65,3.18,1.53,2.5,1.52,2.67,1.53,2.72,1.49,2.59,-0.25,1.94,1.99,1.9,2.01,1.96,2.01,1.91,1.97,1.9,3.8,3.5,2.05,3.7,3.4,2,3.65,3.65,2.01,3.89,3.66,2,3.8,3.5,2.05,3.8,3.4,2.05,4.03,3.85,2,3.76,3.57,1.44,2.75,1.47,2.85,1.5,2.86,1.46,2.71,-0.5,2.02,1.91,2.01,1.91,2.05,1.92,2,1.88 65 | D1,18/10/2019,19:30,Ein Frankfurt,Leverkusen,3,0,H,2,0,H,10,19,5,10,11,12,4,1,1,1,0,0,2.75,3.9,2.3,2.85,3.75,2.3,2.8,3.6,2.4,2.9,3.89,2.34,2.88,3.75,2.3,2.8,3.9,2.3,2.96,4,2.42,2.85,3.79,2.32,1.53,2.5,1.53,2.62,1.55,2.63,1.52,2.52,0.25,1.87,2.06,1.86,2.06,1.89,2.07,1.84,2.03,2.7,3.8,2.37,2.75,3.7,2.4,2.8,3.6,2.4,2.79,3.85,2.43,2.7,3.75,2.4,2.75,3.8,2.4,3.07,3.9,2.56,2.74,3.76,2.41,1.53,2.5,1.52,2.66,1.54,2.7,1.51,2.54,0.25,1.75,2.05,1.8,2.12,1.83,2.17,1.78,2.11 66 | D1,19/10/2019,14:30,Augsburg,Bayern Munich,2,2,D,1,1,D,9,24,7,9,10,6,3,7,3,3,0,0,15,8,1.16,16,7.75,1.17,13,7,1.2,16.25,8.41,1.16,17,8,1.15,13,8.5,1.17,21,9,1.2,16.44,8.18,1.16,1.28,3.75,1.29,3.8,1.3,3.9,1.28,3.64,2.25,2.05,1.88,2.05,1.85,2.06,1.89,2,1.86,17,8.5,1.14,20,8.5,1.13,13,7,1.2,19.86,9.57,1.13,19,9,1.12,13,9.5,1.15,23,10.25,1.2,18.63,9.13,1.13,1.25,4,1.25,4.18,1.26,4.26,1.25,3.89,2.5,1.96,1.97,1.96,1.96,1.97,2.2,1.92,1.96 67 | D1,19/10/2019,14:30,Fortuna Dusseldorf,Mainz,1,0,H,0,0,D,20,7,4,1,10,17,8,1,2,4,0,1,2.55,3.4,2.62,2.45,3.6,2.75,2.6,3.4,2.65,2.65,3.61,2.67,2.55,3.6,2.62,2.6,3.6,2.63,2.65,3.7,2.76,2.57,3.55,2.65,1.66,2.2,1.71,2.24,1.72,2.32,1.66,2.22,0,1.95,1.98,1.95,1.97,1.96,2.01,1.91,1.96,2.55,3.4,2.62,2.65,3.5,2.6,2.65,3.35,2.65,2.72,3.7,2.55,2.6,3.6,2.6,2.7,3.6,2.5,2.75,3.74,2.72,2.66,3.58,2.55,1.57,2.37,1.62,2.41,1.65,2.47,1.6,2.35,0,2.03,1.9,2.02,1.89,2.06,1.91,2,1.88 68 | D1,19/10/2019,14:30,RB Leipzig,Wolfsburg,1,1,D,0,0,D,13,14,5,6,10,9,3,3,1,3,0,0,1.53,4.5,5.75,1.55,4.2,6,1.57,4.2,5.6,1.56,4.41,6.14,1.53,4.33,6,1.53,4.5,5.75,1.58,4.55,6.25,1.54,4.35,5.9,1.61,2.3,1.64,2.38,1.65,2.43,1.61,2.32,-1,1.93,2,1.93,1.99,1.93,2.01,1.9,1.96,1.53,4.5,5.5,1.53,4.33,6,1.57,4.2,5.6,1.55,4.42,6.21,1.52,4.4,6,1.53,4.5,5.75,1.58,4.6,6.26,1.54,4.37,5.85,1.57,2.37,1.59,2.48,1.62,2.55,1.58,2.39,-1,1.93,2,1.92,2,1.95,2.03,1.91,1.96 69 | D1,19/10/2019,14:30,Union Berlin,Freiburg,2,0,H,1,0,H,18,12,5,4,21,13,3,4,3,0,0,0,2.5,3.5,2.7,2.4,3.6,2.8,2.6,3.3,2.75,2.68,3.5,2.7,2.6,3.4,2.7,2.6,3.5,2.7,2.68,3.6,2.8,2.58,3.45,2.69,1.9,1.9,1.92,1.99,1.92,2.05,1.85,1.97,0,1.94,1.99,1.95,1.96,1.95,2.01,1.91,1.96,2.55,3.3,2.7,2.6,3.4,2.7,2.65,3.35,2.65,2.68,3.41,2.75,2.6,3.4,2.7,2.6,3.4,2.75,2.72,3.46,2.79,2.64,3.35,2.7,1.9,1.9,2,1.9,2,1.97,1.92,1.9,0,1.92,2.01,1.93,1.99,1.95,2.03,1.91,1.97 70 | D1,19/10/2019,14:30,Werder Bremen,Hertha,1,1,D,1,0,H,15,11,5,2,8,11,7,5,1,1,0,0,2.1,3.75,3.2,2.05,3.8,3.4,2.15,3.7,3.15,2.18,3.71,3.31,2.1,3.7,3.25,2.15,3.75,3.2,2.2,3.8,3.4,2.14,3.68,3.25,1.53,2.5,1.56,2.57,1.56,2.63,1.52,2.51,-0.25,1.92,2.01,1.91,2.01,1.92,2.02,1.88,1.99,2.25,3.6,3,2.3,3.4,3.1,2.3,3.6,2.95,2.37,3.63,3.02,2.3,3.5,3,2.38,3.6,2.9,2.39,3.7,3.1,2.32,3.57,2.97,1.66,2.2,1.65,2.34,1.7,2.36,1.63,2.27,-0.25,2.05,1.88,2.06,1.86,2.07,1.9,2.02,1.85 71 | D1,19/10/2019,17:30,Dortmund,M'gladbach,1,0,H,0,0,D,20,13,7,3,13,15,10,8,1,2,0,0,1.44,5,6.5,1.45,5,6.25,1.57,4.2,5.6,1.48,4.94,6.5,1.47,5,6,1.44,5,6.5,1.57,5.05,6.75,1.47,4.83,6.25,1.36,3.2,1.38,3.22,1.4,3.25,1.37,3.07,-1.25,2,1.93,1.98,1.93,2.01,2.01,1.97,1.9,1.53,4.75,5,1.57,4.5,5.25,1.65,4.5,4.5,1.57,4.52,5.73,1.53,4.75,5.25,1.57,4.6,5.25,1.65,4.9,6.05,1.56,4.5,5.47,1.5,2.62,1.5,2.74,1.52,2.82,1.48,2.63,-1,1.97,1.96,1.97,1.95,1.99,2.03,1.92,1.95 72 | D1,20/10/2019,14:30,FC Koln,Paderborn,3,0,H,1,0,H,16,9,6,1,6,7,6,9,0,0,0,0,1.65,4.5,4.33,1.67,4.2,4.6,1.75,4,4.3,1.69,4.42,4.65,1.65,4.33,4.6,1.65,4.4,4.2,1.75,4.59,4.75,1.68,4.36,4.5,1.36,3.2,1.41,3.09,1.5,3.2,1.38,3.02,-0.75,1.87,2.06,1.88,2.04,1.9,2.08,1.85,2.03,1.65,4.5,4.33,1.67,4.4,4.4,1.7,4,4.6,1.74,4.44,4.35,1.7,4.4,4.33,1.73,4.5,4.1,1.78,4.62,4.6,1.71,4.39,4.27,1.25,4,1.29,3.81,1.33,4,1.27,3.73,-0.75,1.92,2.01,1.93,2,1.95,2.04,1.9,1.98 73 | D1,20/10/2019,17:00,Hoffenheim,Schalke 04,2,0,H,0,0,D,9,11,3,1,12,14,3,8,2,2,0,0,2.75,3.4,2.55,2.65,3.6,2.55,2.7,3.5,2.5,2.76,3.6,2.57,2.62,3.5,2.6,2.63,3.5,2.5,2.76,3.65,2.75,2.69,3.52,2.55,1.72,2.1,1.7,2.26,1.76,2.26,1.71,2.15,0,2.03,1.9,2.03,1.88,2.04,1.94,1.98,1.89,2.62,3.6,2.55,2.65,3.6,2.55,2.6,3.5,2.6,2.67,3.58,2.67,2.62,3.5,2.6,2.63,3.6,2.6,2.75,3.7,2.69,2.66,3.55,2.57,1.72,2.1,1.75,2.17,1.75,2.28,1.69,2.18,0,1.98,1.95,1.96,1.96,2,1.97,1.96,1.92 74 | D1,25/10/2019,19:30,Mainz,FC Koln,3,1,H,1,1,D,18,16,6,8,20,9,5,10,2,2,0,0,2.5,3.6,2.62,2.55,3.5,2.7,2.6,3.35,2.7,2.59,3.58,2.74,2.5,3.6,2.7,2.5,3.6,2.7,2.63,3.7,2.83,2.55,3.54,2.7,1.57,2.37,1.57,2.51,1.65,2.51,1.58,2.39,0,1.9,2.03,1.9,2.01,1.92,2.04,1.88,1.99,2.55,3.6,2.55,2.55,3.6,2.6,2.65,3.4,2.65,2.57,3.76,2.67,2.55,3.6,2.6,2.55,3.7,2.63,2.65,3.8,2.75,2.56,3.62,2.63,1.53,2.5,1.56,2.54,1.6,2.72,1.55,2.44,0,1.97,1.96,1.92,2,1.97,2.05,1.91,1.97 75 | D1,26/10/2019,14:30,Bayern Munich,Union Berlin,2,1,H,1,0,H,21,6,10,4,9,15,8,2,0,1,0,0,1.09,12,19,1.11,11,16.5,1.12,9,20,1.11,10.36,22.05,1.1,11,21,1.1,11.5,21,1.13,12,26,1.11,10.24,20.85,1.22,4.33,1.18,5.11,1.22,5.11,1.2,4.43,-2.75,2.03,1.9,2.01,1.89,2.04,1.91,2,1.87,1.09,12,19,1.1,11,21,1.12,9,20,1.11,10.96,23.13,1.1,11,23,1.09,12,23,1.13,13,28,1.1,10.59,22.23,1.22,4.33,1.18,5.17,1.22,5.17,1.2,4.49,-2.75,1.96,1.97,1.95,1.96,1.99,1.99,1.95,1.93 76 | D1,26/10/2019,14:30,Freiburg,RB Leipzig,2,1,H,1,0,H,14,25,3,6,10,9,5,4,3,1,0,0,4,3.8,1.85,4.25,3.8,1.8,3.9,3.75,1.9,4.14,3.73,1.93,4,3.7,1.88,3.9,3.8,1.9,4.25,3.9,1.97,3.96,3.74,1.9,1.66,2.2,1.67,2.32,1.69,2.33,1.63,2.27,0.5,2,1.93,1.99,1.93,2.02,1.96,1.96,1.91,4.75,4.2,1.65,4.5,4,1.72,4,3.6,1.9,4.95,4.24,1.68,4.8,4,1.7,4.8,4.1,1.7,5.2,4.29,1.9,4.8,4.04,1.7,1.61,2.3,1.63,2.39,1.67,2.47,1.62,2.3,0.75,2.07,1.86,2.05,1.87,2.11,1.92,2.01,1.87 77 | D1,26/10/2019,14:30,Hertha,Hoffenheim,2,3,A,0,2,A,13,17,4,8,17,12,4,4,3,3,1,0,2.05,3.6,3.6,2.1,3.5,3.5,2.1,3.65,3.35,2.09,3.78,3.51,2.05,3.7,3.4,2.1,3.75,3.3,2.25,3.81,3.6,2.1,3.66,3.37,1.61,2.3,1.63,2.39,1.7,2.41,1.62,2.31,-0.25,1.85,2.08,1.82,2.11,1.95,2.11,1.83,2.05,2,3.9,3.3,2.1,3.7,3.3,2.25,3.5,3.1,2.13,3.83,3.35,2.05,3.8,3.3,2.1,3.8,3.25,2.25,4,3.46,2.11,3.7,3.3,1.66,2.2,1.65,2.35,1.7,2.4,1.65,2.25,-0.25,1.88,2.05,1.86,2.06,1.9,2.06,1.85,2.03 78 | D1,26/10/2019,14:30,Paderborn,Fortuna Dusseldorf,2,0,H,1,0,H,14,18,6,4,21,17,4,7,5,4,0,0,2.37,3.75,2.7,2.35,3.8,2.8,2.35,3.9,2.7,2.45,3.93,2.73,2.38,3.8,2.7,2.38,3.9,2.7,2.47,4,2.85,2.38,3.85,2.73,1.36,3.2,1.42,3.05,1.42,3.2,1.39,2.97,-0.25,2.09,1.84,2.15,1.79,2.15,1.85,2.08,1.81,2.5,3.75,2.6,2.45,3.8,2.65,2.6,3.5,2.6,2.57,3.9,2.6,2.5,3.75,2.6,2.5,3.8,2.63,2.6,3.95,2.69,2.5,3.78,2.61,1.4,3,1.44,2.93,1.44,3.05,1.41,2.89,0,1.94,1.99,1.95,1.97,1.97,2.01,1.91,1.97 79 | D1,26/10/2019,14:30,Schalke 04,Dortmund,0,0,D,0,0,D,13,8,3,3,8,7,8,2,3,2,0,0,3.1,3.6,2.2,3.1,3.4,2.3,3.05,3.5,2.25,3.1,3.59,2.33,3.1,3.5,2.25,3,3.6,2.3,3.2,3.65,2.35,3.07,3.51,2.29,1.66,2.2,1.72,2.22,1.74,2.25,1.69,2.18,0.25,1.91,2.02,1.89,2.03,1.93,2.03,1.88,1.99,3.2,3.6,2.1,3.3,3.5,2.15,3.2,3.5,2.2,3.18,3.57,2.3,3.2,3.6,2.2,3.1,3.6,2.25,3.33,3.72,2.33,3.18,3.51,2.24,1.8,2,1.83,2.07,1.86,2.15,1.8,2.03,0.25,1.95,1.98,1.93,2,1.97,2.01,1.93,1.96 80 | D1,26/10/2019,17:30,Leverkusen,Werder Bremen,2,2,D,1,1,D,21,10,4,3,12,13,10,1,2,1,0,0,1.57,4.33,5.5,1.6,4.33,5.25,1.63,4.3,4.9,1.63,4.39,5.31,1.6,4.2,5.25,1.62,4.33,5,1.7,4.45,5.5,1.62,4.29,5.1,1.44,2.75,1.44,2.94,1.46,2.95,1.43,2.78,-1,2.03,1.9,1.99,1.93,2.1,1.93,2,1.87,1.65,4.33,4.5,1.7,4,4.75,1.75,4,4.3,1.71,4.21,4.78,1.65,4.2,4.8,1.7,4.2,4.6,1.75,4.44,5.1,1.7,4.12,4.66,1.57,2.37,1.6,2.47,1.61,2.63,1.55,2.44,-0.75,1.93,2,1.91,2.01,1.95,2.12,1.89,1.99 81 | D1,27/10/2019,14:30,Wolfsburg,Augsburg,0,0,D,0,0,D,14,10,3,5,12,13,5,3,0,0,0,0,1.57,4.33,5.5,1.6,4.33,5.25,1.6,4.15,5.5,1.59,4.24,5.95,1.57,4.2,5.8,1.55,4.3,5.2,1.62,4.34,6,1.59,4.19,5.6,1.61,2.3,1.65,2.34,1.67,2.42,1.62,2.29,-1,2,1.93,2.01,1.91,2.07,1.95,1.99,1.88,1.57,4.33,5.5,1.57,4.25,5.5,1.6,4.1,5.4,1.64,4.13,5.52,1.6,4.2,5.5,1.62,4.2,5.25,1.66,4.4,6.25,1.61,4.14,5.44,1.72,2.1,1.74,2.19,1.82,2.28,1.69,2.17,-1,2.1,1.83,2.11,1.81,2.12,1.86,2.06,1.82 82 | D1,27/10/2019,17:00,M'gladbach,Ein Frankfurt,4,2,H,2,0,H,12,15,7,3,12,11,5,6,1,1,0,0,1.83,4,3.75,1.95,3.7,3.75,1.9,3.9,3.75,1.91,4.12,3.8,1.91,3.9,3.7,1.87,4,3.5,2,4.12,3.84,1.91,3.93,3.69,1.5,2.62,1.51,2.71,1.54,2.72,1.5,2.58,-0.5,1.92,2.01,1.91,2.01,1.96,2.03,1.91,1.97,2.05,3.75,3.3,2,3.9,3.4,2.1,3.6,3.35,2.1,3.88,3.38,2.1,3.7,3.25,2.1,3.8,3.3,2.2,3.91,3.45,2.09,3.78,3.29,1.5,2.62,1.51,2.69,1.55,2.76,1.5,2.58,-0.25,1.84,2.09,1.84,2.08,1.86,2.14,1.83,2.05 83 | D1,01/11/2019,19:30,Hoffenheim,Paderborn,3,0,H,3,0,H,12,9,7,2,7,12,4,4,0,1,0,0,1.4,4.75,7,1.45,4.75,6.5,1.45,4.75,6.5,1.45,5.16,6.54,1.42,5,7,1.44,5,6.5,1.5,5.25,7.15,1.44,4.94,6.59,1.3,3.5,1.31,3.65,1.37,3.65,1.31,3.42,-1.25,1.9,2.03,1.91,2.01,1.95,2.05,1.89,1.98,1.4,4.5,7,1.44,5,6.5,1.45,4.75,6.5,1.47,5.06,6.51,1.42,4.8,7,1.45,5,6.5,1.49,5.3,7.4,1.45,4.95,6.48,1.36,3.2,1.34,3.47,1.37,3.47,1.33,3.29,-1.25,1.93,2,1.92,2,1.96,2.01,1.91,1.97 84 | D1,02/11/2019,14:30,Dortmund,Wolfsburg,3,0,H,0,0,D,17,12,8,3,12,18,7,2,1,3,0,0,1.5,4.5,6.5,1.5,4.33,6.5,1.55,4.2,5.9,1.56,4.14,6.67,1.5,4.33,6.5,1.53,4.5,5.75,1.59,4.5,6.95,1.53,4.25,6.31,1.61,2.3,1.65,2.36,1.68,2.36,1.64,2.28,-1,1.94,1.99,1.96,1.96,1.96,2.01,1.91,1.96,1.5,4.5,5.5,1.55,4.1,6.25,1.6,3.9,5.7,1.52,4.38,6.78,1.52,4.2,6.5,1.55,4.2,6.25,1.62,4.66,6.87,1.54,4.23,6.21,1.66,2.2,1.61,2.43,1.7,2.47,1.62,2.3,-1,1.88,2.05,1.89,2.02,2.08,2.08,1.89,1.98 85 | D1,02/11/2019,14:30,Ein Frankfurt,Bayern Munich,5,1,H,2,1,H,17,7,11,3,12,7,3,0,1,2,0,1,6.5,5.25,1.4,7,5,1.42,6,4.5,1.5,7.04,5.42,1.41,7,5.25,1.4,6.5,5.4,1.4,7.5,5.5,1.5,6.7,5.19,1.42,1.3,3.5,1.33,3.53,1.37,3.6,1.31,3.39,1.25,2.05,1.88,2.06,1.85,2.09,1.9,2.03,1.85,6.5,5.5,1.4,6.5,5.5,1.4,6,4.5,1.5,6.66,5.82,1.4,6.5,5.5,1.4,6.5,5.5,1.4,7,5.91,1.5,6.54,5.51,1.4,1.28,3.75,1.28,3.93,1.35,4.02,1.29,3.59,1.5,1.91,2.02,1.93,2,1.95,2.25,1.87,2.01 86 | D1,02/11/2019,14:30,Leverkusen,M'gladbach,1,2,A,1,2,A,23,11,6,6,13,8,13,0,2,1,1,0,1.95,3.9,3.5,2,3.9,3.4,1.97,3.85,3.5,2.04,3.84,3.61,2,3.75,3.5,2,3.9,3.5,2.1,3.95,3.7,2,3.82,3.5,1.5,2.62,1.51,2.71,1.55,2.71,1.5,2.57,-0.5,2.02,1.91,2.04,1.88,2.1,1.92,2.01,1.87,1.8,4,4,1.85,4,3.8,2.1,3.6,3.35,1.93,3.93,3.94,1.85,3.9,3.9,1.87,4,3.8,2.1,4.1,4.1,1.89,3.86,3.85,1.61,2.3,1.63,2.39,1.65,2.45,1.6,2.33,-0.5,1.9,2.03,1.93,2,2.1,2.04,1.91,1.96 87 | D1,02/11/2019,14:30,RB Leipzig,Mainz,8,0,H,5,0,H,19,10,12,2,10,7,3,4,0,1,0,0,1.33,5.25,8,1.36,5.25,8.25,1.37,5,8,1.35,5.39,9.08,1.33,5.25,9,1.36,5.5,7.5,1.38,5.55,9.5,1.35,5.32,8.32,1.4,3,1.41,3.08,1.5,3.08,1.42,2.87,-1.5,2.01,1.92,1.98,1.93,2.02,1.94,1.98,1.89,1.33,5.75,8.5,1.36,5.25,7.75,1.37,5,8,1.33,6,8.57,1.33,5.5,8.5,1.33,5.75,8.5,1.42,6.09,9.6,1.34,5.57,8.15,1.33,3.4,1.33,3.51,1.45,3.62,1.36,3.12,-1.5,1.9,2.03,1.88,2.03,2.09,2.07,1.92,1.96 88 | D1,02/11/2019,14:30,Werder Bremen,Freiburg,2,2,D,1,1,D,20,13,10,3,17,9,5,0,3,4,0,1,1.85,3.8,3.8,1.95,3.7,3.7,2.1,3.5,3.4,1.95,3.87,3.89,1.95,3.7,3.8,1.95,3.8,3.7,2.1,3.9,3.98,1.95,3.73,3.74,1.66,2.2,1.67,2.31,1.69,2.33,1.65,2.25,-0.5,1.97,1.96,1.95,1.97,2.1,1.97,1.95,1.92,1.8,4,3.8,1.87,3.8,4,2,3.6,3.6,1.88,3.98,4.09,1.88,3.9,3.8,1.85,4,3.9,2,4.14,4.2,1.88,3.84,3.93,1.57,2.37,1.61,2.44,1.65,2.47,1.6,2.34,-0.5,1.88,2.05,1.88,2.04,2,2.08,1.88,1.99 89 | D1,02/11/2019,17:30,Union Berlin,Hertha,1,0,H,0,0,D,16,8,6,3,14,9,1,4,1,1,0,0,2.87,3.3,2.5,2.8,3.4,2.5,2.8,3.3,2.55,2.86,3.42,2.58,2.8,3.3,2.55,2.8,3.3,2.6,2.88,3.45,2.61,2.81,3.34,2.53,1.9,1.9,1.94,1.96,1.95,1.97,1.9,1.91,0,2.06,1.87,2.06,1.85,2.08,1.88,2.03,1.84,2.45,3.3,2.87,2.8,3.4,2.5,2.85,3.3,2.5,2.64,3.43,2.78,2.6,3.4,2.7,2.5,3.4,2.88,2.85,3.48,2.88,2.62,3.37,2.7,1.9,1.9,1.93,1.98,1.97,2.05,1.87,1.94,0,1.89,2.04,1.91,2.01,1.97,2.09,1.89,1.99 90 | D1,03/11/2019,14:30,Fortuna Dusseldorf,FC Koln,2,0,H,1,0,H,9,8,3,1,10,20,3,4,1,3,0,0,2.8,3.4,2.5,2.7,3.7,2.45,2.7,3.65,2.45,2.77,3.69,2.51,2.7,3.6,2.5,2.63,3.7,2.4,2.85,3.8,2.6,2.72,3.63,2.46,1.57,2.37,1.62,2.41,1.63,2.5,1.57,2.4,0,2.06,1.87,2.06,1.86,2.07,1.9,2.03,1.85,2.9,3.4,2.4,2.75,3.5,2.5,2.7,3.45,2.55,2.96,3.46,2.48,2.9,3.4,2.45,2.9,3.4,2.45,3,3.55,2.6,2.88,3.42,2.45,1.72,2.1,1.82,2.08,1.84,2.35,1.77,2.07,0.25,1.81,2.13,1.79,2.14,1.84,2.2,1.79,2.11 91 | D1,03/11/2019,17:00,Augsburg,Schalke 04,2,3,A,1,1,D,12,11,4,3,12,10,1,6,3,5,0,0,4,3.6,1.85,3.9,3.7,1.91,3.7,3.7,1.95,3.83,3.92,1.95,3.7,3.8,1.95,3.6,3.75,1.9,4,4,1.99,3.75,3.79,1.93,1.72,2.1,1.76,2.16,1.77,2.24,1.71,2.14,0.5,1.97,1.96,1.96,1.95,1.98,1.97,1.94,1.93,4.5,3.75,1.75,4.2,3.8,1.83,3.7,3.5,2,4.31,4.05,1.81,4.4,3.9,1.78,4.1,4.1,1.8,4.62,4.1,2,4.18,3.91,1.81,1.61,2.3,1.61,2.42,1.67,2.5,1.61,2.34,0.5,2.05,1.75,2.11,1.81,2.16,1.93,2.08,1.81 92 | D1,08/11/2019,19:30,FC Koln,Hoffenheim,1,2,A,1,0,H,11,15,3,5,21,14,5,7,4,3,0,0,2.5,3.6,2.7,2.6,3.6,2.6,2.6,3.5,2.6,2.62,3.62,2.69,2.55,3.6,2.62,2.6,3.6,2.63,2.67,3.76,2.78,2.58,3.59,2.64,1.61,2.3,1.63,2.39,1.72,2.43,1.61,2.33,0,1.93,2,1.93,1.99,2.01,2.01,1.92,1.96,2.2,3.6,3,2.4,3.6,2.8,2.6,3.5,2.6,2.29,3.81,3.03,2.25,3.7,3,2.25,3.75,3,2.6,3.85,3.1,2.29,3.7,2.94,1.66,2.2,1.66,2.32,1.7,2.37,1.63,2.28,-0.25,2,1.93,2.01,1.91,2.05,1.96,1.99,1.89 93 | D1,09/11/2019,14:30,Hertha,RB Leipzig,2,4,A,1,2,A,7,10,3,7,12,12,0,5,2,1,0,0,4.2,4,1.8,4.2,3.9,1.8,4,3.85,1.85,4.19,3.93,1.86,4,3.8,1.85,3.9,4,1.85,4.3,4.05,1.91,4.06,3.88,1.84,1.57,2.37,1.59,2.48,1.63,2.48,1.59,2.36,0.5,2.06,1.87,2.05,1.86,2.1,1.88,2.04,1.84,4.33,4.2,1.7,4.25,4.25,1.72,4,3.8,1.85,4.56,4.3,1.72,4.6,4.2,1.7,4.4,4.2,1.73,4.85,4.38,1.85,4.4,4.16,1.73,1.5,2.62,1.51,2.7,1.54,2.71,1.5,2.57,0.75,2,1.93,2,1.92,2.01,2,1.96,1.92 94 | D1,09/11/2019,14:30,Mainz,Union Berlin,2,3,A,0,2,A,18,14,5,4,15,15,3,2,1,4,0,0,2.15,3.4,3.5,2.2,3.3,3.4,2.2,3.45,3.3,2.21,3.42,3.52,2.15,3.4,3.4,2.2,3.5,3.3,2.25,3.5,3.55,2.2,3.39,3.36,1.9,1.9,1.88,2.02,1.91,2.02,1.85,1.97,-0.25,1.92,2.01,1.9,2.02,1.93,2.02,1.89,1.99,2.37,3.4,2.87,2.2,3.4,3.3,2.35,3.35,3,2.51,3.34,3.01,2.35,3.3,3.1,2.45,3.4,2.9,2.52,3.5,3.35,2.37,3.34,3.08,1.9,1.9,1.89,2.01,1.92,2.08,1.86,1.96,-0.25,2.14,1.8,2.15,1.78,2.17,1.95,2.08,1.81 95 | D1,09/11/2019,14:30,Paderborn,Augsburg,0,1,A,0,1,A,12,13,4,5,15,12,5,7,1,3,0,0,2.62,3.75,2.5,2.6,3.8,2.5,2.5,3.5,2.7,2.61,3.86,2.58,2.55,3.75,2.55,2.6,3.8,2.55,2.65,3.9,2.7,2.59,3.75,2.54,1.44,2.75,1.47,2.83,1.47,2.99,1.44,2.77,0,1.98,1.95,1.97,1.95,2,1.96,1.95,1.93,2.5,3.75,2.6,2.4,3.8,2.7,2.6,3.5,2.6,2.62,3.62,2.69,2.55,3.7,2.55,2.55,3.8,2.55,2.7,3.85,2.75,2.53,3.69,2.63,1.53,2.5,1.56,2.57,1.56,2.75,1.5,2.58,0,1.9,2.03,1.93,1.98,2,2.05,1.91,1.97 96 | D1,09/11/2019,14:30,Schalke 04,Fortuna Dusseldorf,3,3,D,1,0,H,12,9,5,5,9,15,2,4,2,4,0,0,1.5,4.2,7,1.5,4.25,6.75,1.53,4.3,6.1,1.54,4.37,6.4,1.52,4.2,6.5,1.53,4.4,6.25,1.57,4.5,7,1.52,4.31,6.29,1.72,2.1,1.75,2.18,1.78,2.43,1.71,2.15,-1,1.9,2.03,1.93,1.99,1.93,2.03,1.88,1.98,1.61,4,5,1.67,3.8,5.25,1.67,3.9,5,1.68,3.93,5.48,1.62,4,5.5,1.67,4,5.2,1.7,4.14,5.75,1.66,3.93,5.24,1.8,2,1.83,2.07,1.85,2.2,1.78,2.05,-0.75,1.92,2.01,1.89,2.03,1.95,2.12,1.87,2.01 97 | D1,09/11/2019,17:30,Bayern Munich,Dortmund,4,0,H,1,0,H,17,2,5,0,11,12,2,1,2,1,0,0,1.53,4.75,5.5,1.57,4.6,5,1.7,4.2,4.4,1.57,4.62,5.61,1.55,4.5,5.5,1.53,4.75,5.5,1.7,4.8,5.75,1.56,4.57,5.32,1.4,3,1.43,2.99,1.45,3,1.41,2.87,-1,1.88,2.05,1.88,2.03,2,2.08,1.88,1.99,1.53,4.5,5.25,1.57,4.6,5,1.7,4.3,4.3,1.6,4.83,5.02,1.55,4.6,5.25,1.55,4.8,5.2,1.7,5,5.6,1.58,4.65,5.06,1.36,3.2,1.4,3.15,1.43,3.22,1.39,2.99,-1,1.92,2.01,1.93,1.99,2,2.06,1.92,1.95 98 | D1,10/11/2019,12:30,M'gladbach,Werder Bremen,3,1,H,2,0,H,17,16,7,7,17,11,3,8,5,4,1,0,1.72,4.1,4.33,1.72,4,4.5,1.73,4.15,4.4,1.75,4.21,4.47,1.75,4,4.33,1.7,4.2,4.1,1.8,4.34,4.67,1.73,4.12,4.35,1.53,2.5,1.51,2.7,1.57,2.7,1.5,2.56,-0.75,1.97,1.96,1.97,1.95,1.99,1.97,1.94,1.93,1.9,4,3.6,1.91,3.9,3.7,1.9,3.9,3.7,2.04,3.88,3.56,1.95,3.9,3.6,2,4,3.4,2.07,4.08,3.7,1.97,3.84,3.58,1.53,2.5,1.56,2.56,1.56,2.75,1.51,2.55,-0.5,2.06,1.87,2.04,1.88,2.09,1.95,1.99,1.88 99 | D1,10/11/2019,14:30,Wolfsburg,Leverkusen,0,2,A,0,1,A,9,9,1,4,8,9,9,0,2,2,0,0,2.87,3.6,2.37,2.9,3.5,2.4,3,3.45,2.3,3.02,3.58,2.39,3,3.5,2.35,2.8,3.6,2.3,3.1,3.78,2.45,2.96,3.47,2.36,1.8,2,1.83,2.07,1.85,2.29,1.78,2.04,0.25,1.86,2.07,1.85,2.07,1.88,2.1,1.83,2.04,3.1,3.6,2.15,3.1,3.5,2.25,3.1,3.55,2.25,3.25,3.67,2.23,3.2,3.6,2.2,3.2,3.6,2.2,3.28,3.72,2.32,3.16,3.57,2.22,1.72,2.1,1.73,2.21,1.82,2.25,1.72,2.14,0.25,2,1.93,1.98,1.94,2.02,1.97,1.96,1.92 100 | D1,10/11/2019,17:00,Freiburg,Ein Frankfurt,1,0,H,0,0,D,13,17,7,6,7,13,8,10,1,3,1,2,2.7,3.6,2.5,2.75,3.6,2.45,2.7,3.55,2.5,2.79,3.64,2.53,2.75,3.5,2.5,2.6,3.6,2.45,2.83,3.7,2.6,2.74,3.54,2.48,1.66,2.2,1.67,2.32,1.7,2.32,1.66,2.23,0,2.03,1.9,2.06,1.86,2.08,1.91,2.02,1.85,2.75,3.75,2.37,2.8,3.6,2.4,2.95,3.3,2.4,2.84,3.68,2.46,2.9,3.6,2.35,2.75,3.75,2.4,3.15,3.82,2.54,2.82,3.62,2.41,1.61,2.3,1.64,2.38,1.67,2.47,1.62,2.31,0.25,1.72,2.07,1.79,2.14,1.89,2.2,1.78,2.11 101 | D1,22/11/2019,19:30,Dortmund,Paderborn,3,3,D,0,3,A,18,10,7,4,8,7,10,2,3,1,0,0,1.14,9,15,1.15,8.5,16.5,1.17,8,14,1.15,8.81,17.75,1.15,8,17,1.15,9,15,1.18,9.15,19,1.15,8.57,16.15,1.22,4.33,1.21,4.63,1.23,4.63,1.22,4.19,-2.5,2,1.8,2.05,1.85,2.11,1.89,2.05,1.81,1.14,9,15,1.14,8.75,17,1.17,8,14,1.16,8.25,16.56,1.14,8.5,17,1.15,9,15,1.2,9.5,21,1.15,8.48,15.68,1.25,4,1.25,4.18,1.26,4.3,1.24,3.98,-2.25,2.01,1.92,2.03,1.87,2.04,2.02,1.94,1.92 102 | D1,23/11/2019,14:30,Ein Frankfurt,Wolfsburg,0,2,A,0,1,A,17,9,9,6,13,22,12,1,3,5,0,1,2,3.6,3.6,2,3.7,3.6,2,3.7,3.55,2.04,3.76,3.68,2,3.7,3.6,2.05,3.7,3.5,2.06,3.89,3.74,2.02,3.67,3.55,1.66,2.2,1.68,2.3,1.69,2.35,1.65,2.25,-0.5,2.04,1.89,2.04,1.88,2.05,1.89,2.01,1.85,2.05,3.6,3.5,2.15,3.5,3.3,2.1,3.55,3.35,2.13,3.61,3.52,2.05,3.5,3.6,2.1,3.6,3.4,2.15,3.66,3.82,2.1,3.56,3.43,1.66,2.2,1.71,2.24,1.74,2.33,1.68,2.18,-0.25,1.84,2.09,1.85,2.07,1.87,2.18,1.83,2.06 103 | D1,23/11/2019,14:30,Fortuna Dusseldorf,Bayern Munich,0,4,A,0,3,A,12,18,1,5,8,6,8,6,1,1,0,0,13,8,1.18,14.5,7.5,1.18,12.5,6.5,1.22,13.41,7.54,1.2,15,7.5,1.18,15,8,1.17,16.5,8.35,1.22,13.56,7.57,1.19,1.3,3.5,1.29,3.76,1.31,3.85,1.29,3.5,2,2.05,1.75,2.12,1.79,2.14,1.9,2.07,1.8,13,7,1.2,9.75,7,1.25,11,6.1,1.25,10.65,6.72,1.26,13,6.5,1.22,12,7,1.22,13.5,7.5,1.28,11.18,6.77,1.23,1.33,3.4,1.34,3.44,1.35,3.7,1.32,3.33,2,1.85,2.08,1.84,2.07,1.9,2.13,1.83,2.04 104 | D1,23/11/2019,14:30,Leverkusen,Freiburg,1,1,D,1,1,D,27,7,9,2,9,14,13,3,0,3,0,0,1.45,4.75,6.5,1.5,4.4,6.5,1.5,4.55,6,1.52,4.6,6.29,1.5,4.6,6,1.5,4.75,6,1.55,4.84,7,1.5,4.57,6.15,1.53,2.5,1.58,2.49,1.58,2.63,1.53,2.48,-1,1.72,2.07,1.84,2.08,1.85,2.14,1.79,2.07,1.44,4.75,6.5,1.48,4.5,6.75,1.55,4.3,5.7,1.46,4.58,7.76,1.42,4.75,7.5,1.45,4.75,7,1.55,4.9,7.93,1.45,4.6,6.99,1.66,2.2,1.65,2.35,1.7,2.36,1.64,2.26,-1.25,2.06,1.87,2.07,1.85,2.09,1.96,2.03,1.85 105 | D1,23/11/2019,14:30,Union Berlin,M'gladbach,2,0,H,1,0,H,11,12,6,2,12,7,2,6,1,1,0,0,3.6,3.6,2.05,3.4,3.6,2.1,3.35,3.6,2.1,3.52,3.7,2.1,3.4,3.6,2.1,3.4,3.7,2.1,3.7,3.8,2.16,3.4,3.63,2.09,1.72,2.1,1.71,2.24,1.75,2.25,1.69,2.17,0.25,2.08,1.85,2.09,1.83,2.11,1.87,2.06,1.81,3.4,3.8,2,3.7,3.75,1.95,4.1,3.5,1.9,3.6,3.75,2.06,3.6,3.7,2,3.4,3.8,2.05,4.1,3.9,2.08,3.56,3.7,2.01,1.66,2.2,1.68,2.28,1.75,2.32,1.67,2.21,0.5,1.88,2.05,1.85,2.06,1.9,2.08,1.85,2.02 106 | D1,23/11/2019,14:30,Werder Bremen,Schalke 04,1,2,A,0,1,A,16,10,5,5,12,15,1,3,3,2,0,0,2.45,3.5,2.8,2.45,3.6,2.75,2.45,3.6,2.75,2.47,3.71,2.82,2.45,3.6,2.75,2.45,3.7,2.75,2.55,3.75,2.84,2.45,3.62,2.74,1.57,2.37,1.61,2.43,1.63,2.45,1.59,2.36,0,1.85,2.08,1.83,2.09,1.88,2.09,1.83,2.04,2.7,3.6,2.45,2.7,3.4,2.6,2.55,3.5,2.65,2.84,3.41,2.6,2.75,3.5,2.5,2.7,3.6,2.5,2.91,3.68,2.85,2.7,3.45,2.58,1.72,2.1,1.7,2.25,1.72,2.39,1.68,2.2,0,2.07,1.86,2.05,1.87,2.11,1.94,2.01,1.87 107 | D1,23/11/2019,17:30,RB Leipzig,FC Koln,4,1,H,3,1,H,20,6,8,1,9,15,13,3,0,3,0,0,1.33,5.75,7.5,1.33,5.5,8.75,1.35,5.3,8,1.36,5.45,8.65,1.33,5.5,8.5,1.33,5.75,8,1.38,5.8,9,1.35,5.46,8.08,1.4,3,1.4,3.11,1.42,3.2,1.39,2.97,-1.5,2,1.93,2,1.92,2.01,2.01,1.95,1.91,1.44,4.75,6.5,1.42,4.75,7.25,1.4,4.8,7.6,1.42,5.01,7.63,1.42,4.75,7.5,1.44,5,6.5,1.47,5.1,7.75,1.43,4.87,7,1.44,2.75,1.45,2.9,1.48,2.95,1.43,2.79,-1.25,1.97,1.96,1.95,1.97,1.99,1.98,1.93,1.94 108 | D1,24/11/2019,14:30,Augsburg,Hertha,4,0,H,2,0,H,14,5,5,1,8,18,3,3,0,2,0,1,2.62,3.5,2.62,2.55,3.6,2.65,2.6,3.5,2.6,2.62,3.66,2.67,2.6,3.5,2.62,2.5,3.6,2.55,2.68,3.7,2.7,2.59,3.53,2.61,1.72,2.1,1.7,2.26,1.73,2.27,1.68,2.18,0,1.95,1.98,1.94,1.98,1.96,1.99,1.92,1.94,2.45,3.6,2.62,2.55,3.5,2.7,2.55,3.6,2.6,2.68,3.68,2.6,2.5,3.6,2.7,2.5,3.6,2.7,2.8,3.75,3.02,2.56,3.57,2.65,1.61,2.3,1.68,2.29,1.78,2.47,1.65,2.25,0,1.96,1.97,1.99,1.93,2.04,2.17,1.91,1.97 109 | D1,24/11/2019,17:00,Hoffenheim,Mainz,1,5,A,0,1,A,22,11,8,5,10,13,14,3,1,3,0,1,1.65,4.33,4.75,1.65,4.1,5,1.67,4.1,4.7,1.68,4.08,5.24,1.65,4.2,5,1.65,4.2,4.5,1.72,4.33,5.3,1.66,4.07,4.88,1.53,2.5,1.6,2.47,1.6,2.67,1.53,2.46,-1,2.07,1.72,2.13,1.8,2.19,1.82,2.11,1.76,1.66,4,4.75,1.67,4,5,1.65,4,5,1.73,3.96,4.97,1.7,3.9,5,1.7,4.1,4.6,1.75,4.3,5.1,1.7,3.96,4.83,1.61,2.3,1.64,2.37,1.65,2.55,1.6,2.34,-0.75,1.95,1.98,1.94,1.98,1.98,2.12,1.9,1.97 110 | D1,29/11/2019,19:30,Schalke 04,Union Berlin,2,1,H,1,1,D,17,17,8,7,12,13,7,4,1,4,0,0,1.66,4,4.75,1.67,4,5,1.7,3.8,5,1.74,3.82,5.15,1.7,3.8,5,1.73,4,4.6,1.76,4.03,5.25,1.71,3.87,4.93,1.72,2.1,1.79,2.11,1.85,2.19,1.76,2.07,-0.75,1.97,1.96,1.97,1.95,1.99,1.98,1.93,1.94,1.66,4,4.75,1.67,4,5,1.7,3.8,5,1.72,3.78,5.4,1.7,4,5.25,1.7,3.9,5,1.8,4.1,5.48,1.71,3.8,5,1.9,1.9,1.99,1.92,2.02,2.12,1.9,1.93,-0.75,1.94,1.99,1.95,1.97,1.97,2.05,1.92,1.95 111 | D1,30/11/2019,14:30,FC Koln,Augsburg,1,1,D,0,1,A,13,11,6,4,15,17,4,8,8,3,1,1,1.95,4,3.5,1.95,3.8,3.7,2,3.6,3.6,1.91,3.89,4.03,1.88,3.8,3.9,1.9,4,3.75,2,4,4.08,1.92,3.76,3.82,1.66,2.2,1.73,2.21,1.73,2.36,1.64,2.26,-0.5,1.93,2,1.93,1.99,2,2.02,1.92,1.95,1.95,3.75,3.6,1.91,3.75,3.8,1.9,3.7,3.9,2.03,3.79,3.69,2,3.75,3.5,2,3.9,3.5,2.1,4,3.9,1.98,3.76,3.64,1.66,2.2,1.67,2.32,1.7,2.36,1.65,2.24,-0.5,2.03,1.9,2.03,1.89,2.06,1.95,2,1.87 112 | D1,30/11/2019,14:30,Hertha,Dortmund,1,2,A,1,2,A,13,7,3,5,13,8,2,2,3,2,0,1,4,4,1.8,4.4,3.8,1.78,4.1,3.7,1.85,4.23,3.96,1.85,4,3.9,1.83,4,4,1.83,4.4,4.12,1.9,4.1,3.9,1.83,1.61,2.3,1.63,2.4,1.65,2.4,1.61,2.32,0.75,1.75,2.05,1.83,2.1,1.85,2.12,1.81,2.06,4.33,4,1.7,4.25,4.1,1.75,4.1,3.7,1.85,4.5,4.28,1.74,4.6,4.2,1.7,4.4,4.1,1.75,4.84,4.32,1.85,4.32,4.09,1.75,1.53,2.5,1.56,2.54,1.61,2.55,1.56,2.42,0.75,1.97,1.96,1.98,1.94,2,1.99,1.94,1.94 113 | D1,30/11/2019,14:30,Hoffenheim,Fortuna Dusseldorf,1,1,D,1,0,H,12,11,6,3,11,16,2,5,2,4,0,0,1.7,3.8,5,1.67,4.1,4.75,1.7,3.95,4.65,1.71,4.04,5.03,1.67,4,4.8,1.7,4,4.8,1.74,4.3,5.1,1.7,3.97,4.79,1.57,2.37,1.61,2.43,1.65,2.46,1.6,2.32,-0.75,1.92,2.01,1.9,2.01,1.93,2.02,1.89,1.98,1.75,3.9,4.2,1.75,4,4.4,1.77,3.9,4.35,1.77,3.88,4.82,1.75,3.8,4.6,1.8,3.9,4.33,1.81,4.02,4.89,1.77,3.85,4.48,1.66,2.2,1.67,2.31,1.68,2.45,1.62,2.29,-0.75,1.99,1.94,1.99,1.93,2.04,1.96,1.97,1.9 114 | D1,30/11/2019,14:30,Paderborn,RB Leipzig,2,3,A,0,3,A,8,18,4,6,10,13,6,6,3,3,0,0,6.5,5.5,1.36,8,5.25,1.36,7.5,5.3,1.37,7.97,5.55,1.37,7.5,5.5,1.36,7.5,5.5,1.36,8.5,5.8,1.4,7.46,5.46,1.37,1.3,3.5,1.34,3.5,1.37,3.6,1.33,3.29,1.5,1.96,1.97,1.98,1.94,1.98,2.06,1.92,1.95,7.5,6,1.3,7.5,5.5,1.36,8,5.3,1.35,6.97,6.37,1.36,7.5,6,1.33,8.5,6,1.3,8.9,6.48,1.39,7.41,5.96,1.34,1.28,3.75,1.29,3.84,1.33,3.85,1.29,3.54,1.5,2.05,1.88,2.05,1.87,2.09,1.95,2,1.86 115 | D1,30/11/2019,17:30,Bayern Munich,Leverkusen,1,2,A,1,2,A,24,11,11,7,9,16,8,2,1,3,0,1,1.28,6,8.5,1.3,5.75,9,1.3,6,8.7,1.29,6,9.85,1.27,6,10,1.3,6,9.5,1.32,6.63,11,1.29,6.04,9.37,1.3,3.5,1.32,3.55,1.34,3.71,1.31,3.4,-1.75,2,1.93,1.97,1.93,2.01,1.95,1.96,1.91,1.22,7,10,1.25,6.5,10.5,1.3,6,8.7,1.26,6.67,10.8,1.22,7,11,1.25,7,10.5,1.3,7.4,12,1.25,6.65,10.46,1.25,4,1.25,4.23,1.3,4.24,1.24,3.93,-2,2.02,1.91,2.01,1.9,2.15,1.98,2.01,1.86 116 | D1,01/12/2019,14:30,M'gladbach,Freiburg,4,2,H,1,1,D,22,13,13,5,13,15,2,3,3,2,0,0,1.53,4.2,6,1.57,4.33,5.5,1.57,4.4,5.5,1.58,4.56,5.58,1.57,4.33,5.5,1.53,4.4,5.2,1.63,4.65,6,1.56,4.41,5.44,1.57,2.37,1.56,2.57,1.65,2.57,1.55,2.42,-1,1.97,1.96,1.97,1.95,2.03,1.98,1.94,1.92,1.53,4.5,5.5,1.57,4.33,5.5,1.6,4.1,5.5,1.55,4.42,6.22,1.52,4.4,6,1.55,4.5,5.75,1.6,4.6,6.37,1.55,4.37,5.8,1.66,2.2,1.65,2.35,1.66,2.53,1.6,2.33,-1,1.96,1.97,1.95,1.97,1.97,1.99,1.93,1.94 117 | D1,01/12/2019,17:00,Wolfsburg,Werder Bremen,2,3,A,1,2,A,19,10,6,3,14,14,9,3,1,4,0,0,2.15,3.75,3,2.15,3.7,3.2,2.2,3.6,3.15,2.2,3.71,3.27,2.15,3.7,3.2,2.1,3.7,3.1,2.25,3.8,3.3,2.17,3.64,3.17,1.72,2.1,1.74,2.19,1.75,2.25,1.7,2.16,-0.25,1.93,2,1.93,2,1.94,2.01,1.9,1.97,2,3.75,3.3,2.1,3.6,3.4,2.1,3.6,3.35,2.12,3.72,3.45,2.05,3.6,3.5,2.1,3.75,3.3,2.26,3.88,3.76,2.11,3.62,3.36,1.72,2.1,1.72,2.22,1.75,2.26,1.7,2.16,-0.25,1.85,2.08,1.85,2.07,1.89,2.19,1.84,2.04 118 | D1,02/12/2019,19:30,Mainz,Ein Frankfurt,2,1,H,0,1,A,18,14,8,4,13,10,8,6,1,2,0,1,2.8,3.75,2.37,2.8,3.7,2.35,2.8,3.55,2.4,2.91,3.6,2.45,2.8,3.6,2.4,2.7,3.75,2.3,3.04,3.95,2.5,2.81,3.59,2.4,1.57,2.37,1.6,2.45,1.63,2.55,1.57,2.37,0.25,1.81,2.13,1.81,2.12,1.84,2.13,1.78,2.09,2.75,3.8,2.25,2.8,3.75,2.35,2.85,3.4,2.45,3.04,3.91,2.25,3,3.75,2.2,2.9,3.8,2.3,3.18,4.03,2.45,2.91,3.78,2.28,1.44,2.75,1.47,2.85,1.55,3.02,1.45,2.71,0.25,1.94,1.99,1.93,1.98,1.99,2.1,1.9,1.97 119 | D1,06/12/2019,19:30,Ein Frankfurt,Hertha,2,2,D,0,1,A,25,9,6,3,11,15,16,1,3,4,0,0,1.8,3.9,4.2,1.8,3.9,4.2,1.85,3.8,4,1.85,4.04,4.16,1.8,3.9,4.2,1.83,4,4,1.9,4.09,4.3,1.83,3.91,4.11,1.57,2.37,1.6,2.46,1.63,2.55,1.59,2.37,-0.5,1.85,2.08,1.85,2.07,1.9,2.11,1.83,2.04,1.72,4,4.33,1.75,4,4.33,1.85,3.8,4,1.82,3.95,4.38,1.73,3.9,4.6,1.8,4,4.1,1.85,4.15,4.94,1.78,3.98,4.28,1.61,2.3,1.64,2.36,1.65,2.55,1.6,2.34,-0.5,1.77,2.02,1.82,2.1,1.85,2.17,1.8,2.07 120 | D1,07/12/2019,14:30,Augsburg,Mainz,2,1,H,1,1,D,18,12,5,3,13,14,8,2,2,2,0,0,2.2,3.6,3.1,2.35,3.6,2.9,2.25,3.6,3,2.28,3.7,3.11,2.3,3.6,3,2.3,3.7,2.9,2.35,3.75,3.13,2.28,3.62,2.99,1.61,2.3,1.62,2.41,1.65,2.41,1.62,2.3,-0.25,2.02,1.91,1.99,1.93,2.04,1.93,1.99,1.88,2.1,3.8,3.2,2.25,3.7,3,2.3,3.4,3.1,2.17,3.9,3.2,2.15,3.75,3.1,2.2,3.75,3.13,2.3,3.94,3.23,2.19,3.72,3.1,1.53,2.5,1.56,2.57,1.65,2.66,1.56,2.44,-0.25,1.91,2.02,1.91,2.01,1.96,2.05,1.91,1.96 121 | D1,07/12/2019,14:30,Dortmund,Fortuna Dusseldorf,5,0,H,1,0,H,23,2,10,0,8,10,6,0,0,3,0,0,1.33,5.5,8.5,1.3,5.75,9.5,1.3,5.5,9.6,1.31,5.86,9.9,1.3,5.8,9.5,1.3,6,9,1.35,6.1,10.25,1.3,5.75,9.24,1.4,3,1.41,3.08,1.44,3.08,1.41,2.88,-1.5,1.9,2.03,1.92,2,1.92,2.09,1.87,2,1.3,5.5,8.5,1.33,5.5,8.75,1.33,5.3,8.8,1.32,5.72,9.94,1.3,5.8,9.5,1.33,5.5,9,1.34,5.95,10.15,1.32,5.56,9.11,1.4,3,1.41,3.06,1.46,3.19,1.41,2.88,-1.5,1.93,2,1.93,2,1.95,2.12,1.9,1.97 122 | D1,07/12/2019,14:30,Freiburg,Wolfsburg,1,0,H,0,0,D,10,10,3,0,13,20,2,7,0,2,0,0,2.9,3.5,2.4,2.8,3.5,2.45,2.9,3.3,2.45,2.92,3.43,2.53,2.88,3.4,2.45,2.88,3.5,2.4,3,3.5,2.6,2.88,3.36,2.46,1.9,1.9,1.93,1.97,1.95,2.01,1.88,1.93,0.25,1.75,2.05,1.77,2.17,1.82,2.19,1.76,2.13,3.25,3.5,2.15,3.2,3.4,2.25,2.85,3.3,2.5,3.28,3.49,2.28,3.2,3.4,2.25,3.2,3.5,2.25,3.34,3.58,2.5,3.19,3.41,2.27,1.9,1.9,1.97,1.93,2.02,2.05,1.91,1.9,0.25,1.96,1.97,1.94,1.98,1.97,1.99,1.92,1.95 123 | D1,07/12/2019,14:30,M'gladbach,Bayern Munich,2,1,H,0,0,D,7,17,3,5,12,17,2,5,3,5,0,1,5.25,4.5,1.57,5.25,4.75,1.55,4.6,4.3,1.65,5.51,4.67,1.57,5.25,4.5,1.57,5.25,4.75,1.55,5.6,4.8,1.65,5.24,4.61,1.56,1.36,3.2,1.35,3.4,1.4,3.4,1.35,3.15,1,2.03,1.9,2.02,1.89,2.04,2,1.98,1.88,5,5.25,1.5,5,5,1.53,4.6,4.3,1.65,5.44,5.06,1.53,5.5,5,1.5,5.4,5.2,1.5,5.75,5.35,1.65,5.27,4.95,1.52,1.28,3.75,1.3,3.73,1.35,4.02,1.3,3.49,1.25,1.85,2.08,1.85,2.06,1.95,2.12,1.84,2.03 124 | D1,07/12/2019,14:30,RB Leipzig,Hoffenheim,3,1,H,1,0,H,25,11,14,1,14,5,8,6,3,1,0,0,1.44,4.75,6.5,1.42,5.25,6.5,1.5,4.6,5.9,1.45,5.16,6.73,1.42,5,7,1.44,5,6.5,1.52,5.25,7.2,1.44,4.98,6.48,1.4,3,1.43,2.97,1.47,3,1.42,2.82,-1.25,1.96,1.97,1.94,1.98,1.98,1.98,1.93,1.94,1.4,5,6.5,1.4,5.25,7,1.5,4.6,5.9,1.4,5.28,7.57,1.38,5.25,7.5,1.4,5.2,7,1.5,5.45,8.4,1.4,5.14,7.11,1.36,3.2,1.38,3.23,1.42,3.44,1.38,3.03,-1.25,1.86,2.07,1.83,2.08,1.89,2.16,1.83,2.04 125 | D1,07/12/2019,17:30,Leverkusen,Schalke 04,2,1,H,1,0,H,19,5,9,3,11,11,9,0,2,2,0,0,1.95,3.75,3.75,1.91,3.6,4,1.95,3.65,3.8,1.98,3.75,3.9,1.91,3.7,3.9,1.95,3.8,3.75,1.99,3.8,4.05,1.94,3.66,3.85,1.72,2.1,1.73,2.21,1.79,2.22,1.72,2.13,-0.5,1.97,1.96,1.98,1.93,1.98,1.97,1.94,1.92,2,3.8,3.3,1.95,3.8,3.6,2.05,3.6,3.5,2.13,3.79,3.38,2.1,3.75,3.3,2.1,3.8,3.25,2.16,4,3.6,2.07,3.74,3.38,1.57,2.37,1.55,2.57,1.6,2.61,1.54,2.46,-0.25,1.87,2.06,1.86,2.06,1.9,2.2,1.83,2.06 126 | D1,08/12/2019,14:30,Union Berlin,FC Koln,2,0,H,1,0,H,11,14,5,4,21,19,3,5,1,3,0,0,2.15,3.5,3.3,2.2,3.4,3.3,2.15,3.5,3.3,2.19,3.6,3.39,2.15,3.5,3.3,2.1,3.5,3.25,2.34,3.6,3.5,2.18,3.47,3.29,1.8,2,1.86,2.04,1.9,2.08,1.81,2,-0.25,1.9,2.03,1.9,2.02,1.93,2.05,1.88,1.98,2.1,3.5,3.4,2.1,3.5,3.5,2.1,3.45,3.45,2.14,3.55,3.56,2.1,3.5,3.5,2.15,3.5,3.5,2.2,3.6,3.6,2.12,3.49,3.46,1.8,2,1.88,2.01,1.99,2.07,1.85,1.96,-0.25,1.86,2.07,1.85,2.06,1.88,2.11,1.84,2.03 127 | D1,08/12/2019,17:00,Werder Bremen,Paderborn,0,1,A,0,0,D,12,18,3,5,10,13,13,6,1,4,0,0,1.53,4.5,5.75,1.5,4.75,5.75,1.55,4.7,5.3,1.56,4.66,5.65,1.52,4.75,5.5,1.5,4.75,5.2,1.6,4.9,6,1.53,4.63,5.49,1.33,3.4,1.35,3.41,1.37,3.6,1.33,3.29,-1,1.85,2.08,1.85,2.06,1.87,2.11,1.83,2.03,1.5,5,5.5,1.5,4.75,5.75,1.45,4.8,6.4,1.53,4.93,5.59,1.5,4.6,6,1.53,4.8,5.4,1.57,5.05,6.55,1.51,4.81,5.62,1.33,3.4,1.34,3.47,1.36,3.7,1.32,3.32,-1.25,2,1.8,2.07,1.85,2.14,1.99,2.04,1.83 128 | D1,13/12/2019,19:30,Hoffenheim,Augsburg,2,4,A,1,1,D,19,6,8,4,10,7,11,1,1,0,0,0,1.8,4,4.2,1.85,3.9,4,1.85,3.8,4.05,1.85,4.06,4.11,1.83,3.9,4,1.85,4,3.9,1.89,4.2,4.34,1.84,3.98,4.02,1.53,2.5,1.57,2.52,1.62,2.63,1.56,2.42,-0.5,1.88,2.05,1.86,2.06,1.9,2.1,1.84,2.03,1.9,3.8,3.75,1.95,3.8,3.7,1.9,3.8,3.8,1.95,3.94,3.81,1.88,3.9,3.8,1.95,3.9,3.6,2,4.1,4.1,1.92,3.87,3.74,1.57,2.37,1.61,2.44,1.62,2.57,1.57,2.39,-0.5,1.96,1.97,1.95,1.97,1.99,1.98,1.92,1.94 129 | D1,14/12/2019,14:30,Bayern Munich,Werder Bremen,6,1,H,2,1,H,29,11,14,2,13,12,8,2,2,2,0,0,1.14,9,15,1.14,8.5,17.5,1.15,8.2,15.5,1.15,8.78,18.35,1.14,8.5,17,1.14,8.5,19,1.18,9.65,20,1.15,8.74,16.7,1.22,4.33,1.22,4.5,1.25,4.6,1.22,4.16,-2.5,2.03,1.9,2,1.9,2.04,1.91,2,1.86,1.12,10,17,1.12,10,17,1.2,7,13,1.11,11.24,21.16,1.11,10,19,1.09,11,26,1.2,12,26,1.11,10.37,19.89,1.2,4.5,1.16,5.49,1.22,5.5,1.17,4.77,-2.75,1.93,2,1.93,1.98,1.95,2.03,1.92,1.95 130 | D1,14/12/2019,14:30,FC Koln,Leverkusen,2,0,H,0,0,D,13,6,5,2,12,9,3,4,2,3,0,2,4.2,3.9,1.8,4,3.9,1.85,4.05,3.9,1.83,4.24,3.91,1.85,4,3.9,1.83,4.2,4,1.8,4.4,4.05,1.9,4.13,3.9,1.83,1.57,2.37,1.63,2.39,1.64,2.45,1.59,2.35,0.75,1.77,2.02,1.82,2.1,1.9,2.1,1.82,2.05,4,3.75,1.9,4,3.9,1.85,3.9,3.7,1.9,3.78,3.77,2.01,3.8,3.75,1.91,3.7,3.9,1.93,4.05,4.02,2.02,3.83,3.81,1.91,1.57,2.37,1.61,2.44,1.62,2.5,1.58,2.38,0.5,1.95,1.98,1.91,2.01,2.01,2.03,1.94,1.92 131 | D1,14/12/2019,14:30,Hertha,Freiburg,1,0,H,0,0,D,14,15,4,2,9,5,4,7,2,0,0,0,2,3.6,3.6,2.05,3.6,3.5,2,3.6,3.6,2.02,3.75,3.74,2,3.6,3.7,2.05,3.75,3.5,2.12,3.75,3.75,2.03,3.63,3.59,1.8,2,1.85,2.06,1.85,2.12,1.79,2.04,-0.5,2.06,1.87,2.02,1.89,2.1,1.89,2.03,1.84,1.85,3.5,4.2,1.95,3.6,3.9,2.05,3.4,3.7,1.96,3.67,4.1,1.88,3.6,4.2,1.91,3.75,3.9,2.05,3.76,4.34,1.94,3.63,3.91,1.8,2,1.79,2.12,1.82,2.15,1.77,2.05,-0.5,1.95,1.98,1.96,1.96,2.05,1.99,1.94,1.92 132 | D1,14/12/2019,14:30,Mainz,Dortmund,0,4,A,0,1,A,9,18,0,7,8,10,3,5,1,0,0,0,5,4.33,1.6,5.25,4.2,1.62,4.8,4.2,1.65,5.05,4.22,1.68,5.25,4,1.63,4.8,4.2,1.67,5.3,4.54,1.69,4.95,4.19,1.65,1.44,2.75,1.48,2.8,1.49,2.88,1.46,2.7,1,1.83,2.1,1.81,2.12,1.9,2.12,1.8,2.07,6,4.75,1.5,5.5,5,1.5,5.5,4.4,1.55,6.29,4.81,1.5,6.5,4.75,1.47,6,4.8,1.5,6.5,5.05,1.6,5.84,4.79,1.5,1.36,3.2,1.39,3.18,1.43,3.2,1.38,3.02,1,2.07,1.72,2.15,1.78,2.17,1.97,2.09,1.78 133 | D1,14/12/2019,14:30,Paderborn,Union Berlin,1,1,D,1,1,D,14,15,3,2,19,16,2,3,2,4,0,0,2.8,3.75,2.37,2.85,3.5,2.4,2.8,3.6,2.4,2.83,3.65,2.49,2.8,3.6,2.4,2.8,3.6,2.45,2.95,3.85,2.55,2.8,3.58,2.43,1.66,2.2,1.67,2.31,1.7,2.35,1.64,2.26,0,2.09,1.84,2.09,1.83,2.14,1.85,2.07,1.81,2.87,3.75,2.3,2.7,3.6,2.5,2.7,3.5,2.5,2.91,3.62,2.44,2.8,3.6,2.4,2.8,3.7,2.4,2.93,3.82,2.55,2.78,3.61,2.43,1.66,2.2,1.65,2.35,1.7,2.41,1.64,2.26,0.25,1.77,2.02,1.81,2.12,1.84,2.16,1.78,2.1 134 | D1,14/12/2019,17:30,Fortuna Dusseldorf,RB Leipzig,0,3,A,0,1,A,4,21,1,7,11,7,3,9,2,1,0,0,7,4.75,1.44,6.25,5,1.45,6.6,4.7,1.45,6.77,5.11,1.45,6.5,5,1.44,6.5,5,1.45,7.05,5.25,1.47,6.52,4.93,1.44,1.44,2.75,1.47,2.83,1.52,2.85,1.46,2.7,1.25,1.94,1.99,1.97,1.95,1.97,2.01,1.91,1.94,6.5,5,1.4,6.75,5,1.42,7.2,5,1.4,6.57,5.06,1.46,7,5,1.42,6.5,5,1.45,7.4,5.25,1.48,6.7,4.99,1.43,1.5,2.62,1.5,2.74,1.5,2.92,1.46,2.69,1.25,1.88,2.05,1.86,2.06,1.95,2.08,1.9,1.96 135 | D1,15/12/2019,14:30,Wolfsburg,M'gladbach,2,1,H,1,1,D,17,6,7,5,20,15,5,2,3,3,0,0,2.7,3.4,2.6,2.6,3.5,2.65,2.6,3.45,2.65,2.62,3.43,2.81,2.6,3.3,2.75,2.55,3.4,2.63,2.75,3.66,2.81,2.6,3.41,2.68,1.72,2.1,1.78,2.13,1.79,2.19,1.74,2.09,0,1.92,2.01,1.88,2.03,1.97,2.03,1.89,1.96,2.62,3.5,2.6,2.65,3.4,2.65,2.6,3.5,2.6,2.68,3.51,2.69,2.75,3.4,2.55,2.63,3.5,2.63,2.91,3.6,2.72,2.64,3.48,2.61,1.72,2.1,1.74,2.19,1.8,2.26,1.71,2.13,0,1.96,1.97,1.95,1.97,2.05,2,1.94,1.93 136 | D1,15/12/2019,17:00,Schalke 04,Ein Frankfurt,1,0,H,0,0,D,11,17,5,3,15,12,7,6,1,4,1,0,1.9,3.75,3.6,2,3.7,3.6,1.95,3.8,3.6,1.97,3.93,3.77,1.95,3.8,3.6,1.93,3.8,3.5,2.01,4,3.78,1.96,3.79,3.61,1.66,2.2,1.66,2.33,1.74,2.33,1.66,2.22,-0.5,1.99,1.94,1.97,1.95,2.01,1.95,1.96,1.89,1.9,3.8,3.8,1.95,3.8,3.6,2,3.6,3.6,1.88,4.03,3.99,1.88,3.9,3.8,1.87,3.9,3.9,2.01,4.05,4.05,1.9,3.89,3.8,1.57,2.37,1.61,2.43,1.64,2.5,1.58,2.38,-0.5,1.88,2.05,1.88,2.03,2,2.08,1.88,1.98 137 | D1,17/12/2019,17:30,Werder Bremen,Mainz,0,5,A,0,4,A,15,19,5,8,13,13,8,5,2,2,0,0,1.75,4.2,4.2,1.8,4,4.1,1.85,3.9,3.9,1.84,4.01,4.2,1.83,3.9,4,1.83,4.1,3.9,1.87,4.32,4.32,1.82,4,4.08,1.4,3,1.45,2.91,1.47,3,1.43,2.8,-0.75,2.06,1.87,2.07,1.85,2.07,1.88,2.03,1.84,1.66,4.33,4.5,1.72,4.2,4.33,1.85,3.9,3.9,1.71,4.29,4.67,1.67,4.2,4.75,1.7,4.4,4.33,1.85,4.42,4.85,1.7,4.25,4.47,1.36,3.2,1.39,3.16,1.45,3.22,1.37,3.04,-0.75,1.91,2.02,1.9,2.02,1.94,2.1,1.87,2 138 | D1,17/12/2019,19:30,Augsburg,Fortuna Dusseldorf,3,0,H,1,0,H,12,6,7,2,10,15,4,2,3,4,0,0,1.75,4.2,4.2,1.72,4,4.5,1.7,4,4.6,1.81,4.15,4.24,1.78,4,4.2,1.8,4,4.2,1.85,4.32,4.6,1.78,4.04,4.21,1.66,2.2,1.68,2.3,1.69,2.38,1.65,2.25,-0.75,2.06,1.87,2.05,1.87,2.09,1.89,2.03,1.84,1.85,3.8,4,1.87,3.75,4,1.8,3.9,4.1,1.93,3.85,4.01,1.85,3.7,4.2,1.87,4,3.8,2,4,4.34,1.9,3.75,3.91,1.72,2.1,1.7,2.25,1.74,2.3,1.67,2.19,-0.5,1.93,2,1.93,1.99,1.95,2.02,1.9,1.96 139 | D1,17/12/2019,19:30,Dortmund,RB Leipzig,3,3,D,2,0,H,14,12,6,8,9,5,12,3,0,0,0,0,2.1,3.8,3.2,2.1,3.8,3.25,2.2,3.8,3,2.24,3.79,3.14,2.2,3.7,3.1,2.25,3.8,3,2.3,3.92,3.33,2.19,3.76,3.11,1.44,2.75,1.46,2.88,1.48,2.95,1.44,2.76,-0.25,1.97,1.96,1.96,1.96,2,1.98,1.93,1.93,2.15,3.9,3,2.2,3.75,3,2.3,3.7,2.9,2.25,3.86,3.07,2.2,3.8,3,2.25,3.8,2.9,2.35,3.98,3.16,2.22,3.8,2.99,1.4,3,1.41,3.08,1.47,3.08,1.41,2.85,-0.25,1.99,1.94,1.98,1.94,2.05,1.95,1.95,1.91 140 | D1,17/12/2019,19:30,Union Berlin,Hoffenheim,0,2,A,0,0,D,16,7,2,4,16,13,6,1,2,6,0,0,2.37,3.5,2.9,2.35,3.6,2.9,2.45,3.45,2.85,2.5,3.54,2.88,2.45,3.4,2.88,2.45,3.5,2.88,2.52,3.61,3,2.44,3.48,2.86,1.8,2,1.82,2.08,1.84,2.11,1.79,2.03,-0.25,2.07,1.72,2.16,1.78,2.17,1.8,2.12,1.77,2.3,3.6,2.87,2.4,3.5,2.85,2.35,3.5,2.95,2.46,3.58,2.91,2.35,3.6,2.9,2.4,3.5,2.9,2.5,3.7,3.04,2.39,3.5,2.89,1.8,2,1.86,2.03,1.9,2.13,1.79,2.02,-0.25,2.1,1.83,2.13,1.79,2.17,1.85,2.09,1.8 141 | D1,18/12/2019,17:30,Leverkusen,Hertha,0,1,A,0,0,D,17,10,7,5,12,16,5,4,2,3,0,0,1.5,4.33,6.5,1.57,4,6,1.6,4.2,5.3,1.54,4.44,6.27,1.53,4.33,6,1.55,4.4,5.75,1.6,4.61,6.63,1.54,4.33,5.97,1.53,2.5,1.51,2.69,1.55,2.69,1.51,2.53,-1,1.9,2.03,1.88,2.03,1.93,2.05,1.87,1.98,1.5,4.5,6,1.53,4.33,6,1.6,4.2,5.3,1.52,4.58,6.33,1.5,4.33,6.5,1.53,4.5,5.75,1.6,4.65,6.8,1.51,4.45,6.12,1.53,2.5,1.54,2.6,1.56,2.69,1.52,2.5,-1,1.88,2.05,1.85,2.06,1.93,2.16,1.84,2.02 142 | D1,18/12/2019,19:30,Ein Frankfurt,FC Koln,2,4,A,2,1,H,17,21,6,9,12,10,7,10,2,4,0,0,1.75,3.8,4.75,1.7,4,4.75,1.8,3.8,4.2,1.76,3.86,4.88,1.75,3.75,4.75,1.8,3.9,4.33,1.8,4.04,4.9,1.75,3.85,4.59,1.57,2.37,1.61,2.44,1.62,2.45,1.58,2.37,-0.75,2,1.93,1.98,1.93,2.01,1.95,1.96,1.9,1.9,3.8,3.8,1.91,3.6,4,1.85,3.8,4,1.97,3.78,3.91,1.88,3.7,4,1.95,3.8,3.7,1.98,3.9,4.2,1.92,3.73,3.86,1.61,2.3,1.63,2.39,1.65,2.5,1.59,2.35,-0.5,1.96,1.97,1.97,1.95,1.98,1.99,1.92,1.93 143 | D1,18/12/2019,19:30,Freiburg,Bayern Munich,1,3,A,0,1,A,15,22,5,10,5,8,6,8,0,3,0,0,10,7.5,1.22,10.5,6.5,1.25,11,6.1,1.25,10.96,6.86,1.24,11,7,1.22,12,7,1.22,15,7.6,1.27,11.08,6.88,1.23,1.28,3.75,1.28,3.81,1.31,3.85,1.28,3.6,2,1.98,1.95,1.98,1.92,1.99,2.05,1.93,1.93,12,7.5,1.18,10.5,7.5,1.22,10.5,5.8,1.27,9.96,8.73,1.22,12,8,1.18,13,7.5,1.2,13,8.73,1.27,11.36,7.87,1.2,1.25,4,1.24,4.33,1.29,4.34,1.24,3.93,2.25,1.97,1.96,1.96,1.96,2.05,2.01,1.91,1.95 144 | D1,18/12/2019,19:30,M'gladbach,Paderborn,2,0,H,0,0,D,17,12,6,2,6,14,8,4,2,3,0,0,1.33,6,7.5,1.3,6,9,1.33,5.5,8.3,1.3,6.07,9.24,1.3,5.8,9,1.3,6,8.5,1.34,6.35,10,1.3,5.89,8.74,1.28,3.75,1.29,3.74,1.3,3.95,1.28,3.63,-1.5,1.77,2.02,1.83,2.08,1.86,2.13,1.8,2.06,1.36,5.75,6.5,1.36,5.75,7.25,1.33,5.5,8.3,1.39,5.67,7.21,1.36,5.8,7,1.4,5.5,7,1.41,5.95,8.3,1.38,5.53,7.07,1.36,3.2,1.39,3.19,1.4,3.5,1.35,3.15,-1.5,2.07,1.86,2.04,1.88,2.09,1.96,2,1.86 145 | D1,18/12/2019,19:30,Wolfsburg,Schalke 04,1,1,D,0,0,D,29,8,11,2,13,11,12,5,1,1,0,0,2.3,3.4,3.1,2.35,3.3,3.1,2.35,3.35,3.05,2.42,3.43,3.08,2.4,3.3,3,2.38,3.4,3,2.48,3.45,3.2,2.38,3.33,3.04,2,1.8,2.06,1.85,2.06,1.89,1.99,1.82,-0.25,2.07,1.86,2.08,1.83,2.09,1.89,2.05,1.82,2,3.6,3.5,2.05,3.5,3.6,2.1,3.5,3.5,2.09,3.62,3.64,2.05,3.6,3.5,2.1,3.5,3.5,2.3,3.7,3.65,2.08,3.5,3.52,1.9,1.9,1.93,1.96,1.97,2.05,1.9,1.91,-0.25,1.75,2.05,1.81,2.12,1.95,2.17,1.8,2.07 146 | D1,20/12/2019,19:30,Hoffenheim,Dortmund,2,1,H,0,1,A,11,12,3,5,8,12,0,8,0,1,0,0,3.6,4,1.9,3.8,3.9,1.87,4,3.8,1.85,3.81,4.01,1.93,3.8,3.9,1.88,3.7,4,1.91,4.02,4.13,1.96,3.76,3.94,1.9,1.44,2.75,1.49,2.76,1.49,2.88,1.46,2.69,0.5,2.01,1.92,1.99,1.93,2.03,1.93,1.97,1.88,4.33,4.5,1.66,3.8,3.9,1.87,4.7,4,1.7,4.5,4.36,1.71,4.8,4.33,1.63,4.4,4.33,1.7,5.2,4.58,1.87,4.4,4.25,1.71,1.44,2.75,1.47,2.82,1.49,2.99,1.45,2.73,0.75,2.02,1.91,2.01,1.91,2.12,1.95,1.99,1.88 147 | D1,21/12/2019,14:30,Bayern Munich,Wolfsburg,2,0,H,0,0,D,18,10,8,3,7,7,12,6,2,2,0,0,1.14,8.5,17,1.14,8.5,17,1.2,7.4,12,1.17,7.86,17.81,1.17,7.5,17,1.17,8,17,1.2,8.81,20,1.16,7.96,16.49,1.3,3.5,1.33,3.49,1.34,3.6,1.31,3.39,-2.25,2.02,1.91,1.99,1.91,2.04,1.95,1.97,1.89,1.18,7.5,13,1.19,7.25,13.5,1.22,7,11,1.22,6.86,13.38,1.18,7.5,15,1.2,7.5,13,1.23,8,17,1.2,7.22,13.24,1.3,3.5,1.32,3.55,1.35,3.72,1.31,3.39,-2,1.93,2,1.91,2,1.95,2.05,1.88,1.97 148 | D1,21/12/2019,14:30,FC Koln,Werder Bremen,1,0,H,1,0,H,7,6,1,1,11,18,1,7,1,4,0,0,2.05,3.75,3.4,2.1,3.7,3.25,2,3.6,3.6,2.09,3.87,3.39,2.1,3.7,3.3,2.1,3.8,3.25,2.21,3.9,3.6,2.08,3.74,3.32,1.57,2.37,1.59,2.49,1.6,2.57,1.55,2.42,-0.25,1.85,2.08,1.83,2.09,1.87,2.1,1.82,2.04,1.9,3.8,3.8,1.91,3.9,3.7,2,3.6,3.6,1.93,3.95,3.84,1.91,3.8,3.8,1.93,3.9,3.7,2.03,4,3.95,1.92,3.87,3.73,1.57,2.37,1.6,2.46,1.6,2.51,1.57,2.41,-0.5,1.94,1.99,1.93,1.99,2,2.01,1.92,1.94 149 | D1,21/12/2019,14:30,Mainz,Leverkusen,0,1,A,0,0,D,17,14,2,4,8,8,6,6,0,2,0,1,3.8,4,1.83,4.1,4,1.8,3.65,3.9,1.9,3.97,4.04,1.88,3.9,3.9,1.85,3.8,4,1.87,4.1,4.23,1.91,3.86,3.99,1.86,1.44,2.75,1.51,2.72,1.51,2.79,1.47,2.65,0.5,2.04,1.89,2.04,1.88,2.04,1.9,2,1.86,3.6,4,1.9,3.4,3.9,2,3.5,3.7,2,3.65,4.04,1.96,3.6,3.9,1.95,3.5,4,1.95,3.66,4.2,2.05,3.49,3.95,1.96,1.4,3,1.44,2.94,1.5,3,1.42,2.84,0.5,1.97,1.96,1.96,1.96,1.99,2,1.91,1.94 150 | D1,21/12/2019,14:30,RB Leipzig,Augsburg,3,1,H,0,1,A,22,6,7,2,7,9,10,4,1,3,0,0,1.25,6.5,11,1.26,6.25,10,1.3,6,8.5,1.27,6.22,11.55,1.25,6,12,1.25,6.25,10.5,1.3,6.67,12.25,1.26,6.17,10.65,1.33,3.4,1.35,3.41,1.36,3.5,1.33,3.27,-1.75,1.93,2,1.94,1.98,1.95,2.03,1.9,1.96,1.25,6.5,10,1.26,6.25,10,1.3,6,8.5,1.24,6.75,12,1.24,6.5,11,1.25,6.5,11,1.3,7,12.25,1.25,6.51,10.47,1.3,3.5,1.32,3.61,1.36,3.68,1.31,3.38,-2,2.07,1.72,2.17,1.77,2.2,1.82,2.13,1.75 151 | D1,21/12/2019,14:30,Schalke 04,Freiburg,2,2,D,1,0,H,19,19,6,7,9,12,7,5,1,1,0,0,1.65,3.8,5.5,1.65,4.1,5,1.7,3.8,5,1.7,3.94,5.19,1.7,3.8,5,1.7,4,4.8,1.74,4.1,5.67,1.68,3.91,5.06,1.66,2.2,1.71,2.23,1.73,2.25,1.69,2.17,-0.75,1.9,2.03,1.9,2.02,1.92,2.05,1.87,1.99,1.85,3.8,4,1.83,3.6,4.4,1.85,3.5,4.4,1.93,3.61,4.24,1.85,3.75,4.2,1.91,3.7,4,1.95,3.9,4.5,1.87,3.65,4.16,1.8,2,1.79,2.11,1.82,2.23,1.75,2.08,-0.5,1.93,2,1.93,1.99,1.96,2.06,1.88,1.98 152 | D1,21/12/2019,17:30,Hertha,M'gladbach,0,0,D,0,0,D,8,11,0,5,11,11,1,7,2,2,0,0,3.1,3.7,2.2,3,3.7,2.25,2.9,3.5,2.35,3.21,3.65,2.23,3.2,3.5,2.2,3.1,3.6,2.25,3.24,3.73,2.35,3.1,3.6,2.22,1.61,2.3,1.68,2.3,1.68,2.41,1.62,2.28,0.25,1.97,1.96,1.97,1.95,1.98,1.98,1.92,1.93,2.8,3.6,2.37,2.85,3.5,2.4,3,3.5,2.3,2.93,3.59,2.41,2.88,3.5,2.4,2.88,3.5,2.45,3.1,3.7,2.53,2.87,3.51,2.4,1.72,2.1,1.79,2.11,1.79,2.25,1.7,2.15,0.25,1.72,2.07,1.83,2.1,1.83,2.19,1.77,2.1 153 | D1,22/12/2019,14:30,Fortuna Dusseldorf,Union Berlin,2,1,H,1,0,H,22,17,8,6,8,18,7,5,2,4,0,0,2.75,3.25,2.62,2.7,3.25,2.7,2.75,3.3,2.6,2.87,3.31,2.61,2.8,3.3,2.55,2.7,3.3,2.55,2.87,3.41,2.7,2.77,3.28,2.6,1.9,1.9,2.04,1.86,2.04,1.98,1.94,1.86,0,2.02,1.91,2.05,1.87,2.05,1.94,1.99,1.87,3,3.4,2.3,2.95,3.3,2.45,2.75,3.25,2.6,3.07,3.39,2.42,3,3.4,2.38,3,3.4,2.4,3.1,3.5,2.6,2.99,3.34,2.41,2,1.8,2.06,1.84,2.12,1.92,2,1.81,0.25,1.83,2.1,1.83,2.09,1.85,2.14,1.81,2.07 154 | D1,22/12/2019,17:00,Paderborn,Ein Frankfurt,2,1,H,2,0,H,19,20,5,5,11,11,3,8,3,2,0,0,3.4,4,2,3.75,4,1.87,3.05,3.7,2.2,3.56,3.93,2.02,3.5,3.8,2,3.25,4,1.95,3.75,4.05,2.2,3.47,3.88,1.99,1.44,2.75,1.48,2.79,1.48,2.9,1.43,2.77,0.5,1.91,2.02,1.9,2.02,1.95,2.05,1.88,1.97,3.1,4,2,3.2,4,2.05,3.4,3.8,2,3.2,3.97,2.13,3.25,3.9,2.05,3.13,4,2.1,3.54,4.16,2.2,3.16,3.92,2.09,1.5,2.62,1.51,2.7,1.51,2.9,1.47,2.66,0.25,2.03,1.9,2.03,1.88,2.12,1.93,2,1.86 155 | -------------------------------------------------------------------------------- /data/produkt_klima_tag_20180307_20190907_00403_Dahlem.txt: -------------------------------------------------------------------------------- 1 | STATIONS_ID;MESS_DATUM;QN_3; FX; FM;QN_4; RSK;RSKF; SDK;SHK_TAG; NM; VPM; PM; TMK; UPM; TXK; TNK; TGK;eor 2 | 403;20180307;-999;-999;-999; 3; 2.2; 8; 0.000; 1; 8.0; 6.6; 984.29; 1.2; 98.79; 1.9; 0.3; -0.5;eor 3 | 403;20180308;-999;-999;-999; 3; 5.7; 8; 3.267; 0; 6.6; 6.8; 991.08; 4.3; 83.25; 9.6; 0.9; -0.7;eor 4 | 403;20180309;-999;-999;-999; 3; 0.0; 6; 2.983; 0; 5.1; 6.4; 995.77; 4.3; 78.71; 8.7; -1.0; -3.5;eor 5 | 403;20180310;-999;-999;-999; 3; 2.0; 6; 0.083; 0; 6.6; 8.3; 995.28; 4.5; 96.04; 9.2; -1.2; -3.2;eor 6 | 403;20180311;-999;-999;-999; 3; 0.0; 0; 8.967; 0; 4.3; 9.5; 989.85; 9.7; 81.30; 16.5; 3.3; -1.1;eor 7 | 403;20180312;-999;-999;-999; 3; 7.6; 6; 0.000; 0; 7.6; 10.2; 982.31; 8.0; 94.96; 9.8; 5.1; 0.9;eor 8 | 403;20180313;-999;-999;-999; 3; 1.9; 6; 0.783; 0; 7.0; 9.5; 989.08; 8.8; 84.54; 11.5; 4.0; 3.5;eor 9 | 403;20180314;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.6; 7.0; 1000.86; 3.9; 87.00; 5.2; 2.5; 1.6;eor 10 | 403;20180315;-999;-999;-999; 3; 0.0; 0; 0.000; 0; 7.6; 6.2; 999.69; 3.0; 82.38; 4.9; 1.7; 0.9;eor 11 | 403;20180316;-999;-999;-999; 3; 0.4; 8; 0.000; 0; 8.0; 4.5; 998.96; -0.2; 73.63; 1.7; -2.7; -3.0;eor 12 | 403;20180317;-999;-999;-999; 3; 0.0; 0; 8.417; 0; 6.4; 2.6; 1004.68; -3.1; 52.71; -0.5; -5.3; -5.5;eor 13 | 403;20180318;-999;-999;-999; 3; 0.0; 0; 11.400; 0; 2.7; 2.1; 1007.59; -2.4; 41.88; 1.7; -6.0; -7.6;eor 14 | 403;20180319;-999;-999;-999; 3; 0.0; 0; 11.617; 0; 0.9; 2.4; 1005.48; -1.5; 45.88; 4.3; -6.0; -9.5;eor 15 | 403;20180320;-999;-999;-999; 3; 1.1; 7; 0.550; 0; 4.4; 4.2; 1005.90; -1.8; 77.50; 2.5; -6.5; -8.6;eor 16 | 403;20180321;-999;-999;-999; 3; 0.0; 7; 9.733; 0; 4.2; 4.2; 1015.00; 0.9; 65.57; 6.3; -6.0; -7.7;eor 17 | 403;20180322;-999;-999;-999; 3; 3.9; 8; 0.000; 0; 8.0; 6.6; 1002.53; 2.2; 90.92; 4.1; 0.4; -0.7;eor 18 | 403;20180323;-999;-999;-999; 3; 0.1; 6; 0.000; 0; 8.0; 6.8; 997.59; 2.8; 91.33; 4.0; 1.6; 0.9;eor 19 | 403;20180324;-999;-999;-999; 3; 0.0; 0; 3.433; 0; 5.2; 5.5; 996.47; 2.9; 74.17; 7.2; -0.8; -3.5;eor 20 | 403;20180325;-999;-999;-999; 3; 0.0; 0; 10.783; 0; 5.4; 5.4; 998.22; 4.8; 66.63; 11.3; -2.6; -4.1;eor 21 | 403;20180326;-999;-999;-999; 3; 0.0; 6; 1.383; 0; 7.1; 6.6; 1002.94; 5.4; 73.42; 7.8; 2.4; 0.9;eor 22 | 403;20180327;-999;-999;-999; 3; 0.0; 8; 5.167; 0; 6.0; 5.4; 1004.84; 3.8; 68.54; 8.5; -0.7; -3.2;eor 23 | 403;20180328;-999;-999;-999; 3; 7.7; 8; 0.000; 0; 7.9; 6.2; 996.01; 1.3; 92.54; 2.1; 0.4; -0.3;eor 24 | 403;20180329;-999;-999;-999; 3; 0.4; 8; 0.500; 0; 6.9; 6.8; 992.69; 4.8; 80.25; 7.8; 1.0; -2.1;eor 25 | 403;20180330;-999;-999;-999; 3; 0.0; 0; 9.917; 0; 5.5; 6.0; 997.95; 5.1; 71.13; 11.7; -1.0; -3.4;eor 26 | 403;20180331;-999;-999;-999; 3; 2.5; 8; 0.000; 0; 7.5; 6.8; 989.73; 3.1; 88.13; 5.4; 1.1; -0.8;eor 27 | 403;20180401;-999;-999;-999; 3; 1.7; 8; 0.000; 0; 7.8; 6.4; 992.75; 1.3; 95.46; 2.1; 0.6; -0.7;eor 28 | 403;20180402;-999;-999;-999; 3; 1.6; 6; 8.600; 0; 4.7; 5.5; 999.80; 4.7; 66.33; 9.5; -0.7; -2.2;eor 29 | 403;20180403;-999;-999;-999; 3; 0.2; 6; 5.617; 0; 7.0; 9.3; 994.32; 11.9; 67.96; 18.4; 4.8; 3.8;eor 30 | 403;20180404;-999;-999;-999; 3; 2.1; 6; 10.383; 0; 6.0; 9.9; 993.60; 14.4; 63.42; 21.2; 8.0; 3.6;eor 31 | 403;20180405;-999;-999;-999; 3; 0.2; 6; 4.600; 0; 5.3; 8.8; 998.30; 10.0; 71.83; 15.2; 3.5; 1.3;eor 32 | 403;20180406;-999;-999;-999; 3; 0.0; 0; 12.367; 0; 1.0; 5.6; 1013.68; 6.6; 60.83; 12.9; 1.4; -1.4;eor 33 | 403;20180407;-999;-999;-999; 3; 0.0; 0; 12.850; 0; 3.1; 6.6; 1008.28; 12.1; 48.63; 21.1; 2.5; -1.8;eor 34 | 403;20180408;-999;-999;-999; 3; 0.0; 0; 12.017; 0; 0.7; 9.4; 1001.75; 14.0; 60.46; 20.6; 7.9; 3.5;eor 35 | 403;20180409;-999;-999;-999; 3; 0.0; 0; 10.767; 0; 1.9; 9.6; 997.39; 14.4; 62.04; 22.3; 5.3; 1.6;eor 36 | 403;20180410;-999;-999;-999; 3; 0.1; 6; 11.183; 0; 2.0; 11.2; 996.39; 17.4; 57.67; 24.7; 11.3; 6.5;eor 37 | 403;20180411;-999;-999;-999; 3; 0.0; 6; 10.633; 0; 2.3; 12.3; 1000.15; 14.9; 72.96; 19.6; 11.4; 8.5;eor 38 | 403;20180412;-999;-999;-999; 3; 0.0; 6; 8.900; 0; 4.7; 12.4; 996.61; 16.7; 67.83; 24.3; 10.1; 7.0;eor 39 | 403;20180413;-999;-999;-999; 3; 23.8; 6; 1.750; 0; 6.8; 14.6; 997.27; 15.6; 83.00; 20.9; 10.9; 9.7;eor 40 | 403;20180414;-999;-999;-999; 3; 4.3; 6; 3.850; 0; 6.5; 12.3; 1006.65; 12.6; 85.17; 17.3; 9.6; 6.2;eor 41 | 403;20180415;-999;-999;-999; 3; 0.0; 6; 10.117; 0; 5.9; 11.1; 1004.27; 15.2; 68.46; 22.1; 8.7; 5.3;eor 42 | 403;20180416;-999;-999;-999; 3; 3.0; 6; 0.217; 0; 7.4; 12.5; 1004.02; 12.1; 88.87; 15.8; 9.5; 8.0;eor 43 | 403;20180417;-999;-999;-999; 3; 0.0; 0; 11.383; 0; 2.0; 10.2; 1015.84; 13.0; 71.58; 18.9; 7.9; 4.6;eor 44 | 403;20180418;-999;-999;-999; 3; 0.0; 0; 12.517; 0; 1.5; 10.8; 1021.74; 15.5; 66.46; 23.7; 6.5; 3.5;eor 45 | 403;20180419;-999;-999;-999; 3; 0.0; 0; 12.333; 0; 2.0; 12.6; 1021.13; 17.2; 67.75; 24.4; 8.8; 5.3;eor 46 | 403;20180420;-999;-999;-999; 3; 0.0; 0; 13.183; 0; 2.1; 12.8; 1013.73; 19.0; 63.83; 27.1; 10.3; 6.3;eor 47 | 403;20180421;-999;-999;-999; 3; 0.0; 0; 12.800; 0; 2.4; 10.8; 1009.76; 16.5; 59.17; 21.6; 9.5; 4.7;eor 48 | 403;20180422;-999;-999;-999; 3; 0.0; 6; 12.267; 0; 4.0; 10.8; 1005.87; 16.2; 60.92; 23.7; 6.6; 2.8;eor 49 | 403;20180423;-999;-999;-999; 3; 0.1; 6; 7.533; 0; 5.0; 13.1; 1002.15; 16.6; 69.46; 21.3; 11.0; 6.7;eor 50 | 403;20180424;-999;-999;-999; 3; 0.6; 6; 2.617; 0; 6.5; 10.5; 1004.39; 12.5; 73.54; 16.4; 7.7; 4.2;eor 51 | 403;20180425;-999;-999;-999; 3; 0.9; 6; 5.533; 0; 5.4; 10.7; 998.44; 12.4; 75.58; 18.4; 7.4; 3.2;eor 52 | 403;20180426;-999;-999;-999; 3; 2.4; 6; 4.550; 0; 4.8; 9.3; 1003.64; 8.9; 82.21; 13.8; 5.8; 2.0;eor 53 | 403;20180427;-999;-999;-999; 3; 0.0; 0; 9.367; 0; 5.3; 8.0; 1005.00; 10.6; 66.50; 16.4; 3.1; 0.0;eor 54 | 403;20180428;-999;-999;-999; 3; 0.0; 6; 11.100; 0; 4.6; 9.1; 1001.10; 14.9; 58.17; 22.5; 5.0; 1.5;eor 55 | 403;20180429;-999;-999;-999; 3; 0.0; 6; 11.267; 0; 3.2; 11.9; 1000.01; 17.6; 61.79; 24.6; 10.1; 6.1;eor 56 | 403;20180430;-999;-999;-999; 3; 0.0; 6; 10.283; 0; 2.5; 12.2; 992.22; 16.4; 65.92; 23.6; 8.5; 3.8;eor 57 | 403;20180501;-999;-999;-999; 3; 0.0; 0; 10.883; 0; 3.4; 8.1; 1000.30; 12.0; 59.08; 16.0; 4.4; 0.3;eor 58 | 403;20180502;-999;-999;-999; 3; 0.0; 6; 4.267; 0; 6.0; 8.3; 1005.18; 10.5; 67.67; 14.9; 2.6; -0.8;eor 59 | 403;20180503;-999;-999;-999; 3; 0.0; 0; 9.383; 0; 4.3; 9.4; 1005.50; 13.7; 60.42; 18.9; 7.1; 2.0;eor 60 | 403;20180504;-999;-999;-999; 3; 0.0; 0; 14.033; 0; 1.1; 7.2; 1014.05; 11.9; 54.75; 18.3; 4.2; 0.1;eor 61 | 403;20180505;-999;-999;-999; 3; 0.0; 0; 14.433; 0; 1.8; 8.3; 1017.63; 13.1; 57.54; 19.5; 4.9; -0.3;eor 62 | 403;20180506;-999;-999;-999; 3; 0.0; 0; 14.533; 0; 0.5; 10.6; 1016.93; 15.0; 63.63; 21.8; 7.9; 2.6;eor 63 | 403;20180507;-999;-999;-999; 3; 0.0; 0; 14.633; 0; 0.3; 11.2; 1012.96; 16.8; 62.38; 24.3; 7.7; 2.6;eor 64 | 403;20180508;-999;-999;-999; 3; 0.0; 0; 14.550; 0; 0.1; 11.6; 1006.17; 18.5; 57.29; 25.6; 10.4; 5.2;eor 65 | 403;20180509;-999;-999;-999; 3; 0.2; 6; 12.700; 0; 2.2; 14.1; 1000.61; 19.9; 61.96; 27.0; 12.7; 7.5;eor 66 | 403;20180510;-999;-999;-999; 3; 5.8; 6; 7.167; 0; 6.2; 16.6; 999.70; 19.9; 74.21; 27.2; 14.4; 11.8;eor 67 | 403;20180511;-999;-999;-999; 3; 0.0; 0; 0.350; 0; 6.4; 13.7; 1009.52; 13.5; 88.46; 15.8; 9.8; 6.3;eor 68 | 403;20180512;-999;-999;-999; 3; 0.0; 0; 8.800; 0; 3.3; 13.8; 1008.13; 16.7; 74.75; 22.9; 9.0; 5.3;eor 69 | 403;20180513;-999;-999;-999; 3; 0.0; 0; 14.533; 0; 0.7; 12.2; 1003.65; 20.2; 55.79; 26.5; 14.0; 9.5;eor 70 | 403;20180514;-999;-999;-999; 3; 0.0; 0; 14.733; 0; 1.0; 10.2; 1004.84; 19.0; 47.17; 24.2; 11.8; 6.7;eor 71 | 403;20180515;-999;-999;-999; 3; 7.2; 6; 6.200; 0; 4.6; 12.0; 1004.81; 15.1; 72.00; 22.9; 10.1; 6.3;eor 72 | 403;20180516;-999;-999;-999; 3; 0.0; 0; 8.250; 0; 6.5; 13.1; 1002.60; 16.6; 72.46; 22.0; 11.2; 8.0;eor 73 | 403;20180517;-999;-999;-999; 3; 0.0; 0; 12.933; 0; 6.0; 12.5; 1003.90; 15.9; 70.25; 21.1; 10.7; 7.6;eor 74 | 403;20180518;-999;-999;-999; 3; 0.0; 6; 0.333; 0; 6.1; 11.4; 1009.55; 11.9; 82.17; 14.0; 8.8; 6.9;eor 75 | 403;20180519;-999;-999;-999; 3; 0.0; 0; 12.533; 0; 5.3; 9.8; 1012.47; 16.1; 57.00; 22.2; 11.4; 6.6;eor 76 | 403;20180520;-999;-999;-999; 3; 0.0; 0; 15.450; 0; 0.7; 7.9; 1015.24; 15.9; 45.04; 22.4; 8.3; 3.6;eor 77 | 403;20180521;-999;-999;-999; 3; 0.0; 0; 14.583; 0; 1.4; 9.7; 1011.23; 17.2; 49.96; 23.9; 9.2; 3.2;eor 78 | 403;20180522;-999;-999;-999; 3; 0.0; 0; 14.467; 0; 1.8; 10.4; 1006.42; 18.4; 50.71; 25.3; 10.5; 4.6;eor 79 | 403;20180523;-999;-999;-999; 3; 0.0; 0; 14.033; 0; 4.8; 10.9; 1011.45; 19.4; 51.13; 25.5; 11.5; 5.6;eor 80 | 403;20180524;-999;-999;-999; 3; 0.0; 0; 14.817; 0; 4.5; 11.8; 1013.14; 20.0; 51.29; 26.0; 14.2; 9.7;eor 81 | 403;20180525;-999;-999;-999; 3; 0.0; 0; 13.667; 0; 2.1; 11.1; 1011.57; 20.6; 47.29; 27.8; 14.5; 9.0;eor 82 | 403;20180526;-999;-999;-999; 3; 0.0; 0; 13.250; 0; 2.8; 13.1; 1012.45; 20.0; 58.21; 27.4; 12.8; 7.4;eor 83 | 403;20180527;-999;-999;-999; 3; 0.0; 6; 9.467; 0; 3.6; 15.3; 1011.37; 20.4; 66.29; 27.8; 14.6; 9.5;eor 84 | 403;20180528;-999;-999;-999; 3; 0.0; 0; 13.817; 0; 4.4; 16.6; 1010.22; 24.3; 58.29; 32.1; 15.6; 10.6;eor 85 | 403;20180529;-999;-999;-999; 3; 0.0; 0; 15.317; 0; 0.8; 12.7; 1006.57; 25.3; 41.83; 32.2; 18.3; 12.1;eor 86 | 403;20180530;-999;-999;-999; 3; 0.0; 6; 10.967; 0; 3.3; 15.7; 1005.38; 23.8; 54.67; 32.4; 17.2; 12.3;eor 87 | 403;20180531;-999;-999;-999; 3; 0.0; 0; 11.783; 0; 3.2; 16.8; 1005.57; 24.3; 58.13; 31.5; 16.2; 11.7;eor 88 | 403;20180601;-999;-999;-999; 3; 1.9; 6; 11.350; 0; 5.0; 19.1; 1004.90; 23.7; 67.79; 31.1; 18.6; 14.2;eor 89 | 403;20180602;-999;-999;-999; 3; 0.0; 6; 4.300; 0; 6.8; 19.5; 1005.81; 21.2; 78.58; 26.0; 18.0; 15.0;eor 90 | 403;20180603;-999;-999;-999; 3; 0.0; 6; 4.267; 0; 5.6; 18.3; 1007.42; 19.6; 81.08; 23.7; 16.8; 12.6;eor 91 | 403;20180604;-999;-999;-999; 3; 0.0; 0; 12.933; 0; 2.0; 16.6; 1002.78; 20.8; 69.75; 26.1; 14.6; 10.4;eor 92 | 403;20180605;-999;-999;-999; 3; 0.0; 0; 4.083; 0; 4.8; 14.0; 1003.55; 18.1; 68.42; 23.6; 13.5; 7.6;eor 93 | 403;20180606;-999;-999;-999; 3; 0.0; 0; 16.017; 0; 1.6; 8.9; 1008.23; 18.2; 43.58; 24.6; 12.2; 7.8;eor 94 | 403;20180607;-999;-999;-999; 3; 0.0; 0; 15.900; 0; 1.3; 10.0; 1007.60; 20.3; 41.83; 28.8; 12.1; 7.1;eor 95 | 403;20180608;-999;-999;-999; 3; 0.0; 0; 15.433; 0; 3.1; 12.4; 1004.25; 23.3; 45.58; 31.5; 12.9; 8.1;eor 96 | 403;20180609;-999;-999;-999; 3; 0.0; 0; 13.600; 0; 3.7; 16.0; 1002.74; 24.7; 53.42; 31.9; 17.2;-999;eor 97 | 403;20180610;-999;-999;-999; 3; 0.7; 6; 7.050; 0; 5.1; 20.0; 1000.35; 22.1; 78.00; 30.5; 17.1; 12.7;eor 98 | 403;20180611;-999;-999;-999; 3; 0.0; 0; 8.550; 0; 4.6; 14.8; 1001.12; 19.5; 67.42; 24.6; 15.8; 10.8;eor 99 | 403;20180612;-999;-999;-999; 3; 0.0; 0; 9.867; 0; 5.2; 11.7; 1000.61; 16.6; 62.50; 21.2; 13.5; 11.5;eor 100 | 403;20180613;-999;-999;-999; 3; 0.0; 6; 0.817; 0; 7.7; 12.2; 1002.61; 15.2; 70.88; 17.4; 14.0; 13.7;eor 101 | 403;20180614;-999;-999;-999; 3; 0.0; 0; 12.467; 0; 5.1; 11.1; 1005.54; 17.0; 58.88; 23.2; 11.6; 6.7;eor 102 | 403;20180615;-999;-999;-999; 3; 0.0; 0; 1.083; 0; 6.9; 15.0; 1007.11; 18.5; 70.67; 23.2; 13.5; 11.9;eor 103 | 403;20180616;-999;-999;-999; 3; 0.0; 0; 4.783; 0; 6.7; 15.5; 1006.33; 21.3; 63.00; 27.4; 15.6; 13.2;eor 104 | 403;20180617;-999;-999;-999; 3; 0.0; 0; 12.883; 0; 3.2; 14.4; 1005.70; 20.6; 60.13; 26.3; 14.6; 9.0;eor 105 | 403;20180618;-999;-999;-999; 3; 0.0; 6; 5.083; 0; 5.5; 13.8; 1009.85; 18.9; 64.50; 24.0; 12.3; 7.5;eor 106 | 403;20180619;-999;-999;-999; 3; 0.0; 6; 5.783; 0; 5.4; 16.3; 1011.46; 20.7; 67.50; 25.7; 16.1; 11.8;eor 107 | 403;20180620;-999;-999;-999; 3; 0.0; 0; 5.950; 0; 4.6; 17.0; 1010.68; 21.4; 68.88; 28.1; 14.7; 10.7;eor 108 | 403;20180621;-999;-999;-999; 3; 2.2; 6; 8.317; 0; 4.3; 13.7; 1003.30; 16.9; 70.96; 27.1; 10.8; 9.2;eor 109 | 403;20180622;-999;-999;-999; 3; 5.0; 8; 3.450; 0; 5.5; 10.8; 1007.52; 13.6; 70.17; 18.5; 9.9; 8.6;eor 110 | 403;20180623;-999;-999;-999; 3; 3.9; 6; 1.833; 0; 7.2; 12.7; 1009.45; 13.4; 83.21; 18.3; 11.1; 10.2;eor 111 | 403;20180624;-999;-999;-999; 3; 1.6; 6; 0.000; 0; 7.9; 14.4; 1009.01; 12.8; 97.25; 14.9; 11.5; 11.3;eor 112 | 403;20180625;-999;-999;-999; 3; 0.0; 0; 2.450; 0; 5.9; 13.9; 1010.81; 15.5; 80.96; 21.4; 11.6; 9.7;eor 113 | 403;20180626;-999;-999;-999; 3; 0.0; 6; 5.750; 0; 5.0; 13.8; 1013.25; 16.8; 74.54; 23.6; 11.4; 7.6;eor 114 | 403;20180627;-999;-999;-999; 3; 0.0; 0; 10.667; 0; 3.5; 13.2; 1015.01; 19.2; 62.04; 25.8; 13.0; 10.0;eor 115 | 403;20180628;-999;-999;-999; 3; 0.0; 0; 10.500; 0; 4.8; 14.8; 1011.42; 21.8; 58.38; 27.4; 15.0; 12.4;eor 116 | 403;20180629;-999;-999;-999; 3; 0.0; 0; 14.967; 0; 3.0; 14.1; 1006.60; 21.7; 55.92; 29.8; 14.6; 10.9;eor 117 | 403;20180630;-999;-999;-999; 3; 0.0; 0; 12.533; 0; 2.3; 10.4; 1010.28; 17.1; 53.96; 22.6; 11.5; 7.4;eor 118 | 403;20180701;-999;-999;-999; 3; 0.0; 0; 13.033; 0; 2.3; 10.1; 1011.34; 16.6; 54.54; 22.6; 10.2; 4.7;eor 119 | 403;20180702;-999;-999;-999; 3; 0.0; 0; 12.800; 0; 2.2; 10.4; 1008.61; 17.0; 56.75; 23.6; 8.6; 3.6;eor 120 | 403;20180703;-999;-999;-999; 3; 0.0; 0; 15.633; 0; 1.0; 11.2; 1006.41; 19.9; 51.79; 27.3; 9.7; 6.5;eor 121 | 403;20180704;-999;-999;-999; 3; 0.0; 0; 16.017; 0; 0.8; 11.0; 1004.10; 22.8; 44.00; 30.5; 12.9; 9.6;eor 122 | 403;20180705;-999;-999;-999; 3; 0.0; 0; 14.183; 0; 2.5; 14.2; 1001.32; 23.9; 49.96; 31.0; 15.3; 12.8;eor 123 | 403;20180706;-999;-999;-999; 3; 0.0; 0; 3.117; 0; 5.5; 13.8; 1006.28; 18.6; 65.04; 23.1; 14.7; 12.9;eor 124 | 403;20180707;-999;-999;-999; 3; 0.0; 0; 15.617; 0; 2.1; 11.9; 1009.54; 18.6; 58.29; 25.5; 11.5; 9.5;eor 125 | 403;20180708;-999;-999;-999; 3; 0.0; 0; 7.133; 0; 5.0; 15.5; 1010.26; 19.9; 67.38; 26.6; 14.1; 13.0;eor 126 | 403;20180709;-999;-999;-999; 3; 0.0; 0; 8.583; 0; 5.6; 14.1; 1008.59; 19.3; 63.33; 23.1; 15.2; 14.1;eor 127 | 403;20180710;-999;-999;-999; 3; 0.7; 6; 3.083; 0; 6.9; 13.1; 1006.28; 16.6; 69.25; 20.1; 13.9; 12.5;eor 128 | 403;20180711;-999;-999;-999; 3; 38.5; 6; 7.367; 0; 6.3; 14.5; 1004.53; 17.7; 74.21; 23.9; 13.8; 12.9;eor 129 | 403;20180712;-999;-999;-999; 3; 14.8; 6; 0.000; 0; 7.7; 16.8; 1003.55; 17.0; 87.29; 20.2; 14.3; 14.2;eor 130 | 403;20180713;-999;-999;-999; 3; 0.2; 6; 6.533; 0; 4.2; 16.2; 1007.35; 19.5; 73.88; 26.6; 14.4; 12.7;eor 131 | 403;20180714;-999;-999;-999; 3; 0.0; 0; 14.333; 0; 1.5; 14.8; 1009.06; 18.5; 70.92; 23.0; 14.4; 11.7;eor 132 | 403;20180715;-999;-999;-999; 3; 0.0; 0; 14.000; 0; 1.4; 13.4; 1007.68; 18.6; 65.08; 24.4; 11.7; 10.4;eor 133 | 403;20180716;-999;-999;-999; 3; 0.0; 0; 13.533; 0; 2.1; 15.4; 1004.40; 21.0; 65.29; 27.8; 13.8; 12.0;eor 134 | 403;20180717;-999;-999;-999; 3; 0.0; 6; 9.850; 0; 6.3; 16.3; 1002.24; 22.6; 62.33; 29.0; 16.1; 14.4;eor 135 | 403;20180718;-999;-999;-999; 3; 0.0; 0; 12.067; 0; 6.5; 16.5; 1004.60; 22.1; 62.96; 26.1; 18.4; 17.0;eor 136 | 403;20180719;-999;-999;-999; 3; 0.0; 6; 8.717; 0; 3.6; 16.1; 1006.79; 20.4; 67.96; 25.8; 14.5; 12.2;eor 137 | 403;20180720;-999;-999;-999; 3; 0.0; 0; 12.700; 0; 2.3; 13.2; 1005.20; 20.3; 58.71; 26.7; 12.3; 10.3;eor 138 | 403;20180721;-999;-999;-999; 3; 0.0; 0; 12.117; 0; 5.5; 13.9; 1003.03; 21.2; 57.17; 27.3; 13.3; 11.4;eor 139 | 403;20180722;-999;-999;-999; 3; 0.0; 0; 5.267; 0; 6.2; 16.3; 1003.63; 22.3; 61.79; 26.9; 16.0; 14.5;eor 140 | 403;20180723;-999;-999;-999; 3; 0.0; 0; 14.467; 0; 1.0; 16.8; 1006.20; 21.7; 66.88; 26.4; 16.9; 14.8;eor 141 | 403;20180724;-999;-999;-999; 3; 0.0; 0; 13.517; 0; 1.6; 18.2; 1006.13; 23.1; 66.33; 29.5; 15.3; 13.3;eor 142 | 403;20180725;-999;-999;-999; 3; 0.0; 0; 11.867; 0; 1.6; 19.0; 1005.88; 25.4; 61.21; 31.3; 18.0; 15.7;eor 143 | 403;20180726;-999;-999;-999; 3; 0.0; 0; 15.183; 0; 1.1; 18.4; 1007.26; 25.4; 59.50; 31.4; 16.9; 13.3;eor 144 | 403;20180727;-999;-999;-999; 3; 0.0; 6; 11.500; 0; 2.3; 20.9; 1005.46; 25.3; 65.96; 31.5; 19.4; 16.3;eor 145 | 403;20180728;-999;-999;-999; 3; 16.3; 6; 12.083; 0; 3.8; 21.9; 1000.58; 24.6; 74.33; 32.6; 19.3; 16.3;eor 146 | 403;20180729;-999;-999;-999; 3; 0.0; 0; 12.883; 0; 4.4; 18.4; 1006.09; 22.3; 71.29; 28.5; 17.1; 16.4;eor 147 | 403;20180730;-999;-999;-999; 3; 0.0; 0; 11.717; 0; 3.0; 18.3; 1007.18; 25.9; 56.63; 32.2; 20.2; 18.0;eor 148 | 403;20180731;-999;-999;-999; 3; 0.0; 0; 14.050; 0; 1.4; 18.4; 1006.89; 27.3; 52.92; 34.8; 19.1; 16.3;eor 149 | 403;20180801;-999;-999;-999; 3; 0.0; 6; 8.617; 0; 5.1; 21.7; 1009.37; 26.5; 62.71; 30.0; 22.5; 19.7;eor 150 | 403;20180802;-999;-999;-999; 3; 0.0; 0; 7.917; 0; 4.9; 19.9; 1012.47; 25.7; 60.63; 30.8; 21.4; 19.3;eor 151 | 403;20180803;-999;-999;-999; 3; 0.0; 0; 12.783; 0; 1.8; 17.3; 1011.86; 25.9; 52.21; 32.5; 20.6; 17.2;eor 152 | 403;20180804;-999;-999;-999; 3; 0.0; 0; 11.967; 0; 2.9; 19.1; 1007.51; 26.1; 58.00; 32.9; 17.8; 15.3;eor 153 | 403;20180805;-999;-999;-999; 3; 0.0; 0; 10.417; 0; 3.3; 16.9; 1009.84; 21.4; 66.54; 24.5; 15.4; 12.3;eor 154 | 403;20180806;-999;-999;-999; 3; 0.0; 0; 14.550; 0; 0.7; 15.2; 1008.85; 20.9; 65.17; 29.1; 12.8; 10.5;eor 155 | 403;20180807;-999;-999;-999; 3; 0.0; 0; 13.617; 0; 2.0; 16.1; 1003.21; 25.2; 54.38; 35.1; 14.7; 10.9;eor 156 | 403;20180808;-999;-999;-999; 3; 0.0; 6; 10.500; 0; 4.2; 19.2; 1001.18; 27.4; 53.63; 37.0; 19.9; 16.5;eor 157 | 403;20180809;-999;-999;-999; 3; 0.8; 6; 11.833; 0; 2.4; 20.2; 1003.72; 26.8; 60.75; 34.3; 20.8; 19.1;eor 158 | 403;20180810;-999;-999;-999; 3; 0.0; 0; 7.383; 0; 4.0; 14.2; 1009.95; 19.7; 62.33; 23.5; 13.9; 11.0;eor 159 | 403;20180811;-999;-999;-999; 3; 0.0; 6; 7.150; 0; 3.9; 11.2; 1010.30; 18.5; 53.88; 22.7; 14.5; 10.7;eor 160 | 403;20180812;-999;-999;-999; 3; 0.0; 0; 13.050; 0; 5.1; 11.3; 1007.13; 19.1; 54.79; 26.7; 11.6; 8.0;eor 161 | 403;20180813;-999;-999;-999; 3; 0.0; 6; 8.500; 0; 4.8; 14.0; 998.69; 21.5; 58.88; 31.4; 11.8; 9.0;eor 162 | 403;20180814;-999;-999;-999; 3; 0.4; 6; 6.683; 0; 5.3; 17.8; 1001.07; 20.0; 77.17; 24.7; 16.9; 14.3;eor 163 | 403;20180815;-999;-999;-999; 3; 0.0; 0; 6.583; 0; 5.0; 16.3; 1008.29; 19.7; 72.42; 25.2; 14.6; 12.1;eor 164 | 403;20180816;-999;-999;-999; 3; 0.0; 0; 13.567; 0; 1.1; 15.3; 1007.70; 21.4; 64.54; 29.5; 13.3; 10.8;eor 165 | 403;20180817;-999;-999;-999; 3; 0.0; 6; 12.500; 0; 4.2; 16.1; 1005.40; 23.6; 58.00; 32.4; 15.2; 11.9;eor 166 | 403;20180818;-999;-999;-999; 3; 0.0; 6; 9.067; 0; 3.9; 16.1; 1011.12; 20.7; 67.63; 26.1; 15.2; 12.2;eor 167 | 403;20180819;-999;-999;-999; 3; 0.0; 0; 12.767; 0; 2.7; 14.8; 1009.52; 21.5; 62.00; 29.7; 13.3; 10.6;eor 168 | 403;20180820;-999;-999;-999; 3; 0.0; 6; 2.150; 0; 5.3; 17.6; 1007.41; 20.5; 72.96; 23.6; 16.0; 12.5;eor 169 | 403;20180821;-999;-999;-999; 3; 0.0; 0; 12.333; 0; 3.0; 14.1; 1011.54; 18.7; 66.63; 23.2; 12.4; 9.0;eor 170 | 403;20180822;-999;-999;-999; 3; 0.0; 0; 13.433; 0; 1.0; 14.1; 1009.27; 19.6; 65.25; 28.3; 10.9; 7.7;eor 171 | 403;20180823;-999;-999;-999; 3; 0.1; 6; 10.083; 0; 2.8; 15.5; 1001.72; 24.2; 57.25; 33.9; 13.9; 11.7;eor 172 | 403;20180824;-999;-999;-999; 3; 0.0; 6; 3.767; 0; 6.4; 14.9; 999.28; 19.6; 65.58; 23.0; 15.8; 13.7;eor 173 | 403;20180825;-999;-999;-999; 3; 0.2; 6; 5.183; 0; 4.3; 11.9; 1000.23; 15.9; 67.13; 21.7; 11.2; 8.0;eor 174 | 403;20180826;-999;-999;-999; 3; 0.0; 0; 10.933; 0; 2.5; 10.3; 1005.52; 14.4; 65.42; 21.1; 10.0; 7.2;eor 175 | 403;20180827;-999;-999;-999; 3; 0.0; 6; 2.417; 0; 6.3; 11.9; 1003.47; 17.1; 61.17; 21.7; 10.2; 7.2;eor 176 | 403;20180828;-999;-999;-999; 3; 0.0; 0; 6.000; 0; 3.8; 14.0; 1009.58; 17.3; 72.21; 22.2; 11.2; 8.2;eor 177 | 403;20180829;-999;-999;-999; 3; 0.0; 6; 11.967; 0; 2.3; 12.6; 1006.27; 19.3; 61.38; 27.8; 10.1; 6.7;eor 178 | 403;20180830;-999;-999;-999; 3; 3.3; 6; 0.000; 0; 7.1; 16.1; 1004.41; 16.8; 84.04; 19.3; 14.4; 11.8;eor 179 | 403;20180831;-999;-999;-999; 3; 0.0; 0; 6.817; 0; 5.3; 12.3; 1010.68; 15.0; 73.58; 20.4; 11.2; 9.2;eor 180 | 403;20180901;-999;-999;-999; 3; 0.0; 0; 8.183; 0; 5.3; 12.7; 1014.95; 16.3; 71.00; 22.4; 9.5; 6.3;eor 181 | 403;20180902;-999;-999;-999; 3; 0.6; 6; 0.050; 0; 5.9; 16.1; 1014.63; 18.4; 77.38; 22.7; 14.5; 12.3;eor 182 | 403;20180903;-999;-999;-999; 3; 0.0; 0; 10.850; 0; 3.8; 17.1; 1008.66; 22.6; 64.04; 28.7; 18.0; 14.6;eor 183 | 403;20180904;-999;-999;-999; 3; 0.0; 0; 10.917; 0; 3.1; 16.0; 1006.98; 20.1; 70.13; 26.2; 15.4; 12.0;eor 184 | 403;20180905;-999;-999;-999; 3; 0.0; 0; 5.983; 0; 3.6; 15.7; 1008.50; 19.3; 72.33; 25.4; 14.4; 10.4;eor 185 | 403;20180906;-999;-999;-999; 3; 0.5; 6; 10.150; 0; 3.3; 15.1; 1004.12; 19.7; 67.67; 26.1; 15.2; 12.0;eor 186 | 403;20180907;-999;-999;-999; 3; 0.2; 6; 2.817; 0; 6.1; 15.5; 1002.48; 18.1; 75.33; 23.2; 14.1; 11.7;eor 187 | 403;20180908;-999;-999;-999; 3; 0.0; 0; 10.117; 0; 3.8; 11.1; 1010.05; 15.6; 65.83; 21.5; 9.5; 6.0;eor 188 | 403;20180909;-999;-999;-999; 3; 0.0; 0; 9.800; 0; 3.6; 11.5; 1011.37; 17.8; 60.17; 25.9; 11.8; 9.2;eor 189 | 403;20180910;-999;-999;-999; 3; 0.0; 6; 4.367; 0; 5.8; 13.5; 1011.01; 18.6; 65.25; 26.0; 11.3; 8.7;eor 190 | 403;20180911;-999;-999;-999; 3; 0.0; 6; 8.500; 0; 6.1; 14.4; 1010.20; 20.3; 62.17; 26.4; 15.7; 13.0;eor 191 | 403;20180912;-999;-999;-999; 3; 0.0; 6; 7.733; 0; 4.4; 15.9; 1009.48; 19.9; 69.00; 27.8; 15.0; 11.3;eor 192 | 403;20180913;-999;-999;-999; 3; 0.5; 6; 0.000; 0; 7.9; 14.6; 1011.38; 14.6; 88.25; 16.5; 13.3; 12.5;eor 193 | 403;20180914;-999;-999;-999; 3; 0.0; 6; 3.283; 0; 6.3; 13.9; 1010.50; 15.6; 79.92; 20.4; 12.9; 9.5;eor 194 | 403;20180915;-999;-999;-999; 3; 0.8; 6; 5.883; 0; 4.9; 12.2; 1011.69; 15.7; 71.08; 21.0; 10.5; 6.4;eor 195 | 403;20180916;-999;-999;-999; 3; 0.0; 0; 7.750; 0; 5.6; 12.1; 1013.82; 14.9; 74.83; 22.4; 9.0; 6.5;eor 196 | 403;20180917;-999;-999;-999; 3; 0.0; 0; 11.000; 0; 4.9; 11.5; 1009.87; 17.1; 64.54; 27.0; 8.7; 4.9;eor 197 | 403;20180918;-999;-999;-999; 3; 0.0; 0; 11.533; 0; 3.0; 13.5; 1005.72; 19.7; 63.46; 30.2; 11.1; 7.8;eor 198 | 403;20180919;-999;-999;-999; 3; 0.0; 0; 11.033; 0; 1.8; 15.8; 1007.58; 20.6; 67.08; 28.7; 13.9; 10.5;eor 199 | 403;20180920;-999;-999;-999; 3; 0.0; 0; 9.883; 0; 4.2; 14.7; 1006.71; 20.3; 66.13; 28.8; 13.9; 11.0;eor 200 | 403;20180921;-999;-999;-999; 3; 1.7; 6; 6.067; 0; 5.2; 14.8; 999.16; 18.5; 73.46; 30.3; 10.9; 7.9;eor 201 | 403;20180922;-999;-999;-999; 3; 0.4; 6; 2.717; 0; 6.5; 10.1; 1006.71; 13.2; 67.75; 17.6; 9.8; 8.0;eor 202 | 403;20180923;-999;-999;-999; 3; 14.6; 6; 0.683; 0; 7.1; 11.5; 1002.50; 10.2; 92.50; 13.4; 8.2; 5.4;eor 203 | 403;20180924;-999;-999;-999; 3; 0.3; 8; 7.433; 0; 3.3; 8.7; 1013.51; 9.3; 75.21; 13.7; 6.1; 4.7;eor 204 | 403;20180925;-999;-999;-999; 3; 0.0; 0; 9.817; 0; 2.1; 7.8; 1026.00; 8.1; 74.42; 14.3; 3.3; 1.1;eor 205 | 403;20180926;-999;-999;-999; 3; 0.0; 0; 7.750; 0; 5.8; 7.4; 1022.08; 11.4; 59.50; 17.2; 3.2; 0.7;eor 206 | 403;20180927;-999;-999;-999; 3; 0.0; 0; 7.967; 0; 3.7; 12.9; 1015.07; 17.4; 64.71; 23.0; 12.2; 8.1;eor 207 | 403;20180928;-999;-999;-999; 3; 0.0; 0; 8.283; 0; 3.8; 9.2; 1012.30; 11.9; 66.75; 16.3; 6.2; 3.0;eor 208 | 403;20180929;-999;-999;-999; 3; 0.0; 0; 10.817; 0; 0.9; 8.2; 1017.81; 8.6; 75.83; 15.0; 3.1; 0.3;eor 209 | 403;20180930;-999;-999;-999; 3; 0.0; 0; 11.017; 0; 1.3; 7.8; 1007.79; 9.2; 71.75; 18.5; 2.5; 0.1;eor 210 | 403;20181001;-999;-999;-999; 3; 1.8; 6; 4.450; 0; 4.7; 9.5; 1002.92; 8.3; 87.21; 14.2; 3.5; 0.5;eor 211 | 403;20181002;-999;-999;-999; 3; 2.1; 6; 2.866; 0; 6.1; 9.7; 1003.98; 7.9; 89.86; 10.9; 4.6; 3.0;eor 212 | 403;20181003;-999;-999;-999; 3; 0.2; 6; 3.617; 0; 5.0; 9.1; 1007.43; 10.9; 70.21; 14.6; 8.5; 6.6;eor 213 | 403;20181004;-999;-999;-999; 3; 0.0; 0; 2.033; 0; 6.0; 11.4; 1015.56; 11.4; 84.38; 14.8; 7.7; 4.9;eor 214 | 403;20181005;-999;-999;-999; 3; 0.0; 0; 9.950; 0; 3.5; 11.6; 1011.56; 13.6; 77.29; 20.5; 8.0; 4.4;eor 215 | 403;20181006;-999;-999;-999; 3; 0.0; 0; 9.317; 0; 4.8; 12.3; 1001.40; 14.3; 77.79; 22.9; 6.9; 3.2;eor 216 | 403;20181007;-999;-999;-999; 3; 0.0; 0; 0.917; 0; 4.8; 10.7; 1006.73; 10.5; 84.13; 13.6; 3.2; 0.0;eor 217 | 403;20181008;-999;-999;-999; 3; 0.0; 0; 10.283; 0; 5.0; 8.3; 1013.29; 7.7; 81.92; 15.1; 1.9; -1.3;eor 218 | 403;20181009;-999;-999;-999; 3; 0.0; 0; 6.183; 0; 5.0; 10.8; 1013.24; 10.5; 86.88; 18.5; 3.9; 1.2;eor 219 | 403;20181010;-999;-999;-999; 3; 0.0; 0; 10.067; 0; 3.0; 12.7; 1012.98; 14.4; 80.00; 23.5; 6.8; 3.5;eor 220 | 403;20181011;-999;-999;-999; 3; 0.0; 0; 9.900; 0; 0.4; 12.4; 1008.92; 16.0; 72.17; 24.2; 10.8; 6.1;eor 221 | 403;20181012;-999;-999;-999; 3; 0.0; 0; 9.967; 0; 0.6; 12.5; 1012.55; 15.6; 73.79; 25.3; 9.0; 4.4;eor 222 | 403;20181013;-999;-999;-999; 3; 0.0; 0; 9.917; 0; 0.0; 12.5; 1013.72; 15.8; 73.67; 25.5; 9.4;-999;eor 223 | 403;20181014;-999;-999;-999; 3; 0.0; 0; 9.817; 0; 0.0; 11.4; 1006.70; 15.6; 67.13; 24.2; 9.2; 4.5;eor 224 | 403;20181015;-999;-999;-999; 3; 0.0; 0; 8.350; 0; 2.8; 10.2; 1006.27; 13.9; 66.29; 22.8; 8.7; 3.9;eor 225 | 403;20181016;-999;-999;-999; 3; 0.0; 0; 8.200; 0; 1.8; 10.8; 1008.71; 12.5; 77.33; 21.8; 6.6; 3.0;eor 226 | 403;20181017;-999;-999;-999; 3; 0.0; 0; 9.450; 0; 0.1; 11.2; 1009.72; 12.2; 82.08; 21.2; 6.2; 2.6;eor 227 | 403;20181018;-999;-999;-999; 3; 0.0; 6; 5.017; 0; 4.5; 12.1; 1011.52; 11.2; 90.71; 15.4; 6.6; 2.9;eor 228 | 403;20181019;-999;-999;-999; 3; 0.0; 0; 7.717; 0; 4.2; 9.1; 1015.53; 9.1; 80.21; 14.5; 2.8; -1.5;eor 229 | 403;20181020;-999;-999;-999; 3; 0.0; 6; 3.067; 0; 5.7; 7.9; 1018.32; 8.1; 75.21; 12.7; 2.5; -1.5;eor 230 | 403;20181021;-999;-999;-999; 3; 0.0; 0; 9.750; 0; 1.6; 8.7; 1018.56; 8.1; 82.83; 15.7; 2.9; -1.2;eor 231 | 403;20181022;-999;-999;-999; 3; 1.4; 6; 1.600; 0; 4.2; 9.2; 1017.20; 7.5; 88.38; 11.6; 4.0; 0.1;eor 232 | 403;20181023;-999;-999;-999; 3; 10.7; 6; 0.000; 0; 7.1; 10.4; 1003.88; 8.6; 91.42; 11.6; 4.5; 1.0;eor 233 | 403;20181024;-999;-999;-999; 3; 0.5; 6; 7.433; 0; 4.7; 7.7; 1003.87; 9.2; 66.67; 11.9; 4.7; 1.2;eor 234 | 403;20181025;-999;-999;-999; 3; 0.6; 6; 0.317; 0; 7.5; 10.9; 1001.49; 11.1; 82.50; 12.7; 9.4; 8.7;eor 235 | 403;20181026;-999;-999;-999; 3; 0.1; 6; 0.467; 0; 7.0; 9.9; 996.53; 9.8; 81.29; 12.0; 7.1; 3.8;eor 236 | 403;20181027;-999;-999;-999; 3; 0.0; 0; 0.850; 0; 6.6; 7.6; 996.16; 7.5; 72.83; 9.6; 4.0; 1.2;eor 237 | 403;20181028;-999;-999;-999; 3; 0.2; 6; 0.900; 0; 7.6; 7.6; 1004.92; 5.9; 81.67; 8.4; 3.6; 2.8;eor 238 | 403;20181029;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.9; 7.6; 997.87; 4.6; 89.63; 6.2; 3.9; 3.8;eor 239 | 403;20181030;-999;-999;-999; 3; 0.3; 6; 6.083; 0; 5.6; 10.0; 986.34; 12.7; 69.46; 21.1; 6.2; 6.2;eor 240 | 403;20181031;-999;-999;-999; 3; 0.0; 0; 8.833; 0; 3.6; 7.4; 1007.04; 8.4; 67.63; 13.2; 4.6; 0.7;eor 241 | 403;20181101;-999;-999;-999; 3; 0.0; 0; 2.833; 0; 5.4; 9.3; 1004.12; 7.7; 88.33; 11.8; 3.4; 0.0;eor 242 | 403;20181102;-999;-999;-999; 3; 0.0; 0; 6.117; 0; 4.7; 9.1; 1011.88; 7.9; 87.04; 14.2; 3.9; 0.3;eor 243 | 403;20181103;-999;-999;-999; 3; 0.0; 0; 1.833; 0; 5.3; 9.0; 1019.12; 7.0; 90.50; 11.1; 4.5; 0.9;eor 244 | 403;20181104;-999;-999;-999; 3; 0.0; 0; 0.000; 0; 7.7; 11.2; 1010.98; 9.2; 96.17; 10.8; 4.7; 1.4;eor 245 | 403;20181105;-999;-999;-999; 3; 0.0; 0; 2.800; 0; 6.7; 11.7; 1003.46; 10.8; 90.63; 14.7; 7.9; 3.7;eor 246 | 403;20181106;-999;-999;-999; 3; 0.0; 0; 8.317; 0; 1.5; 11.0; 1001.29; 10.8; 85.92; 17.9; 5.8; 1.8;eor 247 | 403;20181107;-999;-999;-999; 3; 0.0; 0; 8.367; 0; 2.3; 11.1; 1002.49; 9.5; 93.83; 16.0; 5.7; 1.5;eor 248 | 403;20181108;-999;-999;-999; 3; 0.1; 6; 3.533; 0; 5.4; 10.7; 1010.39; 8.5; 95.38; 13.7; 4.2; 1.4;eor 249 | 403;20181109;-999;-999;-999; 3; -999; 6; 0.000; 0; 6.9; 11.3; 1008.11; 8.7; 100.00; 10.4; 6.8;-999;eor 250 | 403;20181110;-999;-999;-999; 3; 0.0; 6; 3.033;-999; 5.7; 10.5; 1001.56; 7.9; 97.92; 12.0; 5.0; 1.6;eor 251 | 403;20181111;-999;-999;-999; 3; 1.7; 6; 1.817; 0; 5.9; 10.8; 1002.64; 8.0; 100.00; 11.2; 6.1; 3.9;eor 252 | 403;20181112;-999;-999;-999; 3; 0.7; 6; 2.083; 0; 5.9; 11.6; 1007.30; 11.0; 89.00; 15.1; 7.6; 4.6;eor 253 | 403;20181113;-999;-999;-999; 3; 8.9; 6; 1.117; 0; 6.0; 11.8; 1012.26; 9.7; 97.42; 12.3; 6.8; 4.4;eor 254 | 403;20181114;-999;-999;-999; 3; 0.0; 0; 6.433; 0; 5.0; 9.7; 1019.45; 7.2; 96.13; 11.0; 4.7; 1.2;eor 255 | 403;20181115;-999;-999;-999; 3; 0.0; 0; 0.483; 0; 4.6; 8.9; 1020.60; 6.3; 93.00; 10.4; 4.2; 1.1;eor 256 | 403;20181116;-999;-999;-999; 3; 0.0; 0; 8.200; 0; 2.3; 6.9; 1025.10; 5.0; 79.92; 9.3; 1.6; -1.6;eor 257 | 403;20181117;-999;-999;-999; 3; 0.0; 0; 7.833; 0; 1.3; 5.7; 1027.83; 1.5; 84.67; 5.5; -2.5; -5.5;eor 258 | 403;20181118;-999;-999;-999; 3; 0.0; 6; 1.567; 0; 5.0; 6.1; 1020.85; 1.6; 87.83; 5.8; -3.8; -6.4;eor 259 | 403;20181119;-999;-999;-999; 3; 0.7; 6; 0.500; 0; 6.6; 7.1; 1013.21; 3.9; 88.29; 5.6; 2.2; -0.1;eor 260 | 403;20181120;-999;-999;-999; 3; 0.0; 8; 0.000; 0; 7.9; 5.6; 1009.32; 2.3; 77.29; 3.3; 1.7; 1.2;eor 261 | 403;20181121;-999;-999;-999; 3; 0.0; 8; 0.000; 0; 8.0; 5.4; 1012.14; 1.2; 80.96; 1.8; 0.4; 0.0;eor 262 | 403;20181122;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 8.0; 5.7; 1014.76; 1.1; 86.29; 1.9; 0.5; 0.5;eor 263 | 403;20181123;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.8; 6.8; 1012.09; 1.9; 96.79; 3.2; 0.5; -1.1;eor 264 | 403;20181124;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.9; 7.0; 1004.91; 2.2; 97.96; 3.5; 0.2; 0.5;eor 265 | 403;20181125;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.8; 8.1; 1002.98; 4.3; 97.38; 5.7; 2.6; 0.9;eor 266 | 403;20181126;-999;-999;-999; 3; 0.0; 0; 0.000; 0; 7.5; 6.4; 1004.59; 2.5; 86.79; 3.9; -0.3; -3.2;eor 267 | 403;20181127;-999;-999;-999; 3; 0.0; 0; 0.000; 0; 7.0; 5.1; 1012.65; 0.0; 84.38; 2.0; -2.6; -5.0;eor 268 | 403;20181128;-999;-999;-999; 3; 0.0; 0; 7.333; 0; 2.8; 4.7; 1018.37; 0.2; 75.88; 3.7; -3.1; -5.7;eor 269 | 403;20181129;-999;-999;-999; 3; 0.0; 6; 5.067; 0; 6.4; 3.8; 1012.53; 0.3; 62.63; 3.0; -2.1; -4.0;eor 270 | 403;20181130;-999;-999;-999; 3; 3.0; 6; 0.000; 0; 7.8; 4.9; 1005.89; 0.7; 75.92; 1.7; 0.3; -0.7;eor 271 | 403;20181201;-999;-999;-999; 3; 0.0; 6; 1.233; 0; 6.4; 7.7; 1004.34; 3.3; 98.96; 6.7; 0.7; -1.1;eor 272 | 403;20181202;-999;-999;-999; 3; 2.3; 6; 0.000; 0; 7.3; 9.0; 993.44; 6.4; 92.25; 9.6; 3.7; 1.4;eor 273 | 403;20181203;-999;-999;-999; 3; 1.7; 6; 1.650; 0; 5.8; 11.9; 990.24; 10.3; 95.00; 13.6; 7.1; 2.6;eor 274 | 403;20181204;-999;-999;-999; 3; 0.0; 4; 2.800; 0; 3.8; 7.7; 1003.65; 6.4; 78.92; 10.1; 2.4; 0.3;eor 275 | 403;20181205;-999;-999;-999; 3; 0.0; 6; 7.067; 0; 2.2; 6.1; 1016.40; 2.0; 87.33; 7.4; -0.9; -3.6;eor 276 | 403;20181206;-999;-999;-999; 3; 1.2; 6; 0.050; 0; 7.8; 7.3; 1006.75; 4.8; 82.63; 9.3; 1.3; -0.1;eor 277 | 403;20181207;-999;-999;-999; 3; 7.7; 6; 0.000; 0; 7.9; 12.0; 995.41; 10.3; 95.92; 12.1; 9.2; 8.0;eor 278 | 403;20181208;-999;-999;-999; 3; 3.2; 6; 0.183; 0; 5.8; 7.8; 990.07; 7.0; 77.42; 9.4; 5.0; 2.7;eor 279 | 403;20181209;-999;-999;-999; 3; 1.5; 6; 0.033; 0; 7.4; 8.7; 983.38; 7.1; 85.83; 8.2; 5.8; 5.4;eor 280 | 403;20181210;-999;-999;-999; 3; 0.4; 6; 1.217; 0; 6.9; 6.7; 998.75; 4.6; 79.29; 5.9; 3.4; 2.7;eor 281 | 403;20181211;-999;-999;-999; 3; 4.1; 6; 0.000; 0; 7.6; 7.3; 1004.18; 3.7; 92.00; 4.8; 2.2; 1.1;eor 282 | 403;20181212;-999;-999;-999; 3; 0.0; 6; 0.267; 0; 6.8; 6.8; 1013.83; 2.8; 90.79; 4.2; 1.5; -1.6;eor 283 | 403;20181213;-999;-999;-999; 3; 0.0; 8; 0.000; 0; 7.9; 6.4; 1014.36; 2.1; 90.29; 2.7; 0.8; 0.2;eor 284 | 403;20181214;-999;-999;-999; 3; 0.0; 0; 0.000; 0; 7.6; 5.2; 1016.49; 0.4; 82.29; 1.1; -0.4; -1.0;eor 285 | 403;20181215;-999;-999;-999; 3; 0.0; 4; 0.000; 0; 7.9; 5.2; 1018.12; 0.0; 84.25; 0.9; -0.6; -0.9;eor 286 | 403;20181216;-999;-999;-999; 3; 0.0; 7; 0.000; 0; 7.7; 4.6; 1007.25; -0.6; 79.21; 0.2; -1.6; -3.6;eor 287 | 403;20181217;-999;-999;-999; 3; 0.0; 8; 0.000; 0; 7.6; 6.0; 1010.55; 0.8; 91.75; 2.3; -1.2; -1.3;eor 288 | 403;20181218;-999;-999;-999; 3; 0.0; 6; 0.967; 0; 7.0; 7.3; 1014.93; 3.0; 95.75; 6.5; -0.1; -3.1;eor 289 | 403;20181219;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.1; 6.4; 1007.93; 1.5; 93.96; 2.9; -0.8; -3.9;eor 290 | 403;20181220;-999;-999;-999; 3; 1.2; 6; 0.117; 0; 7.4; 7.5; 1004.84; 3.7; 93.46; 5.1; 2.5; -0.1;eor 291 | 403;20181221;-999;-999;-999; 3; 6.7; 6; 0.000; 0; 7.5; 9.2; 996.05; 6.4; 95.92; 10.7; 3.9; 0.8;eor 292 | 403;20181222;-999;-999;-999; 3; 7.5; 6; 0.000; 0; 7.3; 7.9; 997.66; 6.5; 82.13; 9.7; 3.8; 1.7;eor 293 | 403;20181223;-999;-999;-999; 3; 3.9; 6; 0.000; 0; 7.8; 9.0; 1005.24; 5.8; 97.13; 7.4; 4.1; 3.0;eor 294 | 403;20181224;-999;-999;-999; 3; 0.7; 8; 0.000; 0; 7.8; 6.3; 1013.10; 1.8; 89.29; 5.4; -0.1; -0.1;eor 295 | 403;20181225;-999;-999;-999; 3; 0.2; 6; 0.000; 0; 7.5; 7.3; 1017.89; 4.6; 85.83; 5.7; 3.0; 2.7;eor 296 | 403;20181226;-999;-999;-999; 3; 0.6; 6; 0.000; 0; 7.8; 8.4; 1016.41; 5.5; 93.38; 6.3; 4.6; 4.1;eor 297 | 403;20181227;-999;-999;-999; 3; 0.4; 6; 0.017; 0; 7.9; 8.6; 1014.25; 5.1; 97.08; 5.9; 3.8; 2.3;eor 298 | 403;20181228;-999;-999;-999; 3; 1.0; 6; 0.000; 0; 7.8; 8.7; 1014.53; 5.9; 94.04; 6.8; 5.0; 4.8;eor 299 | 403;20181229;-999;-999;-999; 3; 5.8; 6; 0.000; 0; 7.9; 8.9; 1014.50; 5.6; 97.42; 6.6; 4.3; 4.1;eor 300 | 403;20181230;-999;-999;-999; 3; 0.1; 6; 0.017; 0; 6.7; 7.9; 1012.66; 6.2; 83.96; 7.7; 3.5; 1.4;eor 301 | 403;20181231;-999;-999;-999; 3; 0.4; 6; 0.050; 0; 7.5; 8.7; 1019.43; 5.5; 96.29; 8.2; 3.0; 1.4;eor 302 | 403;20190101;-999;-999;-999; 3; 2.2; 8; 0.633; 0; 7.2; 8.0; 1007.15; 6.4; 82.33; 8.5; 3.1; 2.1;eor 303 | 403;20190102;-999;-999;-999; 3; 0.1; 7; 1.250; 0; 4.1; 4.3; 1013.65; 1.8; 61.83; 3.5; -1.5; -3.6;eor 304 | 403;20190103;-999;-999;-999; 3; 0.0; 7; 0.000; 0; 4.2; 4.9; 1022.47; -0.4; 82.58; 1.5; -2.5; -5.2;eor 305 | 403;20190104;-999;-999;-999; 3; 1.9; 6; 0.000; 0; 7.6; 6.8; 1017.32; 1.8; 97.71; 4.7; -1.0; -1.5;eor 306 | 403;20190105;-999;-999;-999; 3; 0.0; 8; 0.433; 0; 7.3; 8.7; 1009.96; 6.0; 92.63; 7.9; 2.4; 0.1;eor 307 | 403;20190106;-999;-999;-999; 3; 0.2; 8; 0.633; 0; 6.7; 6.1; 1017.64; 2.0; 87.04; 3.3; 0.0; -2.2;eor 308 | 403;20190107;-999;-999;-999; 3; 6.5; 6; 0.000; 0; 7.6; 7.6; 1014.93; 3.0; 99.13; 5.6; -0.3; -2.4;eor 309 | 403;20190108;-999;-999;-999; 3; 10.2; 8; 0.000; 0; 7.3; 8.1; 991.73; 4.6; 95.50; 6.0; 2.1; 1.7;eor 310 | 403;20190109;-999;-999;-999; 3; 2.3; 8; 0.000; 0; 7.9; 6.7; 996.97; 1.9; 95.00; 2.9; 1.0; 0.4;eor 311 | 403;20190110;-999;-999;-999; 3; 0.0; 8; 0.467; 0; 7.3; 5.5; 1012.08; 0.9; 83.13; 2.0; 0.0; -0.6;eor 312 | 403;20190111;-999;-999;-999; 3; 1.5; 8; 0.000; 0; 7.8; 6.9; 1006.65; 2.2; 95.25; 5.4; -0.2; -0.5;eor 313 | 403;20190112;-999;-999;-999; 3; 3.8; 6; 0.000; 0; 7.9; 7.9; 1000.15; 4.9; 90.88; 5.8; 4.0; 3.4;eor 314 | 403;20190113;-999;-999;-999; 3; 4.0; 8; 0.000; 0; 7.8; 8.9; 985.71; 6.1; 94.21; 7.9; 5.0; 4.4;eor 315 | 403;20190114;-999;-999;-999; 3; 0.0; 8; 3.833; 0; 4.0; 4.5; 991.11; 2.5; 61.63; 6.0; 0.2; -1.0;eor 316 | 403;20190115;-999;-999;-999; 3; 1.6; 8; 0.000; 0; 7.4; 7.0; 999.09; 3.9; 85.33; 6.5; 1.3; 0.0;eor 317 | 403;20190116;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.8; 7.9; 996.63; 6.1; 83.58; 7.0; 2.8; 1.0;eor 318 | 403;20190117;-999;-999;-999; 3; 3.3; 8; 1.817; 0; 7.2; 6.6; 989.95; 4.4; 79.04; 7.3; 1.7; 0.7;eor 319 | 403;20190118;-999;-999;-999; 3; 0.0; 7; 7.733; 1; 5.0; 5.1; 1005.23; 0.4; 80.71; 2.1; -1.4; -3.1;eor 320 | 403;20190119;-999;-999;-999; 3; 0.0; 0; 6.100; 0; 5.1; 5.1; 1010.10; -0.2; 84.88; 3.3; -4.2; -6.4;eor 321 | 403;20190120;-999;-999;-999; 3; 0.0; 0; 7.583; 0; 2.7; 4.6; 1010.07; -2.7; 91.83; 1.9; -6.2; -8.4;eor 322 | 403;20190121;-999;-999;-999; 3; 0.0; 7; 2.567; 0; 6.7; 4.5; 1011.70; -3.5; 94.17; -2.0; -4.9; -6.8;eor 323 | 403;20190122;-999;-999;-999; 3; 0.0; 7; 6.067; 0; 2.9; 4.0; 1002.30; -3.5; 86.29; 0.7; -5.6; -7.7;eor 324 | 403;20190123;-999;-999;-999; 3; 0.0; 7; 2.900; 0; 6.6; 3.6; 996.22; -5.5; 89.04; -3.5; -6.8; -7.3;eor 325 | 403;20190124;-999;-999;-999; 3; 0.0; 7; 0.000; 0; 7.9; 3.6; 1002.60; -3.9; 78.38; -3.3; -4.5; -4.2;eor 326 | 403;20190125;-999;-999;-999; 3; 0.7; 7; 1.367; 0; 7.5; 3.8; 1004.30; -3.7; 81.42; -2.3; -4.6; -4.5;eor 327 | 403;20190126;-999;-999;-999; 3; 5.0; 8; 0.000; 1; 8.0; 6.4; 992.63; 0.6; 98.00; 3.6; -3.2; -3.3;eor 328 | 403;20190127;-999;-999;-999; 3; 2.7; 6; 0.000; 0; 7.3; 7.6; 980.55; 4.0; 93.42; 6.0; 2.4; 0.8;eor 329 | 403;20190128;-999;-999;-999; 3; 1.8; 8; 4.267; 0; 6.8; 6.9; 981.84; 3.0; 90.79; 5.7; 1.1; -1.1;eor 330 | 403;20190129;-999;-999;-999; 3; 0.0; 7; 0.717; 0; 6.8; 6.1; 992.87; 0.9; 93.71; 3.2; -2.0; -4.1;eor 331 | 403;20190130;-999;-999;-999; 3; 0.0; 0; 5.967; 0; 5.1; 4.9; 990.88; -0.5; 83.38; 3.1; -3.0; -4.9;eor 332 | 403;20190131;-999;-999;-999; 3; 0.0; 0; 2.617; 0; 6.0; 5.0; 990.59; 0.1; 82.63; 4.7; -2.2; -4.8;eor 333 | 403;20190201;-999;-999;-999; 3; 1.3; 8; 0.000; 0; 5.5; 5.1; 987.02; -0.7; 87.25; 1.9; -3.6; -5.9;eor 334 | 403;20190202;-999;-999;-999; 3; 1.1; 8; 0.000; 0; 8.0; 6.3; 987.77; 0.7; 98.13; 1.4; 0.3; -0.1;eor 335 | 403;20190203;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.6; 6.4; 1003.76; 1.0; 97.29; 1.8; -0.5; -2.0;eor 336 | 403;20190204;-999;-999;-999; 3; 0.1; 7; 7.783; 0; 3.8; 5.5; 1016.62; 1.0; 85.50; 6.0; -1.7; -3.7;eor 337 | 403;20190205;-999;-999;-999; 3; 0.0; 7; 0.000; 0; 7.6; 5.6; 1016.05; 2.1; 78.58; 3.7; -0.3; -2.1;eor 338 | 403;20190206;-999;-999;-999; 3; 0.0; 0; 6.783; 0; 7.0; 5.7; 1014.57; 3.1; 75.63; 7.0; -0.2; -3.2;eor 339 | 403;20190207;-999;-999;-999; 3; 0.2; 6; 0.683; 0; 6.5; 5.1; 1003.02; 2.3; 71.04; 5.4; -0.5; -2.5;eor 340 | 403;20190208;-999;-999;-999; 3; 0.0; 4; 3.633; 0; 5.1; 6.8; 1003.30; 5.2; 76.75; 8.3; 1.9; -1.9;eor 341 | 403;20190209;-999;-999;-999; 3; 0.9; 8; 3.433; 0; 6.2; 6.7; 995.14; 7.5; 65.29; 11.1; 5.0; 2.7;eor 342 | 403;20190210;-999;-999;-999; 3; 10.6; 8; 0.000; 0; 6.8; 8.4; 988.25; 6.2; 88.21; 8.5; 3.7; -0.1;eor 343 | 403;20190211;-999;-999;-999; 3; 0.2; 6; 1.750; 0; 5.5; 6.3; 996.55; 4.3; 76.33; 7.4; 0.9; -0.1;eor 344 | 403;20190212;-999;-999;-999; 3; 0.1; 6; 5.383; 0; 5.6; 5.3; 1016.93; 3.1; 70.29; 5.8; 1.0; -2.5;eor 345 | 403;20190213;-999;-999;-999; 3; 0.3; 6; 0.000; 0; 8.0; 8.7; 1021.63; 6.1; 91.83; 8.0; 3.6; 2.6;eor 346 | 403;20190214;-999;-999;-999; 3; 0.0; 0; 6.100; 0; 3.8; 7.8; 1024.85; 6.2; 82.50; 10.6; -0.2; -3.2;eor 347 | 403;20190215;-999;-999;-999; 3; 0.0; 0; 9.633; 0; 1.8; 5.6; 1023.23; 4.5; 72.17; 14.0; -2.0; -4.1;eor 348 | 403;20190216;-999;-999;-999; 3; 0.0; 0; 9.783; 0; 1.0; 5.8; 1016.30; 5.9; 68.38; 16.6; -1.3; -4.2;eor 349 | 403;20190217;-999;-999;-999; 3; 0.0; 0; 9.000; 0; 4.8; 6.5; 1014.21; 4.8; 78.13; 14.4; -1.2; -3.7;eor 350 | 403;20190218;-999;-999;-999; 3; 0.0; 0; 9.600; 0; 2.0; 6.4; 1009.15; 5.8; 73.92; 15.4; -1.3; -4.0;eor 351 | 403;20190219;-999;-999;-999; 3; 0.5; 6; 0.900; 0; 6.1; 7.3; 1005.39; 6.2; 77.25; 9.8; 1.5; -2.9;eor 352 | 403;20190220;-999;-999;-999; 3; 0.3; 6; 1.700; 0; 6.8; 7.8; 1010.97; 7.5; 75.75; 10.1; 5.4; 1.7;eor 353 | 403;20190221;-999;-999;-999; 3; 3.3; 6; 1.050; 0; 7.4; 9.0; 1013.34; 8.0; 83.04; 10.6; 5.7; 1.9;eor 354 | 403;20190222;-999;-999;-999; 3; 0.1; 6; 7.000; 0; 3.5; 5.8; 1026.67; 3.4; 69.42; 8.6; -2.5; -5.3;eor 355 | 403;20190223;-999;-999;-999; 3; 0.0; 0; 9.083; 0; 3.2; 3.4; 1033.40; -0.2; 57.92; 5.1; -4.0; -5.8;eor 356 | 403;20190224;-999;-999;-999; 3; 0.0; 0; 7.800; 0; 2.3; 3.9; 1028.89; 2.8; 55.46; 12.5; -3.3; -5.1;eor 357 | 403;20190225;-999;-999;-999; 3; 0.0; 0; 9.683; 0; 4.1; 5.9; 1026.35; 5.9; 64.46; 13.7; -1.9; -4.5;eor 358 | 403;20190226;-999;-999;-999; 3; 0.0; 0; 2.150; 0; 4.9; 7.4; 1022.65; 6.4; 76.54; 11.4; 2.2; -2.0;eor 359 | 403;20190227;-999;-999;-999; 3; 0.0; 0; 9.883; 0; 1.3; 5.6; 1015.17; 7.0; 62.29; 16.2; -0.1; -2.6;eor 360 | 403;20190228;-999;-999;-999; 3; 0.0; 6; 7.750; 0; 3.8; 7.4; 1001.68; 7.8; 69.46; 12.6; 2.3; -2.5;eor 361 | 403;20190301;-999;-999;-999; 3; 0.0; 6; 0.000; 0; 7.6; 7.2; 1002.22; 4.3; 85.71; 5.4; 2.7; -0.6;eor 362 | 403;20190302;-999;-999;-999; 3; 0.4; 6; 0.000; 0; 7.5; 6.2; 1004.89; 3.8; 77.46; 5.5; 2.4; -0.1;eor 363 | 403;20190303;-999;-999;-999; 3; 1.0; 6; 0.000; 0; 7.8; 9.8; 996.03; 8.7; 86.83; 11.5; 4.1; 3.1;eor 364 | 403;20190304;-999;-999;-999; 3; 2.7; 6; 1.667; 0; 5.7; 8.6; 983.77; 9.5; 72.63; 15.1; 6.1; 3.9;eor 365 | 403;20190305;-999;-999;-999; 3; 0.8; 8; 3.117; 0; 5.2; 7.0; 992.50; 6.0; 75.63; 8.9; 1.7; -1.9;eor 366 | 403;20190306;-999;-999;-999; 3; 1.2; 6; 7.233; 0; 5.5; 7.0; 997.98; 6.7; 73.33; 12.7; 0.1; -2.9;eor 367 | 403;20190307;-999;-999;-999; 3; 0.2; 6; 1.950; 0; 5.7; 8.6; 987.66; 10.3; 69.25; 16.8; 7.2; 3.7;eor 368 | 403;20190308;-999;-999;-999; 3; 2.2; 6; 3.833; 0; 4.1; 7.2; 996.02; 7.6; 68.50; 9.6; 4.5; -0.4;eor 369 | 403;20190309;-999;-999;-999; 3; 6.9; 8; 2.067; 0; 6.7; 7.9; 995.64; 7.1; 79.04; 11.6; 4.5; 2.5;eor 370 | 403;20190310;-999;-999;-999; 3; 13.7; 8; 0.800; 0; 6.7; 7.2; 993.36; 4.4; 86.25; 7.7; 0.4; 0.0;eor 371 | 403;20190311;-999;-999;-999; 3; 3.0; 6; 1.833; 0; 7.1; 7.0; 1000.67; 3.1; 91.67; 5.3; 1.3; 0.1;eor 372 | 403;20190312;-999;-999;-999; 3; 0.7; 6; 3.217; 0; 7.1; 6.4; 1005.21; 5.4; 73.17; 9.5; 1.8; 1.3;eor 373 | 403;20190313;-999;-999;-999; 3; 1.6; 6; 3.583; 0; 6.6; 6.4; 991.86; 7.3; 63.29; 9.6; 4.6; 2.1;eor 374 | 403;20190314;-999;-999;-999; 3; 10.6; 6; 0.117; 0; 7.6; 8.3; 988.01; 5.7; 90.54; 8.4; 4.0; 3.1;eor 375 | 403;20190315;-999;-999;-999; 3; 1.0; 6; 0.817; 0; 6.3; 8.1; 988.32; 7.5; 78.54; 10.0; 5.5; 4.5;eor 376 | 403;20190316;-999;-999;-999; 3; 5.4; 6; 1.400; 0; 6.9; 8.0; 994.65; 6.5; 81.83; 8.7; 4.6; 3.8;eor 377 | 403;20190317;-999;-999;-999; 3; 0.9; 8; 2.650; 0; 6.5; 8.1; 991.45; 8.3; 74.29; 13.0; 3.9; 1.1;eor 378 | 403;20190318;-999;-999;-999; 3; 1.1; 8; 3.150; 0; 4.7; 6.5; 1001.68; 5.0; 75.38; 8.9; 2.8; 0.2;eor 379 | 403;20190319;-999;-999;-999; 3; 0.0; 8; 3.550; 0; 4.3; 6.1; 1015.07; 4.4; 73.67; 8.3; -0.6; -3.5;eor 380 | 403;20190320;-999;-999;-999; 3; 0.0; 0; 8.933; 0; 4.6; 6.5; 1022.39; 6.9; 68.75; 12.8; -2.6; -4.4;eor 381 | 403;20190321;-999;-999;-999; 3; 0.0; 6; 0.717; 0; 6.3; 10.0; 1023.55; 9.5; 84.54; 11.9; 4.8; 0.9;eor 382 | 403;20190322;-999;-999;-999; 3; 0.0; 0; 2.683; 0; 5.1; 10.1; 1022.17; 8.4; 91.96; 11.8; 4.7; 1.0;eor 383 | 403;20190323;-999;-999;-999; 3; 0.0; 0; 10.317; 0; 5.1; 9.6; 1017.09; 9.5; 81.92; 16.2; 4.1; 1.0;eor 384 | 403;20190324;-999;-999;-999; 3; 0.0; 8; 7.517; 0; 4.8; 6.6; 1014.91; 6.6; 69.75; 12.0; 2.5; -1.6;eor 385 | 403;20190325;-999;-999;-999; 3; 4.1; 8; 3.983; 0; 5.1; 6.8; 1006.07; 4.3; 82.33; 7.9; 1.4; -0.3;eor 386 | 403;20190326;-999;-999;-999; 3; 1.1; 8; 2.517; 0; 5.7; 7.2; 1014.01; 4.9; 83.83; 7.8; 1.6; -0.4;eor 387 | 403;20190327;-999;-999;-999; 3; 2.4; 6; 0.483; 0; 7.2; 9.0; 1019.19; 7.3; 87.92; 9.9; 3.3; -0.3;eor 388 | 403;20190328;-999;-999;-999; 3; 0.8; 6; 0.000; 0; 8.0; 11.0; 1022.39; 8.7; 98.04; 10.0; 7.9; 7.6;eor 389 | 403;20190329;-999;-999;-999; 3; 0.0; 0; 0.000; 0; 6.8; 10.1; 1021.75; 9.4; 86.58; 12.1; 4.1; 0.3;eor 390 | 403;20190330;-999;-999;-999; 3; 0.0; 0; 11.250; 0; 4.2; 8.2; 1012.55; 10.2; 70.21; 18.6; 2.2; -1.1;eor 391 | 403;20190331;-999;-999;-999; 3; 0.0; 0; 6.300; 0; 2.7; 6.8; 1012.98; 8.0; 63.29; 11.9; 1.4; -3.4;eor 392 | 403;20190401;-999;-999;-999; 3; 0.0; 0; 12.417; 0; 0.1; 4.8; 1016.39; 5.7; 54.63; 12.2; -2.0; -5.2;eor 393 | 403;20190402;-999;-999;-999; 3; 0.0; 0; 10.750; 0; 3.3; 5.9; 1003.67; 8.8; 51.71; 15.7; 2.1; -1.9;eor 394 | 403;20190403;-999;-999;-999; 3; 0.0; 0; 8.767; 0; 6.3; 8.8; 994.09; 13.1; 59.50; 19.7; 7.1; 3.8;eor 395 | 403;20190404;-999;-999;-999; 3; 0.0; 0; 11.483; 0; 3.2; 9.2; 989.57; 14.4; 56.75; 20.9; 7.8; 2.3;eor 396 | 403;20190405;-999;-999;-999; 3; 0.0; 0; 5.067; 0; 5.6; 9.7; 995.58; 10.4; 77.25; 14.6; 6.0; 2.7;eor 397 | 403;20190406;-999;-999;-999; 3; 0.0; 0; 11.683; 0; 1.5; 9.2; 997.80; 14.6; 58.50; 22.1; 7.1; 3.0;eor 398 | 403;20190407;-999;-999;-999; 3; 0.0; 0; 12.200; 0; 0.4; 8.0; 998.56; 13.7; 52.25; 19.8; 6.5; 1.4;eor 399 | 403;20190408;-999;-999;-999; 3; 0.0; 6; 11.017; 0; 0.7; 8.0; 1000.70; 11.9; 60.04; 20.0; 4.0; 0.0;eor 400 | 403;20190409;-999;-999;-999; 3; 0.0; 0; 11.317; 0; 3.2; 6.7; 1005.07; 7.1; 67.71; 12.4; 3.3; -1.2;eor 401 | 403;20190410;-999;-999;-999; 3; 0.0; 0; 6.833; 0; 5.0; 5.5; 1008.37; 5.6; 61.88; 10.5; 1.1; -2.9;eor 402 | 403;20190411;-999;-999;-999; 3; 0.0; 8; 3.950; 0; 6.2; 5.4; 1014.72; 3.9; 67.29; 6.5; 1.2; -1.0;eor 403 | 403;20190412;-999;-999;-999; 3; 0.0; 7; 0.000; 0; 7.8; 5.7; 1016.10; 3.3; 73.75; 4.8; 2.1; 1.9;eor 404 | 403;20190413;-999;-999;-999; 3; 0.0; 8; 0.250; 0; 7.6; 5.7; 1014.49; 4.7; 66.54; 7.6; 2.2; 1.1;eor 405 | 403;20190414;-999;-999;-999; 3; 1.5; 6; 0.117; 0; 6.9; 7.3; 1015.41; 5.9; 79.33; 9.9; 2.7; -0.4;eor 406 | 403;20190415;-999;-999;-999; 3; 0.0; 0; 13.217; 0; 0.3; 5.6; 1017.56; 7.9; 54.83; 13.8; 1.7; -2.4;eor 407 | 403;20190416;-999;-999;-999; 3; 0.0; 0; 13.000; 0; 0.4; 5.3; 1014.05; 9.2; 48.92; 16.3; 1.2; -3.8;eor 408 | 403;20190417;-999;-999;-999; 3; 0.0; 0; 13.250; 0; 0.8; 6.6; 1017.69; 11.2; 48.63; 18.6; 2.8; -2.5;eor 409 | 403;20190418;-999;-999;-999; 3; 0.0; 0; 13.083; 0; 0.4; 7.0; 1020.49; 13.6; 48.54; 21.3; 5.3; -0.2;eor 410 | 403;20190419;-999;-999;-999; 3; 0.0; 0; 13.267; 0; 0.0; 7.0; 1022.80; 15.1; 42.29; 22.5; 7.8; 1.8;eor 411 | 403;20190420;-999;-999;-999; 3; 0.0; 0; 13.483; 0; 1.8; 7.4; 1020.34; 13.2; 50.75; 21.5; 4.0; -0.6;eor 412 | 403;20190421;-999;-999;-999; 3; 0.0; 0; 13.733; 0; 1.2; 7.6; 1013.59; 14.0; 47.58; 21.1; 5.8; 0.0;eor 413 | 403;20190422;-999;-999;-999; 3; 0.0; 0; 13.600; 0; 1.1; 7.8; 1007.75; 13.3; 51.04; 19.1; 7.2; 0.6;eor 414 | 403;20190423;-999;-999;-999; 3; 0.0; 6; 8.900; 0; 3.7; 8.3; 1000.33; 14.4; 51.17; 19.8; 9.3; 5.2;eor 415 | 403;20190424;-999;-999;-999; 3; 0.2; 6; 11.050; 0; 4.1; 11.2; 997.23; 17.0; 58.42; 23.3; 11.6; 8.6;eor 416 | 403;20190425;-999;-999;-999; 3; 0.0; 0; 13.033; 0; 3.6; 10.9; 1001.12; 18.4; 54.71; 25.4; 12.6; 8.4;eor 417 | 403;20190426;-999;-999;-999; 3; 2.4; 6; 10.450; 0; 5.8; 12.4; 998.90; 18.0; 60.38; 24.0; 10.2; 7.3;eor 418 | 403;20190427;-999;-999;-999; 3; 0.4; 6; 2.567; 0; 6.3; 10.7; 1002.51; 12.9; 74.13; 18.1; 9.4; 5.0;eor 419 | 403;20190428;-999;-999;-999; 3; 0.4; 6; 2.117; 0; 7.2; 9.8; 1007.47; 10.1; 80.33; 13.1; 8.1; 7.9;eor 420 | 403;20190429;-999;-999;-999; 3; 1.1; 6; 4.100; 0; 5.4; 9.8; 1008.07; 10.3; 78.33; 17.1; 5.5; 3.7;eor 421 | 403;20190430;-999;-999;-999; 3; 0.5; 6; 13.350; 0; 2.5; 6.2; 1007.78; 10.7; 51.88; 18.1; 3.5; 1.6;eor 422 | 403;20190501;-999;-999;-999; 3; 0.0; 6; 9.367; 0; 5.3; 10.5; 1002.47; 12.5; 73.63; 17.2; 7.7; 4.4;eor 423 | 403;20190502;-999;-999;-999; 3; 1.0; 6; 0.150; 0; 7.6; 9.8; 996.51; 9.9; 80.17; 13.2; 7.0; 5.6;eor 424 | 403;20190503;-999;-999;-999; 3; 0.0; 6; 5.567; 0; 6.3; 6.6; 998.00; 8.4; 60.38; 11.3; 5.5; 4.1;eor 425 | 403;20190504;-999;-999;-999; 3; 0.0; 6; 3.917; 0; 5.4; 6.6; 997.40; 6.7; 68.17; 11.1; 1.4; -3.3;eor 426 | 403;20190505;-999;-999;-999; 3; 0.0; 0; 7.517; 0; 2.8; 5.8; 1006.02; 6.3; 64.67; 11.9; -0.3; -4.5;eor 427 | 403;20190506;-999;-999;-999; 3; 0.6; 6; 6.733; 0; 5.0; 7.0; 1007.52; 7.9; 66.29; 13.1; 2.6; -2.2;eor 428 | 403;20190507;-999;-999;-999; 3; 0.0; 0; 8.650; 0; 3.9; 6.7; 1007.55; 8.1; 65.58; 13.8; 2.0; -2.1;eor 429 | 403;20190508;-999;-999;-999; 3; 0.2; 6; 8.700; 0; 5.7; 7.8; 997.95; 11.3; 62.25; 18.7; 0.9; -3.4;eor 430 | 403;20190509;-999;-999;-999; 3; 0.9; 6; 3.783; 0; 6.4; 11.7; 990.49; 13.6; 76.42; 18.0; 9.5; 4.9;eor 431 | 403;20190510;-999;-999;-999; 3; 0.4; 6; 4.400; 0; 6.1; 11.3; 997.68; 12.4; 78.63; 16.9; 6.8; 2.0;eor 432 | 403;20190511;-999;-999;-999; 3; 1.2; 6; 3.250; 0; 6.9; 9.5; 1004.30; 10.7; 75.21; 15.1; 5.4; 0.9;eor 433 | 403;20190512;-999;-999;-999; 3; 0.0; 0; 12.333; 0; 5.0; 6.9; 1017.55; 11.6; 51.96; 16.9; 6.0; -0.8;eor 434 | 403;20190513;-999;-999;-999; 3; 0.0; 0; 10.683; 0; 2.7; 6.5; 1024.62; 10.0; 54.46; 15.8; 3.9; -0.4;eor 435 | 403;20190514;-999;-999;-999; 3; 0.0; 0; 8.933; 0; 3.3; 6.8; 1021.98; 8.9; 60.71; 14.0; 4.8; -1.3;eor 436 | 403;20190515;-999;-999;-999; 3; 3.9; 6; 2.800; 0; 6.0; 6.8; 1015.61; 8.7; 61.04; 13.1; 2.7; -3.1;eor 437 | 403;20190516;-999;-999;-999; 3; 7.9; 6; 0.000; 0; 7.3; 11.4; 1006.23; 9.1; 98.33; 11.4; 6.1; 2.5;eor 438 | 403;20190517;-999;-999;-999; 3; 0.0; 0; 6.567; 0; 5.0; 11.3; 1001.82; 13.4; 75.67; 20.2; 6.1; 3.7;eor 439 | 403;20190518;-999;-999;-999; 3; 0.0; 0; 14.617; 0; 1.5; 11.5; 998.27; 16.8; 65.46; 24.4; 9.3; 4.3;eor 440 | 403;20190519;-999;-999;-999; 3; 6.4; 6; 10.183; 0; 4.0; 14.5; 996.03; 17.8; 74.13; 25.9; 9.7; 5.5;eor 441 | 403;20190520;-999;-999;-999; 3; 11.5; 6; 7.167; 0; 6.3; 16.3; 992.91; 17.6; 83.58; 25.5; 12.6; 9.1;eor 442 | 403;20190521;-999;-999;-999; 3; 1.1; 6; 10.033; 0; 4.7; 14.8; 995.74; 17.4; 76.92; 23.6; 11.3; 7.5;eor 443 | 403;20190522;-999;-999;-999; 3; 0.7; 6; 0.000; 0; 7.8; 13.2; 1003.42; 12.6; 89.96; 15.6; 11.3; 10.9;eor 444 | 403;20190523;-999;-999;-999; 3; 0.0; 0; 11.283; 0; 5.8; 9.7; 1008.22; 13.3; 65.71; 19.3; 7.6; 5.4;eor 445 | 403;20190524;-999;-999;-999; 3; 0.0; 0; 13.267; 0; 6.3; 10.2; 1004.07; 16.8; 57.75; 23.2; 7.5; 4.3;eor 446 | 403;20190525;-999;-999;-999; 3; 0.0; 0; 3.700; 0; 5.4; 10.4; 1005.20; 13.2; 68.75; 15.8; 9.5; 5.3;eor 447 | 403;20190526;-999;-999;-999; 3; 0.0; 0; 6.733; 0; 6.4; 10.8; 1002.44; 15.8; 63.08; 21.0; 7.1; 3.1;eor 448 | 403;20190527;-999;-999;-999; 3; 0.1; 6; 1.800; 0; 7.3; 13.9; 997.62; 17.6; 69.13; 21.2; 14.9; 13.4;eor 449 | 403;20190528;-999;-999;-999; 3; 0.0; 0; 5.050; 0; 6.8; 11.2; 997.48; 15.2; 65.46; 19.0; 9.3; 4.1;eor 450 | 403;20190529;-999;-999;-999; 3; 0.0; 0; 11.633; 0; 4.2; 8.0; 1010.64; 12.1; 58.25; 17.5; 5.9; 1.8;eor 451 | 403;20190530;-999;-999;-999; 3; 0.0; 4; 11.500; 0; 4.4; 9.7; 1013.89; 15.3; 59.46; 23.3; 4.4; 0.6;eor 452 | 403;20190531;-999;-999;-999; 3; 3.1; 6; 6.717; 0; 5.6; 16.3; 1012.97; 18.5; 77.42; 24.2; 12.1; 8.0;eor 453 | 403;20190601;-999;-999;-999; 3; 0.0; 0; 12.700; 0; 4.0; 15.2; 1011.15; 20.3; 68.00; 27.1; 14.0; 10.3;eor 454 | 403;20190602;-999;-999;-999; 3; 0.0; 0; 13.367; 0; 3.1; 15.5; 1007.62; 22.7; 60.25; 31.3; 14.6; 10.1;eor 455 | 403;20190603;-999;-999;-999; 3; 0.0; 6; 11.933; 0; 2.9; 15.3; 1003.78; 24.8; 52.83; 33.2; 15.6; 11.4;eor 456 | 403;20190604;-999;-999;-999; 3; 0.0; 0; 11.550; 0; 2.9; 17.0; 1002.47; 23.6; 61.00; 30.6; 17.2; 13.3;eor 457 | 403;20190605;-999;-999;-999; 3; 0.0; 0; 14.183; 0; 1.3; 17.0; 999.16; 25.7; 56.08; 33.6; 16.0; 12.2;eor 458 | 403;20190606;-999;-999;-999; 3; 5.4; 6; 8.367; 0; 4.8; 19.0; 999.29; 21.0; 78.29; 31.7; 14.5; 14.1;eor 459 | 403;20190607;-999;-999;-999; 3; 0.1; 6; 14.133; 0; 2.5; 15.0; 1004.55; 19.4; 68.92; 25.7; 12.8; 10.1;eor 460 | 403;20190608;-999;-999;-999; 3; 0.0; 6; 8.617; 0; 3.8; 11.9; 1009.54; 17.9; 59.25; 22.6; 10.4; 5.9;eor 461 | 403;20190609;-999;-999;-999; 3; 3.4; 6; 12.450; 0; 4.7; 11.0; 1013.62; 18.8; 53.92; 25.9; 8.7; 4.8;eor 462 | 403;20190610;-999;-999;-999; 3; 1.8; 6; 5.750; 0; 6.8; 17.7; 1003.88; 21.1; 71.96; 27.2; 14.5; 14.0;eor 463 | 403;20190611;-999;-999;-999; 3; 48.0; 6; 11.267; 0; 6.3; 20.2; 1000.25; 23.0; 74.79; 29.1; 16.8; 14.6;eor 464 | 403;20190612;-999;-999;-999; 3; 13.6; 6; 9.650; 0; 5.9; 19.7; 998.63; 22.0; 79.04; 33.0; 16.6; 15.5;eor 465 | 403;20190613;-999;-999;-999; 3; 0.0; 6; 8.900; 0; 3.6; 15.1; 1005.27; 18.9; 72.29; 24.6; 14.7; 12.5;eor 466 | 403;20190614;-999;-999;-999; 3; 0.0; 6; 12.050; 0; 4.1; 14.8; 1007.85; 22.8; 56.33; 29.5; 12.8; 10.1;eor 467 | 403;20190615;-999;-999;-999; 3; 0.0; 0; 10.800; 0; 5.4; 19.7; 1001.65; 24.9; 62.88; 31.5; 17.4; 15.7;eor 468 | 403;20190616;-999;-999;-999; 3; 0.0; 6; 5.800; 0; 6.8; 14.8; 1009.99; 17.9; 72.96; 21.5; 14.0; 11.3;eor 469 | 403;20190617;-999;-999;-999; 3; 0.0; 0; 10.300; 0; 3.2; 15.2; 1011.72; 20.4; 66.13; 27.1; 14.4; 12.0;eor 470 | 403;20190618;-999;-999;-999; 3; 0.0; 0; 15.283; 0; 2.6; 14.9; 1007.27; 22.8; 57.08; 29.4; 14.6; 11.1;eor 471 | 403;20190619;-999;-999;-999; 3; 0.9; 6; 12.767; 0; 5.3; 17.8; 1000.28; 24.3; 60.88; 32.1; 16.6; 12.6;eor 472 | 403;20190620;-999;-999;-999; 3; 1.9; 6; 6.983; 0; 6.0; 19.2; 1000.97; 21.0; 78.21; 25.7; 17.1; 14.2;eor 473 | 403;20190621;-999;-999;-999; 3; 0.0; 0; 10.033; 0; 4.8; 15.5; 1007.42; 19.5; 70.79; 24.7; 14.9; 10.7;eor 474 | 403;20190622;-999;-999;-999; 3; 0.0; 0; 12.417; 0; 2.8; 14.5; 1012.16; 20.1; 63.38; 25.7; 14.2; 9.9;eor 475 | 403;20190623;-999;-999;-999; 3; 0.0; 0; 14.550; 0; 1.4; 13.2; 1012.80; 21.2; 53.63; 27.8; 14.0; 10.0;eor 476 | 403;20190624;-999;-999;-999; 3; 0.0; 0; 15.900; 0; 3.7; 12.4; 1014.22; 22.8; 47.75; 29.7; 14.8; 10.1;eor 477 | 403;20190625;-999;-999;-999; 3; 0.0; 0; 15.367; 0; 4.5; 16.1; 1012.10; 25.5; 51.17; 33.5; 17.5; 12.5;eor 478 | 403;20190626;-999;-999;-999; 3; 0.0; 0; 15.100; 0; 2.0; 19.0; 1009.91; 27.9; 53.67; 36.1; 18.7; 15.1;eor 479 | 403;20190627;-999;-999;-999; 3; 0.0; 0; 14.367; 0; 1.7; 12.5; 1013.56; 19.3; 57.83; 25.3; 14.6; 12.8;eor 480 | 403;20190628;-999;-999;-999; 3; 0.0; 0; 10.550; 0; 3.3; 12.9; 1014.31; 17.9; 64.96; 23.9; 11.7; 8.4;eor 481 | 403;20190629;-999;-999;-999; 3; 0.0; 0; 15.683; 0; 0.6; 13.5; 1010.94; 21.7; 57.00; 30.3; 12.2; 8.4;eor 482 | 403;20190630;-999;-999;-999; 3; 0.0; 6; 15.033; 0; 1.3; 15.6; 1003.23; 27.6; 47.58; 37.6; 14.6; 10.1;eor 483 | 403;20190701;-999;-999;-999; 3; 0.0; 6; 9.867; 0; 4.2; 14.4; 1004.59; 22.3; 53.58; 28.0; 16.7; 15.1;eor 484 | 403;20190702;-999;-999;-999; 3; 0.0; 0; 10.300; 0; 3.0; 11.9; 1009.22; 17.5; 60.29; 21.5; 12.5; 9.4;eor 485 | 403;20190703;-999;-999;-999; 3; 0.0; 0; 8.500; 0; 3.8; 9.3; 1012.62; 15.3; 54.96; 20.0; 9.8; 6.1;eor 486 | 403;20190704;-999;-999;-999; 3; 0.0; 6; 12.017; 0; 4.1; 9.7; 1011.53; 16.6; 53.00; 22.7; 9.5; 6.7;eor 487 | 403;20190705;-999;-999;-999; 3; 0.0; 6; 0.067; 0; 7.3; 12.6; 1004.56; 18.4; 59.50; 20.8; 13.9; 10.4;eor 488 | 403;20190706;-999;-999;-999; 3; 7.1; 6; 1.417; 0; 7.3; 14.9; 999.54; 17.4; 76.67; 23.3; 12.9; 10.3;eor 489 | 403;20190707;-999;-999;-999; 3; 0.0; 6; 3.150; 0; 6.4; 10.1; 1001.02; 14.8; 61.42; 18.8; 11.3; 9.3;eor 490 | 403;20190708;-999;-999;-999; 3; 0.2; 6; 2.267; 0; 6.6; 10.6; 1005.25; 14.1; 65.71; 17.6; 11.2; 9.1;eor 491 | 403;20190709;-999;-999;-999; 3; 0.0; 0; 4.933; 0; 4.6; 11.1; 1007.14; 14.3; 68.63; 18.3; 9.8; 7.7;eor 492 | 403;20190710;-999;-999;-999; 3; 0.0; 6; 9.767; 0; 4.3; 11.6; 1007.16; 16.0; 66.08; 22.1; 10.0; 8.3;eor 493 | 403;20190711;-999;-999;-999; 3; 1.2; 6; 9.250; 0; 5.1; 12.2; 1003.49; 18.0; 62.58; 23.6; 9.1; 6.6;eor 494 | 403;20190712;-999;-999;-999; 3; 0.5; 6; 1.367; 0; 6.7; 17.1; 1000.59; 17.9; 84.38; 21.6; 14.9; 12.4;eor 495 | 403;20190713;-999;-999;-999; 3; 2.5; 6; 7.283; 0; 5.8; 16.0; 1002.33; 18.6; 77.83; 26.3; 14.9; 13.9;eor 496 | 403;20190714;-999;-999;-999; 3; 0.0; 0; 2.917; 0; 6.0; 15.3; 1006.65; 16.6; 81.96; 20.2; 14.5; 11.3;eor 497 | 403;20190715;-999;-999;-999; 3; 0.0; 6; 0.267; 0; 7.4; 12.6; 1006.81; 15.3; 72.96; 17.4; 13.0; 12.1;eor 498 | 403;20190716;-999;-999;-999; 3; 0.0; 0; 3.233; 0; 6.0; 13.6; 1004.67; 16.5; 73.04; 20.7; 12.7; 12.3;eor 499 | 403;20190717;-999;-999;-999; 3; 0.0; 0; 8.333; 0; 3.7; 13.2; 1004.63; 16.7; 72.17; 23.2; 11.3; 8.9;eor 500 | 403;20190718;-999;-999;-999; 3; 0.0; 0; 11.350; 0; 3.4; 12.8; 1002.78; 19.9; 58.54; 26.7; 11.6; 8.4;eor 501 | 403;20190719;-999;-999;-999; 3; 0.0; 6; 2.933; 0; 6.6; 16.1; 1003.48; 20.3; 68.54; 24.5; 14.8; 12.6;eor 502 | 403;20190720;-999;-999;-999; 3; 19.1; 6; 10.950; 0; 5.7; 16.2; 1004.38; 22.2; 66.46; 30.8; 13.6; 11.0;eor 503 | 403;20190721;-999;-999;-999; 3; 0.0; 0; 9.750; 0; 4.1; 16.8; 1008.19; 20.6; 71.79; 25.9; 16.1; 14.0;eor 504 | 403;20190722;-999;-999;-999; 3; 0.0; 6; 4.350; 0; 7.0; 16.0; 1012.82; 19.8; 70.46; 24.4; 14.0; 12.3;eor 505 | 403;20190723;-999;-999;-999; 3; 0.0; 0; 15.267; 0; 0.8; 17.9; 1011.23; 23.1; 66.13; 29.9; 15.9; 14.2;eor 506 | 403;20190724;-999;-999;-999; 3; 0.0; 0; 15.317; 0; 1.6; 16.7; 1008.63; 24.4; 59.17; 32.0; 16.1; 13.6;eor 507 | 403;20190725;-999;-999;-999; 3; 0.0; 0; 14.800; 0; 1.6; 17.5; 1008.12; 25.7; 56.58; 32.9; 17.2; 14.2;eor 508 | 403;20190726;-999;-999;-999; 3; 0.0; 0; 15.033; 0; 0.8; 15.8; 1004.05; 24.6; 53.63; 30.7; 18.8; 16.3;eor 509 | 403;20190727;-999;-999;-999; 3; 0.0; 0; 12.183; 0; 1.9; 15.9; 997.45; 23.3; 56.42; 28.4; 18.9; 16.5;eor 510 | 403;20190728;-999;-999;-999; 3; 0.0; 0; 12.117; 0; 4.4; 18.8; 993.27; 24.5; 62.42; 30.7; 17.8; 16.7;eor 511 | 403;20190729;-999;-999;-999; 3; 1.1; 6; 5.717; 0; 6.0; 21.6; 997.74; 24.9; 71.58; 33.3; 20.3; 19.2;eor 512 | 403;20190730;-999;-999;-999; 3; 0.0; 0; 2.900; 0; 6.6; 22.3; 1001.30; 21.9; 85.88; 26.0; 18.5; 15.4;eor 513 | 403;20190731;-999;-999;-999; 3; 23.2; 6; 3.100; 0; 5.3; 19.4; 1004.95; 19.2; 88.21; 23.3; 15.0; 13.4;eor 514 | 403;20190801;-999;-999;-999; 3; 0.3; 6; 6.033; 0; 5.1; 16.3; 1006.85; 18.7; 78.33; 24.4; 14.2; 12.6;eor 515 | 403;20190802;-999;-999;-999; 3; 8.5; 6; 7.250; 0; 3.5; 16.6; 1005.06; 17.5; 85.75; 25.3; 13.0; 11.4;eor 516 | 403;20190803;-999;-999;-999; 3; 0.0; 6; 10.633; 0; 4.8; 14.8; 1004.75; 19.0; 70.75; 25.6; 14.4; 12.7;eor 517 | 403;20190804;-999;-999;-999; 3; 0.0; 0; 7.117; 0; 4.3; 15.2; 1005.95; 18.4; 74.17; 23.9; 13.3; 11.4;eor 518 | 403;20190805;-999;-999;-999; 3; 0.0; 6; 4.600; 0; 6.0; 15.7; 1002.33; 19.3; 72.46; 24.3; 12.2; 10.6;eor 519 | 403;20190806;-999;-999;-999; 3; 1.0; 6; 7.767; 0; 5.8; 18.2; 999.85; 21.0; 75.79; 28.3; 15.5; 12.9;eor 520 | 403;20190807;-999;-999;-999; 1; 5.5; 6; 3.950; 0; 6.6; 18.6; 997.17; 20.1; 79.92; 25.3; 16.0; 14.1;eor 521 | 403;20190808;-999;-999;-999; 1; 0.0; 0; 11.650; 0; 2.4; 14.4; 1000.55; 20.0; 65.38; 26.1; 13.7; 11.8;eor 522 | 403;20190809;-999;-999;-999; 1; 0.0; 6; 10.433; 0; 5.1; 15.1; 1002.22; 20.9; 64.58; 27.5; 12.2; 10.6;eor 523 | 403;20190810;-999;-999;-999; 1; 0.0; 0; 7.300; 0; 5.3; 17.2; 1001.03; 23.2; 60.71; 28.1; 18.5; 14.7;eor 524 | 403;20190811;-999;-999;-999; 1; 0.0; 6; 10.083; 0; 3.9; 14.6; 1004.74; 22.0; 57.75; 28.6; 14.8; 11.8;eor 525 | 403;20190812;-999;-999;-999; 1; 0.0; 0; 4.583; 0; 6.5; 14.6; 1004.41; 19.9; 63.38; 22.9; 16.1; 14.0;eor 526 | 403;20190813;-999;-999;-999; 1; 0.0; 6; 9.917; 0; 4.4; 12.4; 1005.48; 17.6; 62.67; 22.1; 11.5; 8.4;eor 527 | 403;20190814;-999;-999;-999; 1; 0.0; 0; 11.750; 0; 2.8; 10.9; 1007.35; 16.0; 62.54; 22.0; 10.4; 7.5;eor 528 | 403;20190815;-999;-999;-999; 1; 0.1; 6; 1.933; 0; 6.3; 13.2; 1003.05; 17.3; 67.83; 22.6; 9.7; 7.0;eor 529 | 403;20190816;-999;-999;-999; 1; 0.0; 0; 5.567; 0; 4.8; 14.9; 1005.48; 17.6; 75.75; 23.2; 12.4; 9.9;eor 530 | 403;20190817;-999;-999;-999; 1; 0.3; 6; 3.500; 0; 6.8; 13.9; 1001.30; 19.6; 63.54; 27.7; 11.9; 9.4;eor 531 | 403;20190818;-999;-999;-999; 1; 10.4; 6; 2.467; 0; 6.6; 19.8; 998.15; 19.8; 86.96; 26.5; 16.6; 14.8;eor 532 | 403;20190819;-999;-999;-999; 1; 0.0; 0; 9.117; 0; 4.6; 14.7; 1006.00; 18.1; 74.21; 23.8; 12.4; 10.7;eor 533 | 403;20190820;-999;-999;-999; 1; 0.5; 6; 6.083; 0; 6.7; 12.9; 1011.89; 18.1; 66.25; 24.2; 10.7; 9.1;eor 534 | 403;20190821;-999;-999;-999; 1; 0.0; 0; 11.783; 0; 2.7; 12.8; 1017.38; 17.0; 68.92; 23.1; 11.1; 9.5;eor 535 | 403;20190822;-999;-999;-999; 1; 0.0; 0; 12.600; 0; 1.8; 12.6; 1017.57; 17.9; 66.50; 26.3; 9.4; 7.4;eor 536 | 403;20190823;-999;-999;-999; 1; 0.0; 0; 13.217; 0; 1.1; 14.0; 1016.43; 19.5; 66.71; 28.0; 11.3; 9.0;eor 537 | 403;20190824;-999;-999;-999; 1; 0.0; 0; 11.683; 0; 1.3; 15.1; 1014.02; 21.2; 63.33; 29.1; 12.6; 10.2;eor 538 | 403;20190825;-999;-999;-999; 1; 0.0; 6; 11.500; 0; 1.8; 16.5; 1011.52; 24.2; 55.42; 31.2; 18.7; 15.9;eor 539 | 403;20190826;-999;-999;-999; 1; 1.6; 6; 6.517; 0; 4.3; 19.0; 1010.32; 23.0; 70.33; 31.7; 16.8; 14.0;eor 540 | 403;20190827;-999;-999;-999; 1; 0.0; 0; 9.967; 0; 3.2; 19.9; 1008.05; 23.8; 71.83; 31.4; 17.2; 15.8;eor 541 | 403;20190828;-999;-999;-999; 1; 0.0; 6; 8.233; 0; 3.7; 19.4; 1005.25; 24.3; 67.67; 33.4; 17.7; 15.4;eor 542 | 403;20190829;-999;-999;-999; 1; 0.0; 0; 11.567; 0; 4.5; 18.1; 1007.68; 23.4; 65.83; 30.0; 16.3; 14.1;eor 543 | 403;20190830;-999;-999;-999; 1; 0.0; 0; 9.267; 0; 3.8; 19.6; 1011.90; 24.1; 66.71; 29.9; 19.5; 16.7;eor 544 | 403;20190831;-999;-999;-999; 1; 0.0; 0; 11.700; 0; 0.7; 19.1; 1005.96; 25.3; 63.00; 33.4; 18.0; 15.7;eor 545 | 403;20190901;-999;-999;-999; 1; 0.0; 0; 8.383; 0; 3.9; 17.9; 1001.13; 22.4; 67.04; 29.6; 16.2; 15.2;eor 546 | 403;20190902;-999;-999;-999; 1; 0.0; 0; 9.817; 0; 2.2; 11.7; 1010.77; 16.1; 66.21; 21.6; 9.9; 7.1;eor 547 | 403;20190903;-999;-999;-999; 1; 0.0; 6; 2.767; 0; 4.4; 11.8; 1012.47; 15.2; 70.71; 20.9; 8.1; 5.7;eor 548 | 403;20190904;-999;-999;-999; 1; 0.3; 6; 10.283; 0; 4.5; 13.5; 1006.13; 19.1; 64.75; 26.7; 13.0; 10.2;eor 549 | 403;20190905;-999;-999;-999; 1; 0.0; 4; 6.833; 0; 4.3; 12.6; 1005.93; 17.0; 66.17; 21.8; 11.8; 10.2;eor 550 | 403;20190906;-999;-999;-999; 1; 0.0; 0; 11.700; 0; 1.4; 10.0; 975.44; 13.5; 67.54; 20.5; 7.9; 4.9;eor 551 | 403;20190907;-999;-999;-999; 1; 0.0; 6; 2.750; 0; 6.1; 11.1; 1008.67; 13.3; 75.33; 20.0; 6.4; 3.9;eor 552 | -------------------------------------------------------------------------------- /plots/2019_09/README.md: -------------------------------------------------------------------------------- 1 | ### September 2019 - Visualizing Uncertainty 2 | Berlin maximum daily temperatures via [DWD (Deutscher Wetterdienst)](https://www.dwd.de/DE/leistungen/klimadatendeutschland/klarchivtagmonat.html)

3 | ![./plots/2019-09/SWD_2019-09_Uncertainty.png](https://github.com/Z3tt/SWDchallenge/blob/master/plots/2019_09/SWD_2019_09_Uncertainty.png)

4 | The last 365 days:
5 | ![./plots/2019-09/SWD_2019-09_Uncertainty_365.png](https://github.com/Z3tt/SWDchallenge/blob/master/plots/2019_09/SWD_2019_09_Uncertainty_365.png)

6 | German version:
7 | ![./plots/2019-09/SWD_2019-09_Uncertainty_ger.png](https://github.com/Z3tt/SWDchallenge/blob/master/plots/2019_09/SWD_2019_09_Uncertainty_ger.png)

8 | -------------------------------------------------------------------------------- /plots/2019_09/SWD_2019_09_Uncertainty.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2019_09/SWD_2019_09_Uncertainty.png -------------------------------------------------------------------------------- /plots/2019_09/SWD_2019_09_Uncertainty_365.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2019_09/SWD_2019_09_Uncertainty_365.png -------------------------------------------------------------------------------- /plots/2019_09/SWD_2019_09_Uncertainty_98-08-18.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2019_09/SWD_2019_09_Uncertainty_98-08-18.png -------------------------------------------------------------------------------- /plots/2019_09/SWD_2019_09_Uncertainty_Fahrenheit.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2019_09/SWD_2019_09_Uncertainty_Fahrenheit.png -------------------------------------------------------------------------------- /plots/2019_09/SWD_2019_09_Uncertainty_decades.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2019_09/SWD_2019_09_Uncertainty_decades.png -------------------------------------------------------------------------------- /plots/2019_09/SWD_2019_09_Uncertainty_ger.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2019_09/SWD_2019_09_Uncertainty_ger.png -------------------------------------------------------------------------------- /plots/2020_01/README.md: -------------------------------------------------------------------------------- 1 | ### January 2020 - Small Multiples 2 | ![./plots/2020_01/SWD_2020_01_SmallMultiples_grey.png](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2020_01/SWD_2020_01_SmallMultiples_grey.png)

3 | Version with colored annotations:
4 | ![./plots/2020_01/SWD_2020_01_SmallMultiples_color.png](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2020_01/SWD_2020_01_SmallMultiples_color.png)

5 | -------------------------------------------------------------------------------- /plots/2020_01/SWD_2020_01_SmallMultiples_color.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2020_01/SWD_2020_01_SmallMultiples_color.png -------------------------------------------------------------------------------- /plots/2020_01/SWD_2020_01_SmallMultiples_grey.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2020_01/SWD_2020_01_SmallMultiples_grey.png -------------------------------------------------------------------------------- /plots/2020_03/README.md: -------------------------------------------------------------------------------- 1 | ### March 2020 - Get Animated! 2 | ![./plots/2020_03/corona_begin.mp4](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2020_03/corona_begin.gif)

3 | Version with dynamic sorting based on overall death toll:
4 | ![./plots/2020_03/corona_sum.mp4](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2020_03/corona_begin.gif)

5 | Static images:
6 | ![./plots/2020_03/corona_sum.mp4](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2020_03/corona_begin_latest_hq.png)
7 | ![./plots/2020_03/corona_sum.mp4](https://raw.githubusercontent.com/Z3tt/SWDchallenge/master/plots/2020_03/corona_sum_latest_hq.png) 8 | -------------------------------------------------------------------------------- /plots/2020_03/corona_begin.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2020_03/corona_begin.gif -------------------------------------------------------------------------------- /plots/2020_03/corona_begin.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2020_03/corona_begin.mp4 -------------------------------------------------------------------------------- /plots/2020_03/corona_begin_latest_hq.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2020_03/corona_begin_latest_hq.png -------------------------------------------------------------------------------- /plots/2020_03/corona_sum.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2020_03/corona_sum.gif -------------------------------------------------------------------------------- /plots/2020_03/corona_sum.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2020_03/corona_sum.mp4 -------------------------------------------------------------------------------- /plots/2020_03/corona_sum_latest_hq.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/z3tt/SWDchallenge/994e7503a886ed2bbe2d09435636ca8fa3174dcd/plots/2020_03/corona_sum_latest_hq.png --------------------------------------------------------------------------------