├── img └── README.md ├── requirements.local.sh ├── README.md ├── countries ├── countries.sql ├── economies2015.csv ├── economies2010.csv ├── countries_plus.csv ├── cities.csv ├── currencies.csv ├── populations.csv ├── countries.csv ├── economies.csv └── languages.csv ├── audition.ipynb └── .ipynb_checkpoints └── audition-checkpoint.ipynb /img/README.md: -------------------------------------------------------------------------------- 1 | Store your images in this folder. 2 | -------------------------------------------------------------------------------- /requirements.local.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | # If bash command fails, build should error out 4 | set -e 5 | 6 | cd countries 7 | 8 | # Create countries database 9 | createdb -U postgres countries 10 | 11 | # Seed the countries database 12 | psql -U postgres countries < countries.sql 13 | 14 | cd .. 15 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # projects-instructor-application-sql 2 | The audition portion of the application process for becoming a project instructor 3 | 4 | See this [Intercom article](https://instructor-support.datacamp.com/projects/the-application-process-for-becoming-a-project-instructor) for a full description. 5 | 6 | # Things to install 7 | 8 | There are some packages you need to be able to create DataCamp projects locally. Run the following commands in a terminal to install them. 9 | 10 | *You might need to change pip into pip3 depending on how you installed Python.* 11 | 12 | ``` 13 | pip install ipython-sql 14 | ``` 15 | -------------------------------------------------------------------------------- /countries/countries.sql: -------------------------------------------------------------------------------- 1 | CREATE TABLE cities ( 2 | name VARCHAR PRIMARY KEY, 3 | country_code VARCHAR, 4 | city_proper_pop REAL, 5 | metroarea_pop REAL, 6 | urbanarea_pop REAL 7 | ); 8 | 9 | CREATE TABLE countries ( 10 | code VARCHAR PRIMARY KEY, 11 | name VARCHAR, 12 | continent VARCHAR, 13 | region VARCHAR, 14 | surface_area REAL, 15 | indep_year INTEGER, 16 | local_name VARCHAR, 17 | gov_form VARCHAR, 18 | capital VARCHAR, 19 | cap_long REAL, 20 | cap_lat REAL 21 | ); 22 | 23 | CREATE TABLE languages ( 24 | lang_id INTEGER PRIMARY KEY, 25 | code VARCHAR, 26 | name VARCHAR, 27 | percent REAL, 28 | official BOOLEAN 29 | ); 30 | 31 | CREATE TABLE economies ( 32 | econ_id INTEGER PRIMARY KEY, 33 | code VARCHAR, 34 | year INTEGER, 35 | income_group VARCHAR, 36 | gdp_percapita REAL, 37 | gross_savings REAL, 38 | inflation_rate REAL, 39 | total_investment REAL, 40 | unemployment_rate REAL, 41 | exports REAL, 42 | imports REAL 43 | ); 44 | 45 | CREATE TABLE currencies ( 46 | curr_id INTEGER PRIMARY KEY, 47 | code VARCHAR, 48 | basic_unit VARCHAR, 49 | curr_code VARCHAR, 50 | frac_unit VARCHAR, 51 | frac_perbasic REAL 52 | ); 53 | 54 | CREATE TABLE populations ( 55 | pop_id INTEGER PRIMARY KEY, 56 | country_code VARCHAR, 57 | year INTEGER, 58 | fertility_rate REAL, 59 | life_expectancy REAL, 60 | size REAL 61 | ); 62 | 63 | 64 | CREATE TABLE countries_plus ( 65 | name VARCHAR, 66 | continent VARCHAR, 67 | code VARCHAR PRIMARY KEY, 68 | surface_area REAL, 69 | geosize_group VARCHAR 70 | ); 71 | 72 | CREATE TABLE economies2010 ( 73 | code VARCHAR PRIMARY KEY, 74 | year INTEGER, 75 | income_group VARCHAR, 76 | gross_savings REAL 77 | ); 78 | 79 | CREATE TABLE economies2015 ( 80 | code VARCHAR PRIMARY KEY, 81 | year INTEGER, 82 | income_group VARCHAR, 83 | gross_savings REAL 84 | ); 85 | 86 | -- Copy over data from CSVs 87 | \copy cities FROM 'cities.csv' DELIMITER ',' CSV HEADER; 88 | \copy countries FROM 'countries.csv' DELIMITER ',' CSV HEADER; 89 | \copy languages FROM 'languages.csv' DELIMITER ',' CSV HEADER; 90 | \copy economies FROM 'economies.csv' DELIMITER ',' CSV HEADER; 91 | \copy economies2010 FROM 'economies2010.csv' DELIMITER ',' CSV HEADER; 92 | \copy economies2015 FROM 'economies2015.csv' DELIMITER ',' CSV HEADER; 93 | \copy currencies FROM 'currencies.csv' DELIMITER ',' CSV HEADER; 94 | \copy populations FROM 'populations.csv' DELIMITER ',' CSV HEADER; 95 | \copy countries_plus FROM 'countries_plus.csv' DELIMITER ',' CSV HEADER; 96 | 97 | /* 98 | createdb countries 99 | psql countries < data/countries/code/countries.sql 100 | */ -------------------------------------------------------------------------------- /countries/economies2015.csv: -------------------------------------------------------------------------------- 1 | "code","year","income_group","gross_savings" 2 | "AFG",2015,"Low income",21.466 3 | "AGO",2015,"Upper middle income",-0.425 4 | "ALB",2015,"Upper middle income",13.84 5 | "ARE",2015,"High income",34.106 6 | "ARG",2015,"Upper middle income",14.111 7 | "ARM",2015,"Lower middle income",18.306 8 | "ATG",2015,"High income",18.754 9 | "AUS",2015,"High income",22.111 10 | "AUT",2015,"High income",25.353 11 | "AZE",2015,"Upper middle income",26.4 12 | "BDI",2015,"Low income",-11.014 13 | "BEL",2015,"High income",23.653 14 | "BEN",2015,"Low income",17.567 15 | "BFA",2015,"Low income",5.31 16 | "BGD",2015,"Lower middle income",29.707 17 | "BGR",2015,"Upper middle income",21.056 18 | "BHR",2015,"High income",21.955 19 | "BHS",2015,"High income",11.243 20 | "BIH",2015,"Upper middle income",10.217 21 | "BLR",2015,"Upper middle income",25.419 22 | "BLZ",2015,"Upper middle income",12.155 23 | "BOL",2015,"Lower middle income",13.31 24 | "BRA",2015,"Upper middle income",15.865 25 | "BRB",2015,"High income",7.473 26 | "BRN",2015,"High income", 27 | "BTN",2015,"Lower middle income",32.024 28 | "BWA",2015,"Upper middle income",40.026 29 | "CAF",2015,"Low income",4.882 30 | "CAN",2015,"High income",20.416 31 | "CHE",2015,"High income",34.52 32 | "CHL",2015,"High income",21.306 33 | "CHN",2015,"Upper middle income",47.457 34 | "CIV",2015,"Lower middle income",16.82 35 | "CMR",2015,"Lower middle income",17.088 36 | "COD",2015,"Low income",16.495 37 | "COG",2015,"Lower middle income",-8.049 38 | "COL",2015,"Upper middle income",20.23 39 | "COM",2015,"Low income",19.221 40 | "CPV",2015,"Lower middle income",37.094 41 | "CRI",2015,"Upper middle income",15.725 42 | "CYP",2015,"High income",11.55 43 | "CZE",2015,"High income",28.266 44 | "DEU",2015,"High income",27.571 45 | "DJI",2015,"Lower middle income",19.039 46 | "DMA",2015,"Upper middle income",8.814 47 | "DNK",2015,"High income",28.91 48 | "DOM",2015,"Upper middle income",21.447 49 | "DZA",2015,"Upper middle income",34.738 50 | "ECU",2015,"Upper middle income",24.657 51 | "EGY",2015,"Lower middle income",10.62 52 | "ERI",2015,"Low income",1.329 53 | "ESP",2015,"High income",21.429 54 | "EST",2015,"High income",25.422 55 | "ETH",2015,"Low income",31.269 56 | "FIN",2015,"High income",20.728 57 | "FJI",2015,"Upper middle income", 58 | "FRA",2015,"High income",22.163 59 | "FSM",2015,"Lower middle income", 60 | "GAB",2015,"Upper middle income",29.315 61 | "GBR",2015,"High income",12.952 62 | "GEO",2015,"Upper middle income",20.136 63 | "GHA",2015,"Lower middle income",17.146 64 | "GIN",2015,"Low income",-9.697 65 | "GMB",2015,"Low income",4.687 66 | "GNB",2015,"Low income",9.374 67 | "GNQ",2015,"Upper middle income",54.939 68 | "GRC",2015,"High income",9.783 69 | "GRD",2015,"Upper middle income",0.231 70 | "GTM",2015,"Lower middle income",13.115 71 | "GUY",2015,"Upper middle income",8.214 72 | "HKG",2015,"High income",24.858 73 | "HND",2015,"Lower middle income",18.403 74 | "HRV",2015,"High income",23.894 75 | "HTI",2015,"Low income",29.277 76 | "HUN",2015,"High income",25.102 77 | "IDN",2015,"Lower middle income",32.14 78 | "IND",2015,"Lower middle income",31.689 79 | "IRL",2015,"High income",31.998 80 | "IRN",2015,"Upper middle income",34.511 81 | "IRQ",2015,"Upper middle income",17.971 82 | "ISL",2015,"High income",24.552 83 | "ISR",2015,"High income",24.296 84 | "ITA",2015,"High income",18.934 85 | "JAM",2015,"Upper middle income",12.111 86 | "JOR",2015,"Upper middle income",10.146 87 | "JPN",2015,"High income",26.99 88 | "KAZ",2015,"Upper middle income",26.533 89 | "KEN",2015,"Lower middle income",14.392 90 | "KGZ",2015,"Lower middle income",18.333 91 | "KHM",2015,"Lower middle income",11.798 92 | "KIR",2015,"Lower middle income", 93 | "KNA",2015,"High income",17.742 94 | "KOR",2015,"High income",36.58 95 | "KWT",2015,"High income",31.649 96 | "LAO",2015,"Lower middle income", 97 | "LBN",2015,"Upper middle income",3.82 98 | "LBR",2015,"Low income", 99 | "LBY",2015,"Upper middle income", 100 | "LCA",2015,"Upper middle income",17.103 101 | "LKA",2015,"Lower middle income",27.586 102 | "LSO",2015,"Lower middle income",30.116 103 | "LTU",2015,"High income",17.555 104 | "LUX",2015,"High income",24.865 105 | "LVA",2015,"High income",21.325 106 | "MAC",2015,"High income", 107 | "MAR",2015,"Lower middle income",28.079 108 | "MDA",2015,"Lower middle income",17.961 109 | "MDG",2015,"Low income",11.15 110 | "MDV",2015,"Upper middle income",9.798 111 | "MEX",2015,"Upper middle income",20.019 112 | "MHL",2015,"Upper middle income", 113 | "MKD",2015,"Upper middle income",29.029 114 | "MLI",2015,"Low income",10.118 115 | "MLT",2015,"High income",29.024 116 | "MMR",2015,"Lower middle income",19.313 117 | "MNE",2015,"Upper middle income",6.702 118 | "MNG",2015,"Lower middle income",21.122 119 | "MOZ",2015,"Low income",14.228 120 | "MRT",2015,"Lower middle income",18.915 121 | "MUS",2015,"Upper middle income",16.312 122 | "MWI",2015,"Low income",2.676 123 | "MYS",2015,"Upper middle income",28.087 124 | "NAM",2015,"Upper middle income",20.514 125 | "NER",2015,"Low income",24.479 126 | "NGA",2015,"Lower middle income",12.298 127 | "NIC",2015,"Lower middle income",23.627 128 | "NLD",2015,"High income",27.854 129 | "NOR",2015,"High income",36.88 130 | "NPL",2015,"Low income",43.787 131 | "NRU",2015,"High income", 132 | "NZL",2015,"High income",20.123 133 | "OMN",2015,"High income",18.347 134 | "PAK",2015,"Lower middle income",14.48 135 | "PAN",2015,"Upper middle income",39.271 136 | "PER",2015,"Upper middle income",19.703 137 | "PHL",2015,"Lower middle income",23.036 138 | "PLW",2015,"Upper middle income", 139 | "PNG",2015,"Lower middle income", 140 | "POL",2015,"High income",19.832 141 | "PRI",2015,"High income", 142 | "PRT",2015,"High income",15.521 143 | "PRY",2015,"Upper middle income",15.781 144 | "QAT",2015,"High income",46.556 145 | "ROU",2015,"Upper middle income",23.747 146 | "RUS",2015,"Upper middle income",27.175 147 | "RWA",2015,"Low income",8.687 148 | "SAU",2015,"High income",26.174 149 | "SDN",2015,"Lower middle income",9.263 150 | "SEN",2015,"Low income",16.576 151 | "SGP",2015,"High income",44.88 152 | "SLB",2015,"Lower middle income",17.332 153 | "SLE",2015,"Low income",0.947 154 | "SLV",2015,"Lower middle income",10.425 155 | "SMR",2015,"High income", 156 | "SRB",2015,"Upper middle income",14.141 157 | "SSD",2015,"Low income",7.304 158 | "STP",2015,"Lower middle income",19.363 159 | "SUR",2015,"Upper middle income",50.155 160 | "SVK",2015,"High income",23.415 161 | "SVN",2015,"High income",25.243 162 | "SWE",2015,"High income",28.902 163 | "SWZ",2015,"Lower middle income",22.994 164 | "SYC",2015,"High income",15.005 165 | "SYR",2015,"Lower middle income", 166 | "TCD",2015,"Low income",14.605 167 | "TGO",2015,"Low income",15.912 168 | "THA",2015,"Upper middle income",30.301 169 | "TJK",2015,"Lower middle income",12.495 170 | "TKM",2015,"Upper middle income", 171 | "TLS",2015,"Lower middle income", 172 | "TON",2015,"Lower middle income", 173 | "TTO",2015,"High income",11.131 174 | "TUN",2015,"Lower middle income",12.528 175 | "TUR",2015,"Upper middle income",24.743 176 | "TUV",2015,"Upper middle income", 177 | "TZA",2015,"Low income",24.079 178 | "UGA",2015,"Low income",17.888 179 | "UKR",2015,"Lower middle income",15.657 180 | "URY",2015,"High income",17.713 181 | "USA",2015,"High income",19.107 182 | "UZB",2015,"Lower middle income",30.29 183 | "VCT",2015,"Upper middle income",2.483 184 | "VEN",2015,"Upper middle income",31.787 185 | "VNM",2015,"Lower middle income",28.055 186 | "VUT",2015,"Lower middle income", 187 | "WSM",2015,"Lower middle income", 188 | "YEM",2015,"Lower middle income",-3.715 189 | "ZAF",2015,"Upper middle income",16.46 190 | "ZMB",2015,"Lower middle income",39.177 191 | "ZWE",2015,"Low income",5.563 192 | -------------------------------------------------------------------------------- /countries/economies2010.csv: -------------------------------------------------------------------------------- 1 | "code","year","income_group","gross_savings" 2 | "AFG",2010,"Low income",37.133 3 | "AGO",2010,"Upper middle income",23.534 4 | "ALB",2010,"Upper middle income",20.011 5 | "ARE",2010,"High income",27.073 6 | "ARG",2010,"Upper middle income",17.361 7 | "ARM",2010,"Lower middle income",15.797 8 | "ATG",2010,"High income",13.398 9 | "AUS",2010,"High income",23.584 10 | "AUT",2010,"High income",25.521 11 | "AZE",2010,"Upper middle income",46.567 12 | "BDI",2010,"Low income",3.723 13 | "BEL",2010,"High income",24.456 14 | "BEN",2010,"Low income",14.905 15 | "BFA",2010,"Low income",15.788 16 | "BGD",2010,"Lower middle income",29.141 17 | "BGR",2010,"Upper middle income",20.845 18 | "BHR",2010,"High income",36.206 19 | "BHS",2010,"High income",15.141 20 | "BIH",2010,"Upper middle income",10.115 21 | "BLR",2010,"Upper middle income",26.186 22 | "BLZ",2010,"Upper middle income",10.33 23 | "BOL",2010,"Lower middle income",24.969 24 | "BRA",2010,"Upper middle income",18.368 25 | "BRB",2010,"High income",8.12 26 | "BRN",2010,"High income", 27 | "BTN",2010,"Lower middle income",44.674 28 | "BWA",2010,"Upper middle income",32.162 29 | "CAF",2010,"Low income",4.115 30 | "CAN",2010,"High income",19.898 31 | "CHE",2010,"High income",38.881 32 | "CHL",2010,"High income",24.839 33 | "CHN",2010,"Upper middle income",51.802 34 | "CIV",2010,"Lower middle income",16.765 35 | "CMR",2010,"Lower middle income",17.524 36 | "COD",2010,"Low income",15.574 37 | "COG",2010,"Lower middle income",27.651 38 | "COL",2010,"Upper middle income",19.107 39 | "COM",2010,"Low income",15.22 40 | "CPV",2010,"Lower middle income",25.257 41 | "CRI",2010,"Upper middle income",16.489 42 | "CYP",2010,"High income",12.507 43 | "CZE",2010,"High income",23.588 44 | "DEU",2010,"High income",25.241 45 | "DJI",2010,"Lower middle income",24.089 46 | "DMA",2010,"Upper middle income",2.462 47 | "DNK",2010,"High income",24.639 48 | "DOM",2010,"Upper middle income",18.745 49 | "DZA",2010,"Upper middle income",49.869 50 | "ECU",2010,"Upper middle income",25.757 51 | "EGY",2010,"Lower middle income",19.421 52 | "ERI",2010,"Low income",-9.257 53 | "ESP",2010,"High income",19.628 54 | "EST",2010,"High income",23.087 55 | "ETH",2010,"Low income",24.494 56 | "FIN",2010,"High income",22.843 57 | "FJI",2010,"Upper middle income", 58 | "FRA",2010,"High income",21.075 59 | "FSM",2010,"Lower middle income", 60 | "GAB",2010,"Upper middle income",41.009 61 | "GBR",2010,"High income",13.233 62 | "GEO",2010,"Upper middle income",11.64 63 | "GHA",2010,"Lower middle income",17.276 64 | "GIN",2010,"Low income",0.135 65 | "GMB",2010,"Low income",5.026 66 | "GNB",2010,"Low income",-2.057 67 | "GNQ",2010,"Upper middle income",41.231 68 | "GRC",2010,"High income",5.664 69 | "GRD",2010,"Upper middle income",-1.702 70 | "GTM",2010,"Lower middle income",12.575 71 | "GUY",2010,"Upper middle income",7.88 72 | "HKG",2010,"High income",30.892 73 | "HND",2010,"Lower middle income",17.547 74 | "HRV",2010,"High income",20.278 75 | "HTI",2010,"Low income",23.869 76 | "HUN",2010,"High income",20.992 77 | "IDN",2010,"Lower middle income",33.582 78 | "IND",2010,"Lower middle income",33.689 79 | "IRL",2010,"High income",16.039 80 | "IRN",2010,"Upper middle income",41.522 81 | "IRQ",2010,"Upper middle income",23.736 82 | "ISL",2010,"High income",7.256 83 | "ISR",2010,"High income",22.064 84 | "ITA",2010,"High income",17.121 85 | "JAM",2010,"Upper middle income",13.41 86 | "JOR",2010,"Upper middle income",18.381 87 | "JPN",2010,"High income",25.174 88 | "KAZ",2010,"Upper middle income",26.309 89 | "KEN",2010,"Lower middle income",14.809 90 | "KGZ",2010,"Lower middle income",24.869 91 | "KHM",2010,"Lower middle income",10.521 92 | "KIR",2010,"Lower middle income", 93 | "KNA",2010,"High income",13.133 94 | "KOR",2010,"High income",34.659 95 | "KWT",2010,"High income",50.831 96 | "LAO",2010,"Lower middle income", 97 | "LBN",2010,"Upper middle income",3.847 98 | "LBR",2010,"Low income", 99 | "LBY",2010,"Upper middle income", 100 | "LCA",2010,"Upper middle income",11.734 101 | "LKA",2010,"Lower middle income",28.457 102 | "LSO",2010,"Lower middle income",16.421 103 | "LTU",2010,"High income",17.671 104 | "LUX",2010,"High income",24.899 105 | "LVA",2010,"High income",21.365 106 | "MAC",2010,"High income", 107 | "MAR",2010,"Lower middle income",29.7 108 | "MDA",2010,"Lower middle income",16.001 109 | "MDG",2010,"Low income",13.74 110 | "MDV",2010,"Upper middle income",6.844 111 | "MEX",2010,"Upper middle income",21.555 112 | "MHL",2010,"Upper middle income", 113 | "MKD",2010,"Upper middle income",22.443 114 | "MLI",2010,"Low income",13.306 115 | "MLT",2010,"High income",18.954 116 | "MMR",2010,"Lower middle income",23.184 117 | "MNE",2010,"Upper middle income",-1.246 118 | "MNG",2010,"Lower middle income",26.881 119 | "MOZ",2010,"Low income",8.081 120 | "MRT",2010,"Lower middle income",30.703 121 | "MUS",2010,"Upper middle income",14.27 122 | "MWI",2010,"Low income",26.25 123 | "MYS",2010,"Upper middle income",33.468 124 | "NAM",2010,"Upper middle income",20.709 125 | "NER",2010,"Low income",25.45 126 | "NGA",2010,"Lower middle income",20.843 127 | "NIC",2010,"Lower middle income",15.542 128 | "NLD",2010,"High income",27.798 129 | "NOR",2010,"High income",36.27 130 | "NPL",2010,"Low income",35.909 131 | "NRU",2010,"High income", 132 | "NZL",2010,"High income",24.648 133 | "OMN",2010,"High income",33.761 134 | "PAK",2010,"Lower middle income",13.577 135 | "PAN",2010,"Upper middle income",26.436 136 | "PER",2010,"Upper middle income",22.505 137 | "PHL",2010,"Lower middle income",24.138 138 | "PLW",2010,"Upper middle income", 139 | "PNG",2010,"Lower middle income", 140 | "POL",2010,"High income",15.913 141 | "PRI",2010,"High income", 142 | "PRT",2010,"High income",10.709 143 | "PRY",2010,"Upper middle income",15.905 144 | "QAT",2010,"High income",50.419 145 | "ROU",2010,"Upper middle income",21.755 146 | "RUS",2010,"Upper middle income",24.417 147 | "RWA",2010,"Low income",6.369 148 | "SAU",2010,"High income",43.414 149 | "SDN",2010,"Lower middle income",17.259 150 | "SEN",2010,"Low income",17.708 151 | "SGP",2010,"High income",51.68 152 | "SLB",2010,"Lower middle income",12.799 153 | "SLE",2010,"Low income",9.581 154 | "SLV",2010,"Lower middle income",10.831 155 | "SMR",2010,"High income", 156 | "SRB",2010,"Upper middle income",12.102 157 | "SSD",2010,"Low income", 158 | "STP",2010,"Lower middle income",32.965 159 | "SUR",2010,"Upper middle income",50.552 160 | "SVK",2010,"High income",19.303 161 | "SVN",2010,"High income",22.121 162 | "SWE",2010,"High income",28.876 163 | "SWZ",2010,"Lower middle income",3.179 164 | "SYC",2010,"High income",17.241 165 | "SYR",2010,"Lower middle income",23.845 166 | "TCD",2010,"Low income",25.871 167 | "TGO",2010,"Low income",17.634 168 | "THA",2010,"Upper middle income",28.724 169 | "TJK",2010,"Lower middle income",6.999 170 | "TKM",2010,"Upper middle income", 171 | "TLS",2010,"Lower middle income", 172 | "TON",2010,"Lower middle income", 173 | "TTO",2010,"High income",13.168 174 | "TUN",2010,"Lower middle income",20.825 175 | "TUR",2010,"Upper middle income",21.334 176 | "TUV",2010,"Upper middle income", 177 | "TZA",2010,"Low income",21.248 178 | "UGA",2010,"Low income",18.7 179 | "UKR",2010,"Lower middle income",18.654 180 | "URY",2010,"High income",17.593 181 | "USA",2010,"High income",15.086 182 | "UZB",2010,"Lower middle income",37.267 183 | "VCT",2010,"Upper middle income",-1.591 184 | "VEN",2010,"Upper middle income",31.591 185 | "VNM",2010,"Lower middle income",31.902 186 | "VUT",2010,"Lower middle income", 187 | "WSM",2010,"Lower middle income", 188 | "YEM",2010,"Lower middle income",8.25 189 | "ZAF",2010,"Upper middle income",18.012 190 | "ZMB",2010,"Lower middle income",37.404 191 | "ZWE",2010,"Low income",16.109 192 | -------------------------------------------------------------------------------- /countries/countries_plus.csv: -------------------------------------------------------------------------------- 1 | "name","continent","code","surface_area","geosize_group" 2 | "Afghanistan","Asia","AFG",652090,"medium" 3 | "Netherlands","Europe","NLD",41526,"small" 4 | "Albania","Europe","ALB",28748,"small" 5 | "Algeria","Africa","DZA",2381740,"large" 6 | "American Samoa","Oceania","ASM",199,"small" 7 | "Andorra","Europe","AND",468,"small" 8 | "Angola","Africa","AGO",1246700,"medium" 9 | "Antigua and Barbuda","North America","ATG",442,"small" 10 | "United Arab Emirates","Asia","ARE",83600,"small" 11 | "Argentina","South America","ARG",2780400,"large" 12 | "Armenia","Asia","ARM",29800,"small" 13 | "Aruba","North America","ABW",193,"small" 14 | "Australia","Oceania","AUS",7741220,"large" 15 | "Azerbaijan","Asia","AZE",86600,"small" 16 | "Bahamas","North America","BHS",13878,"small" 17 | "Bahrain","Asia","BHR",694,"small" 18 | "Bangladesh","Asia","BGD",143998,"small" 19 | "Barbados","North America","BRB",430,"small" 20 | "Belgium","Europe","BEL",30518,"small" 21 | "Belize","North America","BLZ",22696,"small" 22 | "Benin","Africa","BEN",112622,"small" 23 | "Bermuda","North America","BMU",53,"small" 24 | "Bhutan","Asia","BTN",47000,"small" 25 | "Bolivia","South America","BOL",1098580,"medium" 26 | "Bosnia and Herzegovina","Europe","BIH",51197,"small" 27 | "Botswana","Africa","BWA",581730,"medium" 28 | "Brazil","South America","BRA",8547400,"large" 29 | "United Kingdom","Europe","GBR",242900,"small" 30 | "Virgin Islands, British","North America","VGB",151,"small" 31 | "Brunei","Asia","BRN",5765,"small" 32 | "Bulgaria","Europe","BGR",110994,"small" 33 | "Burkina Faso","Africa","BFA",274000,"small" 34 | "Burundi","Africa","BDI",27834,"small" 35 | "Cayman Islands","North America","CYM",264,"small" 36 | "Chile","South America","CHL",756626,"medium" 37 | "Costa Rica","North America","CRI",51100,"small" 38 | "Djibouti","Africa","DJI",23200,"small" 39 | "Dominica","North America","DMA",751,"small" 40 | "Dominican Republic","North America","DOM",48511,"small" 41 | "Ecuador","South America","ECU",283561,"small" 42 | "Egypt","Africa","EGY",1001450,"medium" 43 | "El Salvador","North America","SLV",21041,"small" 44 | "Eritrea","Africa","ERI",117600,"small" 45 | "Spain","Europe","ESP",505992,"medium" 46 | "South Africa","Africa","ZAF",1221040,"medium" 47 | "Ethiopia","Africa","ETH",1104300,"medium" 48 | "Fiji Islands","Oceania","FJI",18274,"small" 49 | "Philippines","Asia","PHL",300000,"small" 50 | "Faroe Islands","Europe","FRO",1399,"small" 51 | "Gabon","Africa","GAB",267668,"small" 52 | "Gambia","Africa","GMB",11295,"small" 53 | "Georgia","Asia","GEO",69700,"small" 54 | "Ghana","Africa","GHA",238533,"small" 55 | "Gibraltar","Europe","GIB",6,"small" 56 | "Grenada","North America","GRD",344,"small" 57 | "Greenland","North America","GRL",2166090,"large" 58 | "Guam","Oceania","GUM",549,"small" 59 | "Guatemala","North America","GTM",108889,"small" 60 | "Guinea","Africa","GIN",245857,"small" 61 | "Guinea-Bissau","Africa","GNB",36125,"small" 62 | "Guyana","South America","GUY",214969,"small" 63 | "Haiti","North America","HTI",27750,"small" 64 | "Honduras","North America","HND",112088,"small" 65 | "Hong Kong","Asia","HKG",1075,"small" 66 | "Indonesia","Asia","IDN",1904570,"medium" 67 | "India","Asia","IND",3287260,"large" 68 | "Iraq","Asia","IRQ",438317,"medium" 69 | "Iran","Asia","IRN",1648200,"medium" 70 | "Ireland","Europe","IRL",70273,"small" 71 | "Iceland","Europe","ISL",103000,"small" 72 | "Israel","Asia","ISR",21056,"small" 73 | "Italy","Europe","ITA",301316,"small" 74 | "Austria","Europe","AUT",83859,"small" 75 | "Jamaica","North America","JAM",10990,"small" 76 | "Japan","Asia","JPN",377829,"medium" 77 | "Yemen","Asia","YEM",527968,"medium" 78 | "Jordan","Asia","JOR",88946,"small" 79 | "Cambodia","Asia","KHM",181035,"small" 80 | "Cameroon","Africa","CMR",475442,"medium" 81 | "Canada","North America","CAN",9970610,"large" 82 | "Cape Verde","Africa","CPV",4033,"small" 83 | "Kazakhstan","Asia","KAZ",2724900,"large" 84 | "Kenya","Africa","KEN",580367,"medium" 85 | "Central African Republic","Africa","CAF",622984,"medium" 86 | "China","Asia","CHN",9572900,"large" 87 | "Kyrgyzstan","Asia","KGZ",199900,"small" 88 | "Kiribati","Oceania","KIR",726,"small" 89 | "Colombia","South America","COL",1138910,"medium" 90 | "Comoros","Africa","COM",1862,"small" 91 | "Congo","Africa","COG",342000,"small" 92 | "Congo, The Democratic Republic of the","Africa","COD",2344860,"large" 93 | "North Korea","Asia","PRK",120538,"small" 94 | "South Korea","Asia","KOR",99434,"small" 95 | "Greece","Europe","GRC",131626,"small" 96 | "Croatia","Europe","HRV",56538,"small" 97 | "Cuba","North America","CUB",110861,"small" 98 | "Kuwait","Asia","KWT",17818,"small" 99 | "Cyprus","Asia","CYP",9251,"small" 100 | "Laos","Asia","LAO",236800,"small" 101 | "Latvia","Europe","LVA",64589,"small" 102 | "Lesotho","Africa","LSO",30355,"small" 103 | "Lebanon","Asia","LBN",10400,"small" 104 | "Liberia","Africa","LBR",111369,"small" 105 | "Libya","Africa","LBY",1759540,"medium" 106 | "Liechtenstein","Europe","LIE",160,"small" 107 | "Lithuania","Europe","LTU",65301,"small" 108 | "Luxembourg","Europe","LUX",2586,"small" 109 | "Macao","Asia","MAC",18,"small" 110 | "Madagascar","Africa","MDG",587041,"medium" 111 | "Macedonia","Europe","MKD",25713,"small" 112 | "Malawi","Africa","MWI",118484,"small" 113 | "Maldives","Asia","MDV",298,"small" 114 | "Malaysia","Asia","MYS",329758,"small" 115 | "Mali","Africa","MLI",1240190,"medium" 116 | "Malta","Europe","MLT",316,"small" 117 | "Morocco","Africa","MAR",446550,"medium" 118 | "Marshall Islands","Oceania","MHL",181,"small" 119 | "Mauritania","Africa","MRT",1025520,"medium" 120 | "Mauritius","Africa","MUS",2040,"small" 121 | "Mexico","North America","MEX",1958200,"medium" 122 | "Micronesia, Federated States of","Oceania","FSM",702,"small" 123 | "Moldova","Europe","MDA",33851,"small" 124 | "Monaco","Europe","MCO",1.5,"small" 125 | "Mongolia","Asia","MNG",1566500,"medium" 126 | "Mozambique","Africa","MOZ",801590,"medium" 127 | "Myanmar","Asia","MMR",676578,"medium" 128 | "Namibia","Africa","NAM",824292,"medium" 129 | "Nauru","Oceania","NRU",21,"small" 130 | "Nepal","Asia","NPL",147181,"small" 131 | "Nicaragua","North America","NIC",130000,"small" 132 | "Niger","Africa","NER",1267000,"medium" 133 | "Nigeria","Africa","NGA",923768,"medium" 134 | "Norway","Europe","NOR",323877,"small" 135 | "Cote d'Ivoire","Africa","CIV",322463,"small" 136 | "Oman","Asia","OMN",309500,"small" 137 | "Pakistan","Asia","PAK",796095,"medium" 138 | "Palau","Oceania","PLW",459,"small" 139 | "Panama","North America","PAN",75517,"small" 140 | "Papua New Guinea","Oceania","PNG",462840,"medium" 141 | "Paraguay","South America","PRY",406752,"medium" 142 | "Peru","South America","PER",1285220,"medium" 143 | "Northern Mariana Islands","Oceania","MNP",464,"small" 144 | "Portugal","Europe","PRT",91982,"small" 145 | "Puerto Rico","North America","PRI",8875,"small" 146 | "Poland","Europe","POL",323250,"small" 147 | "Equatorial Guinea","Africa","GNQ",28051,"small" 148 | "Qatar","Asia","QAT",11000,"small" 149 | "France","Europe","FRA",551500,"medium" 150 | "French Polynesia","Oceania","PYF",4000,"small" 151 | "Rwanda","Africa","RWA",26338,"small" 152 | "Sweden","Europe","SWE",449964,"medium" 153 | "Saint Kitts and Nevis","North America","KNA",261,"small" 154 | "Saint Lucia","North America","LCA",622,"small" 155 | "Saint Vincent and the Grenadines","North America","VCT",388,"small" 156 | "Germany","Europe","DEU",357022,"medium" 157 | "Solomon Islands","Oceania","SLB",28896,"small" 158 | "Zambia","Africa","ZMB",752618,"medium" 159 | "Samoa","Oceania","WSM",2831,"small" 160 | "San Marino","Europe","SMR",61,"small" 161 | "Sao Tome and Principe","Africa","STP",964,"small" 162 | "Saudi Arabia","Asia","SAU",2149690,"large" 163 | "Senegal","Africa","SEN",196722,"small" 164 | "Seychelles","Africa","SYC",455,"small" 165 | "Sierra Leone","Africa","SLE",71740,"small" 166 | "Singapore","Asia","SGP",618,"small" 167 | "Slovakia","Europe","SVK",49012,"small" 168 | "Slovenia","Europe","SVN",20256,"small" 169 | "Somalia","Africa","SOM",637657,"medium" 170 | "Sri Lanka","Asia","LKA",65610,"small" 171 | "Sudan","Africa","SDN",2505810,"large" 172 | "Finland","Europe","FIN",338145,"small" 173 | "Suriname","South America","SUR",163265,"small" 174 | "Swaziland","Africa","SWZ",17364,"small" 175 | "Switzerland","Europe","CHE",41284,"small" 176 | "Syria","Asia","SYR",185180,"small" 177 | "Tajikistan","Asia","TJK",143100,"small" 178 | "Tanzania","Africa","TZA",883749,"medium" 179 | "Denmark","Europe","DNK",43094,"small" 180 | "Thailand","Asia","THA",513115,"medium" 181 | "Togo","Africa","TGO",56785,"small" 182 | "Tonga","Oceania","TON",650,"small" 183 | "Trinidad and Tobago","North America","TTO",5130,"small" 184 | "Chad","Africa","TCD",1284000,"medium" 185 | "Czech Republic","Europe","CZE",78866,"small" 186 | "Tunisia","Africa","TUN",163610,"small" 187 | "Turkey","Asia","TUR",774815,"medium" 188 | "Turkmenistan","Asia","TKM",488100,"medium" 189 | "Turks and Caicos Islands","North America","TCA",430,"small" 190 | "Tuvalu","Oceania","TUV",26,"small" 191 | "Uganda","Africa","UGA",241038,"small" 192 | "Ukraine","Europe","UKR",603700,"medium" 193 | "Hungary","Europe","HUN",93030,"small" 194 | "Uruguay","South America","URY",175016,"small" 195 | "New Caledonia","Oceania","NCL",18575,"small" 196 | "New Zealand","Oceania","NZL",270534,"small" 197 | "Uzbekistan","Asia","UZB",447400,"medium" 198 | "Belarus","Europe","BLR",207600,"small" 199 | "Vanuatu","Oceania","VUT",12189,"small" 200 | "Venezuela","South America","VEN",912050,"medium" 201 | "Russian Federation","Europe","RUS",17075400,"large" 202 | "Vietnam","Asia","VNM",331689,"small" 203 | "Estonia","Europe","EST",45227,"small" 204 | "United States","North America","USA",9363520,"large" 205 | "Virgin Islands, U.S.","North America","VIR",347,"small" 206 | "Zimbabwe","Africa","ZWE",390757,"medium" 207 | "Palestine","Asia","PSE",6257,"small" 208 | -------------------------------------------------------------------------------- /countries/cities.csv: -------------------------------------------------------------------------------- 1 | "name","country_code","city_proper_pop","metroarea_pop","urbanarea_pop" 2 | "Abidjan","CIV",4765000,,4765000 3 | "Abu Dhabi","ARE",1145000,,1145000 4 | "Abuja","NGA",1235880,6000000,1235880 5 | "Accra","GHA",2070463,4010054,2070463 6 | "Addis Ababa","ETH",3103673,4567857,3103673 7 | "Ahmedabad","IND",5570585,,5570585 8 | "Alexandria","EGY",4616625,,4616625 9 | "Algiers","DZA",3415811,5000000,3415811 10 | "Almaty","KAZ",1703481,,1703481 11 | "Ankara","TUR",5271000,4585000,5271000 12 | "Auckland","NZL",1495000,1614300,1495000 13 | "Baghdad","IRQ",7180889,,7180889 14 | "Baku","AZE",3202300,4308740,3202300 15 | "Bandung","IDN",2575478,6965655,2575478 16 | "Bangkok","THA",8280925,14998000,8280925 17 | "Barcelona","ESP",1604555,5375774,1604555 18 | "Barranquilla","COL",1386865,2370753,1386865 19 | "Basra","IRQ",2750000,,2750000 20 | "Beijing","CHN",21516000,24900000,21516000 21 | "Belo Horizonte","BRA",2502557,5156217,2502557 22 | "Bengaluru","IND",8425970,9807000,8425970 23 | "Berlin","DEU",3517424,5871022,3517424 24 | "Bhopal","IND",1798218,1864389,1798218 25 | "Birmingham","GBR",1111300,3683000,1111300 26 | "Bogota","COL",7878783,9800000,7878783 27 | "Brasilia","BRA",2556149,3919864,2556149 28 | "Brazzaville","COG",1827000,,1827000 29 | "Brisbane","AUS",1180285,2349699,1180285 30 | "Bucharest","ROM",1883425,2272163,1883425 31 | "Budapest","HUN",1759407,2927944,1759407 32 | "Buenos Aires","ARG",3054300,14122000,3054300 33 | "Busan","KOR",3510833,8202239,3510833 34 | "Cairo","EGY",10230350,18290000,10230350 35 | "Calgary","CAN",1235171,1214839,1235171 36 | "Cali","COL",2400653,3400000,2400653 37 | "Caloocan","PHL",1583978,,1583978 38 | "Campinas","BRA",1164098,3094181,1164098 39 | "Cape Town","ZAF",3740026,,3740026 40 | "Caracas","VEN",1943901,2923959,1943901 41 | "Casablanca","MAR",5117832,6861739,5117832 42 | "Changchun","CHN",3815270,7674439,3815270 43 | "Changsha","CHN",7044118,,7044118 44 | "Chaozhou","CHN",2669844,,2669844 45 | "Chengdu","CHN",4741929,10376000,4741929 46 | "Chennai","IND",7088000,,7088000 47 | "Chicago","USA",2695598,9156000,2695598 48 | "Chittagong","BGD",2581643,4009423,2581643 49 | "Chongqing","CHN",8189800,52100100,8189800 50 | "Cologne","DEU",1057327,3573500,1057327 51 | "Cordoba","ARG",1330023,1528000,1330023 52 | "Curitiba","BRA",1879355,3400000,1879355 53 | "Daegu","KOR",2492994,,2492994 54 | "Daejeon","KOR",1535028,,1535028 55 | "Dakar","SEN",1146053,2452656,1146053 56 | "Dalian","CHN",2146099,5935638,2146099 57 | "Dallas","USA",1317929,7233323,1317929 58 | "Dar es Salaam","TZA",4364541,,4364541 59 | "Davao City","PHL",1632991,2516216,1632991 60 | "Delhi","IND",16787941,24998000,16787941 61 | "Dhaka","BGD",14543124,,14543124 62 | "Dongguan","CHN",8220207,,8220207 63 | "Douala","CMR",2446945,,2446945 64 | "Dubai","ARE",2643410,,2643410 65 | "Durban","ZAF",3442361,,3442361 66 | "Ekurhuleni","ZAF",3178470,,3178470 67 | "Faisalabad","PAK",6480765,3675000,6480765 68 | "Fez","MAR",1112072,,1112072 69 | "Fortaleza","BRA",2609716,4019213,2609716 70 | "Foshan","CHN",6151622,,6151622 71 | "Fukuoka","JPN",1483052,5590378,1483052 72 | "Fuzhou","CHN",7115369,,7115369 73 | "Giza","EGY",4239988,,4239988 74 | "Guadalajara","MEX",1495189,4424252,1495189 75 | "Guangzhou","CHN",14043500,44259000,14043500 76 | "Guatemala City","GTM",2110100,4500000,2110100 77 | "Guayaquil","ECU",3600000,5000000,3600000 78 | "Gujranwala","PAK",2700003,,2700003 79 | "Hamburg","DEU",1787408,,1787408 80 | "Hangzhou","CHN",3560391,,3560391 81 | "Hanoi","VNM",6844100,,6844100 82 | "Harare","ZWE",1606000,,1606000 83 | "Harbin","CHN",4280701,10635971,4280701 84 | "Havana","CUB",2106146,,2106146 85 | "Hefei","CHN",3352076,,3352076 86 | "Hiroshima","JPN",1196274,,1196274 87 | "Ho Chi Minh City","VNM",7681700,,7681700 88 | "Hong Kong","CHN",7374900,,7374900 89 | "Houston","USA",2489558,6490180,2489558 90 | "Hyderabad (India)","IND",7859250,,7859250 91 | "Hyderabad","PAK",3429471,,3429471 92 | "Ibadan","NGA",1338659,2837000,1338659 93 | "Incheon","KOR",2978367,,2978367 94 | "Isfahan","IRN",2243249,,2243249 95 | "Islamabad","PAK",1900000,2200000,1900000 96 | "Istanbul","TUR",14025000,13520000,14025000 97 | "Izmir","TUR",4168000,3019000,4168000 98 | "Jaipur","IND",3073350,,3073350 99 | "Jakarta","IDN",10075310,30539000,10075310 100 | "Jeddah","SAU",3456259,,3456259 101 | "Jinan","CHN",2009273,5853196,2009273 102 | "Johannesburg","ZAF",4434827,,4434827 103 | "Kabul","AFG",3414100,,3414100 104 | "Kampala","UGA",1507080,,1507080 105 | "Kano","NGA",2153225,3395000,2153225 106 | "Kanpur","IND",2768057,3152317,2768057 107 | "Kaohsiung","TWN",2778918,,2778918 108 | "Karachi","PAK",27506000,25400000,27506000 109 | "Karaj","IRN",1973470,,1973470 110 | "Kawasaki","JPN",1496035,,1496035 111 | "Kharkov","UKR",1439566,1650000,1439566 112 | "Khartoum","SDN",3639598,5274321,3639598 113 | "Kiev","UKR",2908703,,2908703 114 | "Kinshasa","COD",10130000,13265000,10130000 115 | "Kobe","JPN",1536499,,1536499 116 | "Kochi","IND",2232456,4221140,2232456 117 | "Kolkata","IND",4486679,14667000,4486679 118 | "Kuala Lumpur","MYS",1768000,7200000,1768000 119 | "Kwangju","KOR",1477780,,1477780 120 | "Kyoto","JPN",1474570,,1474570 121 | "Lagos","NGA",16060303,21000000,16060303 122 | "Lahore","PAK",10355000,13569000,10355000 123 | "Lanzhou","CHN",2177130,3616163,2177130 124 | "Lima","PER",8852000,10750000,8852000 125 | "London","GBR",8673713,13879757,8673713 126 | "Los Angeles","USA",3884307,15058000,3884307 127 | "Luanda","AGO",2825311,,2825311 128 | "Lucknow","IND",2815601,,2815601 129 | "Lusaka","ZMB",1742979,2467467,1742979 130 | "Madrid","ESP",3207247,,3207247 131 | "Makassar","IDN",1338633,1976168,1338633 132 | "Managua","NIC",2560789,,2560789 133 | "Mandalay","MMR",1319452,1726889,1319452 134 | "Manila","PHL",1780148,12877253,1780148 135 | "Maputo","MOZ",1766184,1766823,1766184 136 | "Maracaibo","VEN",1599940,3897655,1599940 137 | "Mashhad","IRN",3312090,3372660,3312090 138 | "Medan","IDN",2097610,4103696,2097610 139 | "Medellin","COL",2441123,3731447,2441123 140 | "Mexico City","MEX",8974724,20063000,8974724 141 | "Milan","ITA",1359905,3206465,1359905 142 | "Minsk","BLR",1959781,,1959781 143 | "Monterrey","MEX",1130960,4520329,1130960 144 | "Montevideo","URY",1305082,1947604,1305082 145 | "Montreal","CAN",1649519,4127100,1649519 146 | "Moscow","RUS",12197596,16170000,12197596 147 | "Multan","PAK",3117000,,3117000 148 | "Mumbai","IND",12478447,17712000,12478447 149 | "Munich","DEU",1450381,2606021,1450381 150 | "Nagoya","JPN",2296014,9107414,2296014 151 | "Nagpur","IND",2405665,2497870,2405665 152 | "Nairobi","KEN",3138369,,3138369 153 | "Nanjing","CHN",8230000,34360000,8230000 154 | "New Taipei City","TWN",3954929,,3954929 155 | "New York City","USA",8550405,20182305,8550405 156 | "Ningbo","CHN",3491597,7639000,3491597 157 | "Nizhny Novgorod","RUS",1250619,,1250619 158 | "Novosibirsk","RUS",1567087,,1567087 159 | "Omsk","RUS",1154116,,1154116 160 | "Oran","DZA",1560329,3454078,1560329 161 | "Osaka","JPN",2691742,19341976,2691742 162 | "Ouagadougou","BFA",2200000,2500000,2200000 163 | "Palembang","IDN",1708413,,1708413 164 | "Paris","FRA",2229621,10601122,2229621 165 | "Patna","IND",1683200,2231554,1683200 166 | "Peshawar","PAK",3201000,,3201000 167 | "Philadelphia","USA",1567872,6069875,1567872 168 | "Phnom Penh","KHM",2234566,,2234566 169 | "Phoenix","USA",1563025,4574531,1563025 170 | "Porto Alegre","BRA",1476867,,1476867 171 | "Prague","CZE",1324000,,1324000 172 | "Pune","IND",3115431,,3115431 173 | "Pyongyang","PRK",3255388,,3255388 174 | "Qingdao","CHN",6188100,9046200,6188100 175 | "Quanzhou","CHN",8128533,6107475,8128533 176 | "Quezon City","PHL",2936116,,2936116 177 | "Quito","ECU",2671191,4700000,2671191 178 | "Rawalpindi","PAK",3198911,,3198911 179 | "Recife","BRA",1555039,3743854,1555039 180 | "Rio de Janeiro","BRA",6429923,12727000,6429923 181 | "Riyadh","SAU",5676621,,5676621 182 | "Rome","ITA",2877215,4353775,2877215 183 | "Rosario","ARG",1193605,1276000,1193605 184 | "Rostov-on-Don","RUS",1119900,,1119900 185 | "Saint Petersburg","RUS",5191690,5900000,5191690 186 | "Saitama","JPN",1226656,,1226656 187 | "Salvador","BRA",2902927,3919864,2902927 188 | "San Antonio","USA",1469845,2454061,1469845 189 | "San Diego","USA",1394928,3095313,1394928 190 | "Sana'a","YEM",1937451,2167961,1937451 191 | "Santa Cruz de la Sierra","BOL",1453549,1749000,1453549 192 | "Santiago","CHL",5743719,,5743719 193 | "Sao Paulo","BRA",12038175,21090791,12038175 194 | "Sapporo","JPN",1918096,2584880,1918096 195 | "Semarang","IDN",1555984,3183516,1555984 196 | "Seoul","KOR",9995784,12700000,9995784 197 | "Shanghai","CHN",24256800,34750000,24256800 198 | "Shantou","CHN",5391028,11535677,5391028 199 | "Shenyang","CHN",8106171,,8106171 200 | "Shenzhen","CHN",10778900,,10778900 201 | "Shijiazhuang","CHN",4303700,10701600,4303700 202 | "Shiraz","IRN",1869001,,1869001 203 | "Singapore","SGP",5535000,,5535000 204 | "Surabaya","IDN",2765487,7302283,2765487 205 | "Surat","IND",4462002,,4462002 206 | "Suzhou","CHN",10650501,,10650501 207 | "T'bilisi","GEO",1118035,1485293,1118035 208 | "Tabriz","IRN",1733033,,1733033 209 | "Taichung","TWN",2752413,,2752413 210 | "Tainan","TWN",1885252,,1885252 211 | "Taipei","TWN",2704974,,2704974 212 | "Tangshan","CHN",3187171,7536521,3187171 213 | "Tashkent","UZB",2309600,,2309600 214 | "Tehran","IRN",8154051,13532000,8154051 215 | "Tianjin","CHN",6859779,15469500,6859779 216 | "Tijuana","MEX",1696923,1895797,1696923 217 | "Tokyo","JPN",13513734,37843000,13513734 218 | "Toronto","CAN",2731571,6417516,2731571 219 | "Tripoli","LBY",1126000,2267000,1126000 220 | "Tunis","TUN",1056247,2643695,1056247 221 | "Ulsan","KOR",1163690,,1163690 222 | "Vienna","AUT",1863881,2600000,1863881 223 | "Vijayawada","IND",1491202,,1491202 224 | "Visakhapatnam","IND",2035922,5340000,2035922 225 | "Warsaw","POL",1753977,3100844,1753977 226 | "Wenzhou","CHN",3039439,,3039439 227 | "Wuhan","CHN",6886253,,6886253 228 | "Xi'an","CHN",8705600,13569700,8705600 229 | "Xiamen","CHN",3531347,5114758,3531347 230 | "Yangon","MMR",5214000,,5214000 231 | "Yaounde","CMR",2440462,,2440462 232 | "Yekaterinburg","RUS",1428042,,1428042 233 | "Yerevan","ARM",1060138,,1060138 234 | "Yokohama","JPN",3726167,,3726167 235 | "Zhengzhou","CHN",4122087,,4122087 236 | "Zhongshan","CHN",3121275,,3121275 237 | "Zunyi","CHN",6127009,,6127009 238 | -------------------------------------------------------------------------------- /audition.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "collapsed": true 7 | }, 8 | "source": [ 9 | "Welcome to your DataCamp Project audition! This notebook must be filled out and vetted before a contract can be signed and you can start creating your Project.\n", 10 | "\n", 11 | "The first step is forking the repository in which this notebook lives. After that, there are three parts to be completed in this notebook:\n", 12 | "\n", 13 | "- **Project information**: The title of the Project, a Project description, etc.\n", 14 | "\n", 15 | "- **Project introduction**: The three first text and code cells that will form the introduction of your Project.\n", 16 | "\n", 17 | "- **Rough draft of code for rest of Project:** a rough draft of the remaining code for the rest of your Project (no accompanying text cells required).\n", 18 | "\n", 19 | "When complete, please email the link to your forked repo to projects@datacamp.com with the email subject line _DataCamp Project audition_. If you have any questions, please reach out to projects@datacamp.com." 20 | ] 21 | }, 22 | { 23 | "cell_type": "markdown", 24 | "metadata": {}, 25 | "source": [ 26 | "# Project information" 27 | ] 28 | }, 29 | { 30 | "cell_type": "markdown", 31 | "metadata": {}, 32 | "source": [ 33 | "**Project title**: The title of the Project. Maximum 41 characters.\n", 34 | "\n", 35 | "**Name:** Your full name.\n", 36 | "\n", 37 | "**Email address associated with your DataCamp account:** You can find this email [here](https://www.datacamp.com/profile/account_settings) if you have a DataCamp account.\n", 38 | "\n", 39 | "**Project description**: This will be read by the students on the DataCamp platform **before** deciding to start the Project. The description should be three paragraphs, written in Markdown.\n", 40 | "\n", 41 | "- Paragraph 1 should be an exciting introduction to analysis/model/etc. students will complete.\n", 42 | "- Paragraph 2 should list the background knowledge you assume the student doing this Project will have, the more specific the better. Please list things like modules, tools, functions, methods, statistical concepts, etc.\n", 43 | "- Paragraph 3 should describe and link to (if possible) the dataset used in the Project." 44 | ] 45 | }, 46 | { 47 | "cell_type": "markdown", 48 | "metadata": {}, 49 | "source": [ 50 | "# Project introduction\n", 51 | "\n", 52 | "***Note: nothing needs to be filled out in this cell. It is simply setting up the template cells below.***\n", 53 | "\n", 54 | "The final output of a DataCamp Project looks like a blog post: pairs of text and code cells that tell a story about data. The text is written from the perspective of the data analyst and *not* from the perspective of an instructor on DataCamp. So, for this blog post intro, all you need to do is pretend like you're writing a blog post -- forget the part about instructors and students.\n", 55 | "\n", 56 | "Below you'll see the structure of a DataCamp Project: a series of \"tasks\" where each task consists of a title, a **single** text cell, and a **single** code cell. There are 8-12 tasks in a Project and each task can have up to 10 lines of code. What you need to do:\n", 57 | "1. Read through the template structure.\n", 58 | "2. As best you can, divide your Project as it is currently visualized in your mind into tasks.\n", 59 | "3. Fill out the template structure for the first three tasks of your Project.\n", 60 | "\n", 61 | "As you are completing each task, you may wish to consult the Project notebook format in our [documentation](https://instructor-support.datacamp.com/projects/datacamp-projects-jupyter-notebook). Only the `@context` and `@solution` cells are relevant to this audition.\n", 62 | "\n", 63 | "Type the following commands **in your terminal** (not this notebook) to get PostgreSQL up and running on your computer. (Note: students won't have to do this as everything will be pre-set up on www.datacamp.com.)" 64 | ] 65 | }, 66 | { 67 | "cell_type": "code", 68 | "execution_count": null, 69 | "metadata": {}, 70 | "outputs": [], 71 | "source": [ 72 | "# 1. Install PostgreSQL\n", 73 | "brew install postgresql\n", 74 | "# 2. Start PostgreSQL\n", 75 | "brew services start postgresql\n", 76 | "# 3. Open a PostgreSQL interactive terminal\n", 77 | "psql postgres\n", 78 | "# 4. Set a password for the user named postgres by typing the following in the interactive terminal\n", 79 | "\\password postgres;" 80 | ] 81 | }, 82 | { 83 | "cell_type": "markdown", 84 | "metadata": {}, 85 | "source": [ 86 | "5. If you're populating your database from CSV files, create a folder for your database that mimics the files and structure of the `countries` folder in this repo. That means **creating and naming the folder, putting your CSV file(s) in this folder, and filling out the `.sql` file accordingly**." 87 | ] 88 | }, 89 | { 90 | "cell_type": "code", 91 | "execution_count": null, 92 | "metadata": {}, 93 | "outputs": [], 94 | "source": [ 95 | "# 6. Exit the interactive psql terminal by typing \\q and then pressing ENTER\n", 96 | "# 7. Run the local requirements script to create and seed your database\n", 97 | "./requirements.local.sh\n", 98 | "# 8. Start a Jupyter Notebook terminal with environment variables\n", 99 | "DB_USERNAME=postgres DB_PASSWORD=password jupyter notebook" 100 | ] 101 | }, 102 | { 103 | "cell_type": "markdown", 104 | "metadata": {}, 105 | "source": [ 106 | "## 1. Title of the first task (<= 55 chars) (sentence case)" 107 | ] 108 | }, 109 | { 110 | "cell_type": "markdown", 111 | "metadata": {}, 112 | "source": [ 113 | "An exciting intro to the analysis. Provide context on the problem you're going to solve, the database you're going to use, the relevant industry, etc. You may wish to briefly introduce the techniques you're going to use. Tell a story to get students excited! It should at most have 1200 characters.\n", 114 | "\n", 115 | "The most common error instructors make in **context cells** is referring to the student or the Project. We want Project notebooks to appear as a blog post or a data analysis. Bad: *\"In this Project, you will...\"* Good: *\"In this notebook, we will...\"*\n", 116 | "\n", 117 | "The first task in Projects often involve loading data.\n", 118 | "\n", 119 | "Images are welcome additions to every Markdown cell, but especially this first one. Make sure the images you use have a [permissive license](https://support.google.com/websearch/answer/29508?hl=en) and display them using [Markdown](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet#images). Store your images in the `img/` folder in this repository." 120 | ] 121 | }, 122 | { 123 | "cell_type": "code", 124 | "execution_count": null, 125 | "metadata": {}, 126 | "outputs": [], 127 | "source": [ 128 | "%load_ext sql\n", 129 | "\n", 130 | "# Note: students won't have to do this as everything will be pre-set up on www.datacamp.com\n", 131 | "import os\n", 132 | "user = os.getenv('DB_USERNAME')\n", 133 | "password = os.getenv('DB_PASSWORD')\n", 134 | "# CHANGE YOUR_DATABASE_NAME BELOW TO MATCH YOUR DATABASE NAME (↓)\n", 135 | "connection_string = \"postgresql://{user}:{password}@localhost/YOUR_DATABASE_NAME\".format(user=user, password=password)\n", 136 | "%sql $connection_string\n", 137 | "%sql SELECT version();\n", 138 | "# CHANGE YOUR_DATABASE_NAME BELOW (↓) TO MATCH YOUR DATABASE NAME" 139 | ] 140 | }, 141 | { 142 | "cell_type": "code", 143 | "execution_count": null, 144 | "metadata": {}, 145 | "outputs": [], 146 | "source": [ 147 | "%%sql\n", 148 | "postgresql:///YOUR_DATABASE_NAME" 149 | ] 150 | }, 151 | { 152 | "cell_type": "markdown", 153 | "metadata": {}, 154 | "source": [ 155 | "## 2. Title of the second task (<= 55 chars) (sentence case)" 156 | ] 157 | }, 158 | { 159 | "cell_type": "markdown", 160 | "metadata": {}, 161 | "source": [ 162 | "Context / background / story / etc. This cell should at most have 800 characters.\n", 163 | "\n", 164 | "The most common error instructors make in **context cells** is referring to the student or the Project. We want Project notebooks to appear as a blog post or a data analysis. Bad: *\"In this task, you will...\"* Good: *\"Next, we will...\"*" 165 | ] 166 | }, 167 | { 168 | "cell_type": "code", 169 | "execution_count": null, 170 | "metadata": {}, 171 | "outputs": [], 172 | "source": [ 173 | "%%sql" 174 | ] 175 | }, 176 | { 177 | "cell_type": "markdown", 178 | "metadata": {}, 179 | "source": [ 180 | "## 3. Title of the third task (<= 55 chars) (sentence case)" 181 | ] 182 | }, 183 | { 184 | "cell_type": "markdown", 185 | "metadata": {}, 186 | "source": [ 187 | "Context / background / story / etc. This cell should at most have 800 characters.\n", 188 | "\n", 189 | "The most common error instructors make in **context cells** is referring to the student or the Project. We want Project notebooks to appear as a blog post or a data analysis. Bad: *\"In this task, you will...\"* Good: *\"Next, we will...\"*" 190 | ] 191 | }, 192 | { 193 | "cell_type": "code", 194 | "execution_count": null, 195 | "metadata": {}, 196 | "outputs": [], 197 | "source": [ 198 | "%%sql" 199 | ] 200 | }, 201 | { 202 | "cell_type": "markdown", 203 | "metadata": {}, 204 | "source": [ 205 | "# Rough draft of code for rest of Project\n", 206 | "Please include a rough draft of the code for the rest of your proposed Project below. Use as many code cells as you'd like. No accompanying text (i.e. context) cells required." 207 | ] 208 | }, 209 | { 210 | "cell_type": "code", 211 | "execution_count": null, 212 | "metadata": {}, 213 | "outputs": [], 214 | "source": [ 215 | "%%sql" 216 | ] 217 | } 218 | ], 219 | "metadata": { 220 | "kernelspec": { 221 | "display_name": "Python 3", 222 | "language": "python", 223 | "name": "python3" 224 | }, 225 | "language_info": { 226 | "codemirror_mode": { 227 | "name": "ipython", 228 | "version": 3 229 | }, 230 | "file_extension": ".py", 231 | "mimetype": "text/x-python", 232 | "name": "python", 233 | "nbconvert_exporter": "python", 234 | "pygments_lexer": "ipython3", 235 | "version": "3.7.1" 236 | } 237 | }, 238 | "nbformat": 4, 239 | "nbformat_minor": 2 240 | } 241 | -------------------------------------------------------------------------------- /.ipynb_checkpoints/audition-checkpoint.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "collapsed": true 7 | }, 8 | "source": [ 9 | "Welcome to your DataCamp Project audition! This notebook must be filled out and vetted before a contract can be signed and you can start creating your Project.\n", 10 | "\n", 11 | "The first step is forking the repository in which this notebook lives. After that, there are three parts to be completed in this notebook:\n", 12 | "\n", 13 | "- **Project information**: The title of the Project, a Project description, etc.\n", 14 | "\n", 15 | "- **Project introduction**: The three first text and code cells that will form the introduction of your Project.\n", 16 | "\n", 17 | "- **Rough draft of code for rest of Project:** a rough draft of the remaining code for the rest of your Project (no accompanying text cells required).\n", 18 | "\n", 19 | "When complete, please email the link to your forked repo to projects@datacamp.com with the email subject line _DataCamp Project audition_. If you have any questions, please reach out to projects@datacamp.com." 20 | ] 21 | }, 22 | { 23 | "cell_type": "markdown", 24 | "metadata": {}, 25 | "source": [ 26 | "# Project information" 27 | ] 28 | }, 29 | { 30 | "cell_type": "markdown", 31 | "metadata": {}, 32 | "source": [ 33 | "**Project title**: The title of the Project. Maximum 41 characters.\n", 34 | "\n", 35 | "**Name:** Your full name.\n", 36 | "\n", 37 | "**Email address associated with your DataCamp account:** You can find this email [here](https://www.datacamp.com/profile/account_settings) if you have a DataCamp account.\n", 38 | "\n", 39 | "**Project description**: This will be read by the students on the DataCamp platform **before** deciding to start the Project. The description should be three paragraphs, written in Markdown.\n", 40 | "\n", 41 | "- Paragraph 1 should be an exciting introduction to analysis/model/etc. students will complete.\n", 42 | "- Paragraph 2 should list the background knowledge you assume the student doing this Project will have, the more specific the better. Please list things like modules, tools, functions, methods, statistical concepts, etc.\n", 43 | "- Paragraph 3 should describe and link to (if possible) the dataset used in the Project." 44 | ] 45 | }, 46 | { 47 | "cell_type": "markdown", 48 | "metadata": {}, 49 | "source": [ 50 | "# Project introduction\n", 51 | "\n", 52 | "***Note: nothing needs to be filled out in this cell. It is simply setting up the template cells below.***\n", 53 | "\n", 54 | "The final output of a DataCamp Project looks like a blog post: pairs of text and code cells that tell a story about data. The text is written from the perspective of the data analyst and *not* from the perspective of an instructor on DataCamp. So, for this blog post intro, all you need to do is pretend like you're writing a blog post -- forget the part about instructors and students.\n", 55 | "\n", 56 | "Below you'll see the structure of a DataCamp Project: a series of \"tasks\" where each task consists of a title, a **single** text cell, and a **single** code cell. There are 8-12 tasks in a Project and each task can have up to 10 lines of code. What you need to do:\n", 57 | "1. Read through the template structure.\n", 58 | "2. As best you can, divide your Project as it is currently visualized in your mind into tasks.\n", 59 | "3. Fill out the template structure for the first three tasks of your Project.\n", 60 | "\n", 61 | "As you are completing each task, you may wish to consult the Project notebook format in our [documentation](https://instructor-support.datacamp.com/projects/datacamp-projects-jupyter-notebook). Only the `@context` and `@solution` cells are relevant to this audition.\n", 62 | "\n", 63 | "Type the following commands **in your terminal** (not this notebook) to get PostgreSQL up and running on your computer. (Note: students won't have to do this as everything will be pre-set up on www.datacamp.com.)" 64 | ] 65 | }, 66 | { 67 | "cell_type": "code", 68 | "execution_count": null, 69 | "metadata": {}, 70 | "outputs": [], 71 | "source": [ 72 | "# 1. Install PostgreSQL\n", 73 | "brew install postgresql\n", 74 | "# 2. Start PostgreSQL\n", 75 | "brew services start postgresql\n", 76 | "# 3. Open a PostgreSQL interactive terminal\n", 77 | "psql postgres\n", 78 | "# 4. Set a password for the user named postgres by typing the following in the interactive terminal\n", 79 | "\\password postgres;" 80 | ] 81 | }, 82 | { 83 | "cell_type": "markdown", 84 | "metadata": {}, 85 | "source": [ 86 | "5. If you're populating your database from CSV files, create a folder for your database that mimics the files and structure of the `countries` folder in this repo. That means **creating and naming the folder, putting your CSV file(s) in this folder, and filling out the `.sql` file accordingly**." 87 | ] 88 | }, 89 | { 90 | "cell_type": "code", 91 | "execution_count": null, 92 | "metadata": {}, 93 | "outputs": [], 94 | "source": [ 95 | "# 6. Exit the interactive psql terminal by typing \\q and then pressing ENTER\n", 96 | "# 7. Run the local requirements script to create and seed your database\n", 97 | "./requirements.local.sh\n", 98 | "# 8. Start a Jupyter Notebook terminal with environment variables\n", 99 | "DB_USERNAME=postgres DB_PASSWORD=password jupyter notebook" 100 | ] 101 | }, 102 | { 103 | "cell_type": "markdown", 104 | "metadata": {}, 105 | "source": [ 106 | "## 1. Title of the first task (<= 55 chars) (sentence case)" 107 | ] 108 | }, 109 | { 110 | "cell_type": "markdown", 111 | "metadata": {}, 112 | "source": [ 113 | "An exciting intro to the analysis. Provide context on the problem you're going to solve, the database you're going to use, the relevant industry, etc. You may wish to briefly introduce the techniques you're going to use. Tell a story to get students excited! It should at most have 1200 characters.\n", 114 | "\n", 115 | "The most common error instructors make in **context cells** is referring to the student or the Project. We want Project notebooks to appear as a blog post or a data analysis. Bad: *\"In this Project, you will...\"* Good: *\"In this notebook, we will...\"*\n", 116 | "\n", 117 | "The first task in Projects often involve loading data.\n", 118 | "\n", 119 | "Images are welcome additions to every Markdown cell, but especially this first one. Make sure the images you use have a [permissive license](https://support.google.com/websearch/answer/29508?hl=en) and display them using [Markdown](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet#images). Store your images in the `img/` folder in this repository." 120 | ] 121 | }, 122 | { 123 | "cell_type": "code", 124 | "execution_count": null, 125 | "metadata": {}, 126 | "outputs": [], 127 | "source": [ 128 | "%load_ext sql\n", 129 | "\n", 130 | "# Note: students won't have to do this as everything will be pre-set up on www.datacamp.com\n", 131 | "import os\n", 132 | "user = os.getenv('DB_USERNAME')\n", 133 | "password = os.getenv('DB_PASSWORD')\n", 134 | "# CHANGE YOUR_DATABASE_NAME BELOW TO MATCH YOUR DATABASE NAME (↓)\n", 135 | "connection_string = \"postgresql://{user}:{password}@localhost/YOUR_DATABASE_NAME\".format(user=user, password=password)\n", 136 | "%sql $connection_string\n", 137 | "%sql SELECT version();\n", 138 | "# CHANGE YOUR_DATABASE_NAME BELOW (↓) TO MATCH YOUR DATABASE NAME" 139 | ] 140 | }, 141 | { 142 | "cell_type": "code", 143 | "execution_count": null, 144 | "metadata": {}, 145 | "outputs": [], 146 | "source": [ 147 | "%%sql\n", 148 | "postgresql:///YOUR_DATABASE_NAME" 149 | ] 150 | }, 151 | { 152 | "cell_type": "markdown", 153 | "metadata": {}, 154 | "source": [ 155 | "## 2. Title of the second task (<= 55 chars) (sentence case)" 156 | ] 157 | }, 158 | { 159 | "cell_type": "markdown", 160 | "metadata": {}, 161 | "source": [ 162 | "Context / background / story / etc. This cell should at most have 800 characters.\n", 163 | "\n", 164 | "The most common error instructors make in **context cells** is referring to the student or the Project. We want Project notebooks to appear as a blog post or a data analysis. Bad: *\"In this task, you will...\"* Good: *\"Next, we will...\"*" 165 | ] 166 | }, 167 | { 168 | "cell_type": "code", 169 | "execution_count": null, 170 | "metadata": {}, 171 | "outputs": [], 172 | "source": [ 173 | "%%sql" 174 | ] 175 | }, 176 | { 177 | "cell_type": "markdown", 178 | "metadata": {}, 179 | "source": [ 180 | "## 3. Title of the third task (<= 55 chars) (sentence case)" 181 | ] 182 | }, 183 | { 184 | "cell_type": "markdown", 185 | "metadata": {}, 186 | "source": [ 187 | "Context / background / story / etc. This cell should at most have 800 characters.\n", 188 | "\n", 189 | "The most common error instructors make in **context cells** is referring to the student or the Project. We want Project notebooks to appear as a blog post or a data analysis. Bad: *\"In this task, you will...\"* Good: *\"Next, we will...\"*" 190 | ] 191 | }, 192 | { 193 | "cell_type": "code", 194 | "execution_count": null, 195 | "metadata": {}, 196 | "outputs": [], 197 | "source": [ 198 | "%%sql" 199 | ] 200 | }, 201 | { 202 | "cell_type": "markdown", 203 | "metadata": {}, 204 | "source": [ 205 | "# Rough draft of code for rest of Project\n", 206 | "Please include a rough draft of the code for the rest of your proposed Project below. Use as many code cells as you'd like. No accompanying text (i.e. context) cells required." 207 | ] 208 | }, 209 | { 210 | "cell_type": "code", 211 | "execution_count": null, 212 | "metadata": {}, 213 | "outputs": [], 214 | "source": [ 215 | "%%sql" 216 | ] 217 | } 218 | ], 219 | "metadata": { 220 | "kernelspec": { 221 | "display_name": "Python 3", 222 | "language": "python", 223 | "name": "python3" 224 | }, 225 | "language_info": { 226 | "codemirror_mode": { 227 | "name": "ipython", 228 | "version": 3 229 | }, 230 | "file_extension": ".py", 231 | "mimetype": "text/x-python", 232 | "name": "python", 233 | "nbconvert_exporter": "python", 234 | "pygments_lexer": "ipython3", 235 | "version": "3.7.1" 236 | } 237 | }, 238 | "nbformat": 4, 239 | "nbformat_minor": 2 240 | } 241 | -------------------------------------------------------------------------------- /countries/currencies.csv: -------------------------------------------------------------------------------- 1 | "curr_id","code","basic_unit","curr_code","frac_unit","frac_perbasic" 2 | 1,"AFG","Afghan afghani","AFN","Pul",100 3 | 2,"ALB","Albanian lek","ALL","Qindarke",100 4 | 3,"DZA","Algerian dinar","DZD","Santeem",100 5 | 4,"AND","Euro","EUR","Cent",100 6 | 5,"AGO","Angolan kwanza","AOA","Centimo",100 7 | 6,"AIA","East Caribbean dollar","XCD","Cent",100 8 | 7,"ATG","East Caribbean dollar","XCD","Cent",100 9 | 8,"ARG","Argentine peso","ARS","Centavo",100 10 | 9,"ARM","Armenian dram","AMD","Luma",100 11 | 10,"ABW","Aruban florin","AWG","Cent",100 12 | 11,"AUS","Australian dollar","AUD","Cent",100 13 | 12,"AUT","Euro","EUR","Cent",100 14 | 13,"AZE","Azerbaijani manat","AZN","Qəpik",100 15 | 14,"BHR","Bahraini dinar","BHD","Fils",1000 16 | 15,"BGD","Bangladeshi taka","BDT","Paisa",100 17 | 16,"BRB","Barbadian dollar","BBD","Cent",100 18 | 17,"BLR","New Belarusian ruble","BYN","Kapyeyka",100 19 | 18,"BLR","Old Belarusian ruble","BYR","Kapyeyka",100 20 | 19,"BEL","Euro","EUR","Cent",100 21 | 20,"BLZ","Belize dollar","BZD","Cent",100 22 | 21,"BEN","West African CFA franc","XOF","Centime",100 23 | 22,"BMU","Bermudian dollar","BMD","Cent",100 24 | 23,"BTN","Bhutanese ngultrum","BTN","Chetrum",100 25 | 24,"BTN","Indian rupee","INR","Paisa",100 26 | 25,"BOL","Bolivian boliviano","BOB","Centavo",100 27 | 26,"BIH","Bosnia and Herzegovina convertible mark","BAM","Fening",100 28 | 27,"BWA","Botswana pula","BWP","Thebe",100 29 | 28,"BRA","Brazilian real","BRL","Centavo",100 30 | 29,"IOT","United States dollar","USD","Cent",100 31 | 30,"BRN","Brunei dollar","BND","Sen",100 32 | 31,"BRN","Singapore dollar","SGD","Cent",100 33 | 32,"BGR","Bulgarian lev","BGN","Stotinka",100 34 | 33,"BFA","West African CFA franc","XOF","Centime",100 35 | 34,"BDI","Burundian franc","BIF","Centime",100 36 | 35,"KHM","Cambodian riel","KHR","Sen",100 37 | 36,"KHM","United States dollar","USD","Cent",100 38 | 37,"CMR","Central African CFA franc","XAF","Centime",100 39 | 38,"CAN","Canadian dollar","CAD","Cent",100 40 | 39,"CPV","Cape Verdean escudo","CVE","Centavo",100 41 | 40,"CYM","Cayman Islands dollar","KYD","Cent",100 42 | 41,"CAF","Central African CFA franc","XAF","Centime",100 43 | 42,"TCD","Central African CFA franc","XAF","Centime",100 44 | 43,"CHL","Chilean peso","CLP","Centavo",100 45 | 44,"CHN","Chinese yuan","CNY","Fen",100 46 | 45,"CCK","Australian dollar","AUD","Cent",100 47 | 46,"COL","Colombian peso","COP","Centavo",100 48 | 47,"COM","Comorian franc","KMF","Centime",100 49 | 48,"COD","Congolese franc","CDF","Centime",100 50 | 49,"COG","Central African CFA franc","XAF","Centime",100 51 | 50,"COK","New Zealand dollar","NZD","Cent",100 52 | 51,"CRI","Costa Rican colon","CRC","Centimo",100 53 | 52,"CIV","West African CFA franc","XOF","Centime",100 54 | 53,"HRV","Croatian kuna","HRK","Lipa",100 55 | 54,"CUB","Cuban convertible peso","CUC","Centavo",100 56 | 55,"CUB","Cuban peso","CUP","Centavo",100 57 | 56,"CYP","Euro","EUR","Cent",100 58 | 57,"CZE","Czech koruna","CZK","Haler",100 59 | 58,"DNK","Danish krone","DKK","Ore",100 60 | 59,"DJI","Djiboutian franc","DJF","Centime",100 61 | 60,"DMA","East Caribbean dollar","XCD","Cent",100 62 | 61,"DOM","Dominican peso","DOP","Centavo",100 63 | 62,"TMP","United States dollar","USD","Cent",100 64 | 63,"ECU","United States dollar","USD","Cent",100 65 | 64,"EGY","Egyptian pound","EGP","Piastre",100 66 | 65,"SLV","United States dollar","USD","Cent",100 67 | 66,"GNQ","Central African CFA franc","XAF","Centime",100 68 | 67,"ERI","Eritrean nakfa","ERN","Cent",100 69 | 68,"EST","Euro","EUR","Cent",100 70 | 69,"ETH","Ethiopian birr","ETB","Santim",100 71 | 70,"FLK","Falkland Islands pound","FKP","Penny",100 72 | 71,"FRO","Danish krone","DKK","Ore",100 73 | 72,"FIN","Euro","EUR","Cent",100 74 | 73,"FRA","Euro","EUR","Cent",100 75 | 74,"PYF","CFP franc","XPF","Centime",100 76 | 75,"GAB","Central African CFA franc","XAF","Centime",100 77 | 76,"GEO","Georgian lari","GEL","Tetri",100 78 | 77,"DEU","Euro","EUR","Cent",100 79 | 78,"GHA","Ghanaian cedi","GHS","Pesewa",100 80 | 79,"GIB","Gibraltar pound","GIP","Penny",100 81 | 80,"GRC","Euro","EUR","Cent",100 82 | 81,"GRD","East Caribbean dollar","XCD","Cent",100 83 | 82,"GTM","Guatemalan quetzal","GTQ","Centavo",100 84 | 83,"GIN","Guinean franc","GNF","Centime",100 85 | 84,"GNB","West African CFA franc","XOF","Centime",100 86 | 85,"GUY","Guyanese dollar","GYD","Cent",100 87 | 86,"HTI","Haitian gourde","HTG","Centime",100 88 | 87,"HND","Honduran lempira","HNL","Centavo",100 89 | 88,"HKG","Hong Kong dollar","HKD","Cent",100 90 | 89,"HUN","Hungarian forint","HUF","Filler",100 91 | 90,"ISL","Icelandic krona","ISK","Eyrir",100 92 | 91,"IND","Indian rupee","INR","Paisa",100 93 | 92,"IDN","Indonesian rupiah","IDR","Sen",100 94 | 93,"IRN","Iranian rial","IRR","Dinar",100 95 | 94,"IRQ","Iraqi dinar","IQD","Fils",1000 96 | 95,"IRL","Euro","EUR","Cent",100 97 | 96,"ISR","Israeli new shekel","ILS","Agora",100 98 | 97,"ITA","Euro","EUR","Cent",100 99 | 98,"JAM","Jamaican dollar","JMD","Cent",100 100 | 99,"JPN","Japanese yen","JPY","Sen",100 101 | 100,"JOR","Jordanian dinar","JOD","Piastre",100 102 | 101,"KAZ","Kazakhstani tenge","KZT","Tiin",100 103 | 102,"KEN","Kenyan shilling","KES","Cent",100 104 | 103,"KIR","Australian dollar","AUD","Cent",100 105 | 104,"PRK","North Korean won","KPW","Chon",100 106 | 105,"KOR","South Korean won","KRW","Jeon",100 107 | 106,"KWT","Kuwaiti dinar","KWD","Fils",1000 108 | 107,"KGZ","Kyrgyzstani som","KGS","Tyiyn",100 109 | 108,"LAO","Lao kip","LAK","Att",100 110 | 109,"LVA","Euro","EUR","Cent",100 111 | 110,"LBN","Lebanese pound","LBP","Piastre",100 112 | 111,"LSO","Lesotho loti","LSL","Sente",100 113 | 112,"LSO","South African rand","ZAR","Cent",100 114 | 113,"LBR","Liberian dollar","LRD","Cent",100 115 | 114,"LBY","Libyan dinar","LYD","Dirham",1000 116 | 115,"LIE","Swiss franc","CHF","Rappen",100 117 | 116,"LTU","Euro","EUR","Cent",100 118 | 117,"LUX","Euro","EUR","Cent",100 119 | 118,"MDG","Malagasy ariary","MGA","Iraimbilanja",5 120 | 119,"MWI","Malawian kwacha","MWK","Tambala",100 121 | 120,"MYS","Malaysian ringgit","MYR","Sen",100 122 | 121,"MDV","Maldivian rufiyaa","MVR","Laari",100 123 | 122,"MLI","West African CFA franc","XOF","Centime",100 124 | 123,"MLT","Euro","EUR","Cent",100 125 | 124,"MHL","United States dollar","USD","Cent",100 126 | 125,"MRT","Mauritanian ouguiya","MRO","Khoums",5 127 | 126,"MUS","Mauritian rupee","MUR","Cent",100 128 | 127,"MEX","Mexican peso","MXN","Centavo",100 129 | 128,"MDA","Moldovan leu","MDL","Ban",100 130 | 129,"MCO","Euro","EUR","Cent",100 131 | 130,"MNG","Mongolian togrog","MNT","Mongo",100 132 | 131,"MSR","East Caribbean dollar","XCD","Cent",100 133 | 132,"MAR","Moroccan dirham","MAD","Centime",100 134 | 133,"MOZ","Mozambican metical","MZN","Centavo",100 135 | 134,"MMR","Burmese kyat","MMK","Pya",100 136 | 135,"NAM","Namibian dollar","NAD","Cent",100 137 | 136,"NAM","South African rand","ZAR","Cent",100 138 | 137,"NRU","Australian dollar","AUD","Cent",100 139 | 138,"NPL","Nepalese rupee","NPR","Paisa",100 140 | 139,"NLD","Euro","EUR","Cent",100 141 | 140,"NCL","CFP franc","XPF","Centime",100 142 | 141,"NZL","New Zealand dollar","NZD","Cent",100 143 | 142,"NIC","Nicaraguan cordoba","NIO","Centavo",100 144 | 143,"NER","West African CFA franc","XOF","Centime",100 145 | 144,"NGA","Nigerian naira","NGN","Kobo",100 146 | 145,"NIU","New Zealand dollar","NZD","Cent",100 147 | 146,"NOR","Norwegian krone","NOK","Ore",100 148 | 147,"OMN","Omani rial","OMR","Baisa",1000 149 | 148,"PAK","Pakistani rupee","PKR","Paisa",100 150 | 149,"PLW","United States dollar","USD","Cent",100 151 | 150,"PSE","Israeli new shekel","ILS","Agora",100 152 | 151,"PSE","Jordanian dinar","JOD","Piastre",100 153 | 152,"PAN","Panamanian balboa","PAB","Centesimo",100 154 | 153,"PAN","United States dollar","USD","Cent",100 155 | 154,"PNG","Papua New Guinean kina","PGK","Toea",100 156 | 155,"PRY","Paraguayan guarani","PYG","Centimo",100 157 | 156,"PER","Peruvian sol","PEN","Centimo",100 158 | 157,"PHL","Philippine peso","PHP","Centavo",100 159 | 158,"POL","Polish zloty","PLN","Grosz",100 160 | 159,"PRT","Euro","EUR","Cent",100 161 | 160,"QAT","Qatari riyal","QAR","Dirham",100 162 | 161,"ROM","Romanian leu","RON","Ban",100 163 | 162,"RUS","Russian ruble","RUB","Kopek",100 164 | 163,"RWA","Rwandan franc","RWF","Centime",100 165 | 164,"SHN","Saint Helena pound","SHP","Penny",100 166 | 165,"KNA","East Caribbean dollar","XCD","Cent",100 167 | 166,"LCA","East Caribbean dollar","XCD","Cent",100 168 | 167,"VCT","East Caribbean dollar","XCD","Cent",100 169 | 168,"WSM","Samoan tala","WST","Sene",100 170 | 169,"SMR","Euro","EUR","Cent",100 171 | 170,"SAU","Saudi riyal","SAR","Halala",100 172 | 171,"SEN","West African CFA franc","XOF","Centime",100 173 | 172,"SYC","Seychellois rupee","SCR","Cent",100 174 | 173,"SLE","Sierra Leonean leone","SLL","Cent",100 175 | 174,"SGP","Brunei dollar","BND","Sen",100 176 | 175,"SGP","Singapore dollar","SGD","Cent",100 177 | 176,"SVK","Euro","EUR","Cent",100 178 | 177,"SVN","Euro","EUR","Cent",100 179 | 178,"SLB","Solomon Islands dollar","SBD","Cent",100 180 | 179,"SOM","Somali shilling","SOS","Cent",100 181 | 180,"ZAF","South African rand","ZAR","Cent",100 182 | 181,"SGS","British pound","GBP","Penny",100 183 | 182,"ESP","Euro","EUR","Cent",100 184 | 183,"LKA","Sri Lankan rupee","LKR","Cent",100 185 | 184,"SDN","Sudanese pound","SDG","Piastre",100 186 | 185,"SUR","Surinamese dollar","SRD","Cent",100 187 | 186,"SWZ","Swazi lilangeni","SZL","Cent",100 188 | 187,"SWE","Swedish krona","SEK","Ore",100 189 | 188,"CHE","Swiss franc","CHF","Rappen",100 190 | 189,"SYR","Syrian pound","SYP","Piastre",100 191 | 190,"TWN","New Taiwan dollar","TWD","Cent",100 192 | 191,"TJK","Tajikistani somoni","TJS","Diram",100 193 | 192,"TZA","Tanzanian shilling","TZS","Cent",100 194 | 193,"THA","Thai baht","THB","Satang",100 195 | 194,"TGO","West African CFA franc","XOF","Centime",100 196 | 195,"TON","Tongan paʻanga","TOP","Seniti",100 197 | 196,"TTO","Trinidad and Tobago dollar","TTD","Cent",100 198 | 197,"TUN","Tunisian dinar","TND","Millime",1000 199 | 198,"TUR","Turkish lira","TRY","Kurus",100 200 | 199,"TKM","Turkmenistan manat","TMT","Tennesi",100 201 | 200,"TCA","United States dollar","USD","Cent",100 202 | 201,"TUV","Australian dollar","AUD","Cent",100 203 | 202,"TUV","Tuvaluan dollar","TVD","Cent",100 204 | 203,"UGA","Ugandan shilling","UGX","Cent",100 205 | 204,"UKR","Ukrainian hryvnia","UAH","Kopiyka",100 206 | 205,"UKR","Russian ruble","RUB","Kopek",100 207 | 206,"ARE","United Arab Emirates dirham","AED","Fils",100 208 | 207,"GBR","British pound","GBP","Penny",100 209 | 208,"USA","United States dollar","USD","Cent",100 210 | 209,"URY","Uruguayan peso","UYU","Centesimo",100 211 | 210,"UZB","Uzbekistani soʻm","UZS","Tiyin",100 212 | 211,"VUT","Vanuatu vatu","VUV",, 213 | 212,"VEN","Venezuelan bolivar","VEF","Centimo",100 214 | 213,"VNM","Vietnamese dong","VND","Hao",10 215 | 214,"WLF","CFP franc","XPF","Centime",100 216 | 215,"YEM","Yemeni rial","YER","Fils",100 217 | 216,"ZMB","Zambian kwacha","ZMW","Ngwee",100 218 | 217,"ZWE","Botswana pula","BWP","Thebe",100 219 | 218,"ZWE","British pound","GBP","Penny",100 220 | 219,"ZWE","Chinese yuan","CNY","Fen",100 221 | 220,"ZWE","Euro","EUR","Cent",100 222 | 221,"ZWE","Indian rupee","INR","Paisa",100 223 | 222,"ZWE","Japanese yen","JPY","Sen",100 224 | 223,"ZWE","South African rand","ZAR","Cent",100 225 | 224,"ZWE","United States dollar","USD","Cent",100 226 | -------------------------------------------------------------------------------- /countries/populations.csv: -------------------------------------------------------------------------------- 1 | "pop_id","country_code","year","fertility_rate","life_expectancy","size" 2 | 20,"ABW",2010,1.704,74.9535365853659,101597 3 | 19,"ABW",2015,1.647,75.5735853658537,103889 4 | 2,"AFG",2010,5.746,58.9708292682927,27962207 5 | 1,"AFG",2015,4.653,60.7171707317073,32526562 6 | 12,"AGO",2010,6.416,50.6541707317073,21219954 7 | 11,"AGO",2015,5.996,52.6660975609756,25021974 8 | 4,"ALB",2010,1.663,77.0369512195122,2913021 9 | 3,"ALB",2015,1.793,78.0144634146342,2889167 10 | 10,"AND",2010,1.27,,84419 11 | 9,"AND",2015,,,70473 12 | 409,"ARE",2010,1.868,76.675243902439,8329453 13 | 408,"ARE",2015,1.767,77.541243902439,9156963 14 | 16,"ARG",2010,2.37,75.4849756097561,41222875 15 | 15,"ARG",2015,2.308,76.3342195121951,43416755 16 | 18,"ARM",2010,1.648,74.2263414634146,2963496 17 | 17,"ARM",2015,1.517,74.7971219512195,3017712 18 | 8,"ASM",2010,,,55636 19 | 7,"ASM",2015,,,55538 20 | 14,"ATG",2010,2.13,75.3087804878049,87233 21 | 13,"ATG",2015,2.063,76.1002195121951,91818 22 | 22,"AUS",2010,1.928,81.6951219512195,22031750 23 | 21,"AUS",2015,1.833,82.4512195121951,23789752 24 | 24,"AUT",2010,1.44,80.5804878048781,8363404 25 | 23,"AUT",2015,1.47,81.8439024390244,8638366 26 | 26,"AZE",2010,1.92,70.4513170731707,9054332 27 | 25,"AZE",2015,1.97,70.8487804878049,9649341 28 | 64,"BDI",2010,6.302,54.8291951219512,9461117 29 | 63,"BDI",2015,5.863,57.1070487804878,11178921 30 | 38,"BEL",2010,1.86,80.1829268292683,10895586 31 | 37,"BEL",2015,1.74,81.2878048780488,11249420 32 | 42,"BEN",2010,5.094,58.7297073170732,9509798 33 | 41,"BEN",2015,4.688,59.7207073170732,10879829 34 | 62,"BFA",2010,5.867,57.0513902439024,15632066 35 | 61,"BFA",2015,5.437,58.9312926829268,18105570 36 | 32,"BGD",2010,2.332,70.0802926829268,151616777 37 | 31,"BGD",2015,2.144,72.0011951219512,160995642 38 | 60,"BGR",2010,1.57,73.5121951219512,7395599 39 | 59,"BGR",2015,1.53,74.4658536585366,7177991 40 | 30,"BHR",2010,2.142,76.1275609756098,1261319 41 | 29,"BHR",2015,2.035,76.8190975609756,1377237 42 | 28,"BHS",2010,1.904,74.5923902439024,360830 43 | 27,"BHS",2015,1.861,75.3968292682927,388019 44 | 50,"BIH",2010,1.288,75.8076829268293,3835258 45 | 49,"BIH",2015,1.253,76.5885853658537,3810416 46 | 36,"BLR",2010,1.494,70.4048780487805,9490583 47 | 35,"BLR",2015,1.724,73.6243902439025,9489616 48 | 40,"BLZ",2010,2.714,69.7820487804878,321609 49 | 39,"BLZ",2015,2.546,70.1923658536585,359287 50 | 44,"BMU",2010,1.76,79.2885365853658,65124 51 | 43,"BMU",2015,1.62,81.0121951219512,65235 52 | 48,"BOL",2010,3.2,66.407756097561,9918245 53 | 47,"BOL",2015,2.923,68.7396097560976,10724705 54 | 54,"BRA",2010,1.838,73.2641463414634,198614208 55 | 53,"BRA",2015,1.778,74.6758780487805,207847528 56 | 34,"BRB",2010,1.781,74.8452926829268,279566 57 | 33,"BRB",2015,1.796,75.6584390243903,284215 58 | 58,"BRN",2010,1.953,77.5982682926829,393302 59 | 57,"BRN",2015,1.856,79.0408292682927,423188 60 | 46,"BTN",2010,2.331,67.8924146341463,720246 61 | 45,"BTN",2015,1.984,69.8328536585366,774830 62 | 52,"BWA",2010,2.893,63.4022926829268,2047831 63 | 51,"BWA",2015,2.799,64.4874146341464,2262485 64 | 76,"CAF",2010,4.624,47.6253170731707,4444973 65 | 75,"CAF",2015,4.206,51.4191219512195,4900274 66 | 72,"CAN",2010,1.6269,81.1975609756098,34005274 67 | 71,"CAN",2015,1.6,82.1376341463415,35848610 68 | 377,"CHE",2010,1.52,82.2463414634147,7824909 69 | 376,"CHE",2015,1.54,83.1975609756098,8281430 70 | 80,"CHI",2010,1.436,80.0103658536585,159583 71 | 79,"CHI",2015,1.473,80.7516829268293,163692 72 | 82,"CHL",2010,1.824,80.2758048780488,17015048 73 | 81,"CHL",2015,1.749,81.7875609756098,17948141 74 | 84,"CHN",2010,1.539,75.0074146341463,1337705000 75 | 83,"CHN",2015,1.569,75.9863414634146,1371220000 76 | 96,"CIV",2010,5.231,50.1514634146342,20131707 77 | 95,"CIV",2015,4.937,51.919756097561,22701556 78 | 70,"CMR",2010,5.017,53.6948292682927,20590666 79 | 69,"CMR",2015,4.63,55.9343902439024,23344179 80 | 90,"COD",2010,6.386,56.8961463414634,65938712 81 | 89,"COD",2015,5.908,59.0239024390244,77266814 82 | 92,"COG",2010,5.02,59.1431219512195,4066078 83 | 91,"COG",2015,4.811,62.8676585365854,4620330 84 | 86,"COL",2010,2.01,73.2778536585366,45918101 85 | 85,"COL",2015,1.875,74.1820243902439,48228704 86 | 88,"COM",2010,4.755,61.830512195122,698695 87 | 87,"COM",2015,4.418,63.5540243902439,788474 88 | 66,"CPV",2010,2.464,72.5979024390244,490379 89 | 65,"CPV",2015,2.268,73.3556341463415,520502 90 | 94,"CRI",2010,1.922,78.7360487804878,4545273 91 | 93,"CRI",2015,1.8,79.5864634146341,4807850 92 | 100,"CUB",2010,1.635,78.9356341463415,11308133 93 | 99,"CUB",2015,1.606,79.5464146341464,11389562 94 | 102,"CUW",2010,2.2,,148703 95 | 101,"CUW",2015,1.9,,157979 96 | 74,"CYM",2010,,,55509 97 | 73,"CYM",2015,,,59967 98 | 104,"CYP",2010,1.481,79.3819512195122,1103685 99 | 103,"CYP",2015,1.438,80.3070975609756,1165300 100 | 106,"CZE",2010,1.51,77.4243902439025,10474410 101 | 105,"CZE",2015,1.53,79.4731707317073,10546059 102 | 145,"DEU",2010,1.39,79.9878048780488,81776930 103 | 144,"DEU",2015,1.5,81.090243902439,81679769 104 | 110,"DJI",2010,3.484,60.3606829268293,830802 105 | 109,"DJI",2015,3.131,62.2856585365854,887861 106 | 112,"DMA",2010,,,71167 107 | 111,"DMA",2015,,,72680 108 | 108,"DNK",2010,1.87,79.1,5547683 109 | 107,"DNK",2015,1.69,81.1,5683483 110 | 114,"DOM",2010,2.597,72.7498048780488,9897983 111 | 113,"DOM",2015,2.451,73.6766829268293,10528391 112 | 6,"DZA",2010,2.873,73.8040487804878,36036159 113 | 5,"DZA",2015,2.805,75.0425365853659,39666519 114 | 116,"ECU",2010,2.656,75.0298048780488,14934692 115 | 115,"ECU",2015,2.513,76.1029268292683,16144363 116 | 118,"EGY",2010,3.184,70.3402926829268,82040994 117 | 117,"EGY",2015,3.314,71.3169512195122,91508084 118 | 123,"ERI",2010,4.605,61.4661463414634,4689664 119 | 434,"ERI",2015,4.207,64.1009024390244, 120 | 357,"ESP",2010,1.37,81.6268292682927,46576897 121 | 356,"ESP",2015,1.32,83.3804878048781,46443994 122 | 125,"EST",2010,1.72,75.4292682926829,1331475 123 | 124,"EST",2015,1.54,77.1317073170732,1314608 124 | 127,"ETH",2010,4.903,61.2961219512195,87561814 125 | 126,"ETH",2015,4.275,64.5780487804878,99390750 126 | 133,"FIN",2010,1.87,79.8707317073171,5363352 127 | 132,"FIN",2015,1.71,81.3853658536585,5479531 128 | 131,"FJI",2010,2.669,69.3843658536586,859952 129 | 130,"FJI",2015,2.54,70.2562682926829,892145 130 | 135,"FRA",2010,2.03,81.6634146341463,65027512 131 | 134,"FRA",2015,2.01,82.6707317073171,66538391 132 | 129,"FRO",2010,2.5,80.6390243902439,48567 133 | 128,"FRO",2015,2.4,81.6341463414634,48199 134 | 257,"FSM",2010,3.46,68.6122682926829,103619 135 | 256,"FSM",2015,3.193,69.234243902439,104460 136 | 139,"GAB",2010,4.083,62.1208292682927,1541936 137 | 138,"GAB",2015,3.849,64.8903414634146,1725292 138 | 411,"GBR",2010,1.92,80.4024390243902,62766365 139 | 410,"GBR",2015,1.81,81.6048780487805,65128861 140 | 143,"GEO",2010,1.82,74.0024390243902,3926000 141 | 142,"GEO",2015,1.815,74.8174146341463,3717100 142 | 147,"GHA",2010,4.272,60.6099756097561,24317734 143 | 146,"GHA",2015,4.117,61.4917317073171,27409893 144 | 149,"GIB",2010,,,30732 145 | 148,"GIB",2015,,,32217 146 | 161,"GIN",2010,5.337,56.3050487804878,11012406 147 | 160,"GIN",2015,4.932,59.1934390243903,12608590 148 | 141,"GMB",2010,5.796,59.3406097560976,1693002 149 | 140,"GMB",2015,5.674,60.4676829268293,1990924 150 | 163,"GNB",2010,5.091,53.8143658536585,1634196 151 | 162,"GNB",2015,4.761,55.4673170731707,1844325 152 | 122,"GNQ",2010,5.176,55.971,728710 153 | 121,"GNQ",2015,4.745,57.9634146341463,845060 154 | 151,"GRC",2010,1.48,80.3878048780488,11121341 155 | 150,"GRC",2015,1.3,81.5878048780488,10820883 156 | 155,"GRD",2010,2.24,72.567512195122,104677 157 | 154,"GRD",2015,2.127,73.523,106825 158 | 153,"GRL",2010,2.195,70.8570731707317,56905 159 | 152,"GRL",2015,2,,56114 160 | 159,"GTM",2010,3.434,70.7754634146341,14732261 161 | 158,"GTM",2015,3.159,71.9564878048781,16342897 162 | 157,"GUM",2010,2.472,78.1008780487805,159440 163 | 156,"GUM",2015,2.366,79.379,169885 164 | 165,"GUY",2010,2.68,66.0427073170732,753362 165 | 164,"GUY",2015,2.532,66.5075121951219,767085 166 | 171,"HKG",2010,1.127,82.9780487804878,7024200 167 | 170,"HKG",2015,1.195,84.2780487804878,7305700 168 | 169,"HND",2010,2.695,72.3939756097561,7503875 169 | 168,"HND",2015,2.332,73.3331219512195,8075060 170 | 98,"HRV",2010,1.55,76.4756097560976,4417781 171 | 97,"HRV",2015,1.46,77.2756097560976,4203604 172 | 167,"HTI",2010,3.325,61.2401219512195,9999617 173 | 166,"HTI",2015,2.973,63.073756097561,10711067 174 | 173,"HUN",2010,1.25,74.2073170731707,10000023 175 | 172,"HUN",2015,1.44,75.9609756097561,9843028 176 | 179,"IDN",2010,2.513,68.1471951219512,241613126 177 | 178,"IDN",2015,2.437,69.0716829268293,257563815 178 | 187,"IMN",2010,,,84327 179 | 186,"IMN",2015,,,87780 180 | 177,"IND",2010,2.622,66.5061463414634,1230984504 181 | 176,"IND",2015,2.395,68.3485609756098,1311050527 182 | 185,"IRL",2010,2.05,80.7439024390244,4560155 183 | 184,"IRL",2015,1.94,81.5024390243902,4643740 184 | 181,"IRN",2010,1.765,73.9831707317073,74253373 185 | 180,"IRN",2015,1.685,75.5913414634147,79109272 186 | 183,"IRQ",2010,4.659,68.4901219512195,30868156 187 | 182,"IRQ",2015,4.515,69.5902682926829,36423395 188 | 175,"ISL",2010,2.2,81.8975609756098,318041 189 | 174,"ISL",2015,1.93,82.8609756097561,330815 190 | 189,"ISR",2010,3.03,81.6024390243903,7623600 191 | 188,"ISR",2015,3.09,82.0512195121951,8380100 192 | 191,"ITA",2010,1.46,82.0365853658537,59277417 193 | 190,"ITA",2015,1.37,83.490243902439,60730582 194 | 193,"JAM",2010,2.174,74.8474878048781,2741253 195 | 192,"JAM",2015,2.025,75.7981707317073,2793335 196 | 197,"JOR",2010,3.553,73.4358292682927,6517912 197 | 196,"JOR",2015,3.366,74.2033414634146,7594547 198 | 195,"JPN",2010,1.39,82.8426829268293,128070000 199 | 194,"JPN",2015,1.46,83.8436585365854,126958472 200 | 199,"KAZ",2010,2.6,68.2953658536585,16321581 201 | 198,"KAZ",2015,2.73,72,17544126 202 | 201,"KEN",2010,4.629,58.7186097560976,40328313 203 | 200,"KEN",2015,4.263,62.1337317073171,46050302 204 | 213,"KGZ",2010,3.1,69.3,5447900 205 | 212,"KGZ",2015,3.2,70.6512195121951,5956900 206 | 68,"KHM",2010,2.875,66.3856585365854,14363586 207 | 67,"KHM",2015,2.595,68.6561463414634,15577899 208 | 203,"KIR",2010,3.843,65.3027804878049,102648 209 | 202,"KIR",2015,3.69,66.1478536585366,112423 210 | 361,"KNA",2010,,,52352 211 | 360,"KNA",2015,,,55572 212 | 207,"KOR",2010,1.226,80.5512195121951,49410366 213 | 206,"KOR",2015,1.239,82.1558536585366,50617045 214 | 211,"KWT",2010,2.353,74.1166341463415,3059473 215 | 210,"KWT",2015,2.072,74.6979024390244,3892115 216 | 215,"LAO",2010,3.293,64.3336341463415,6260544 217 | 214,"LAO",2015,2.923,66.5398780487805,6802023 218 | 219,"LBN",2010,1.613,78.4653658536586,4337156 219 | 218,"LBN",2015,1.722,79.6286097560976,5850743 220 | 223,"LBR",2010,5.024,59.4412926829268,3957990 221 | 222,"LBR",2015,4.647,61.1609512195122,4503438 222 | 225,"LBY",2010,2.603,71.7373902439024,6265697 223 | 224,"LBY",2015,2.426,71.8263170731707,6278438 224 | 363,"LCA",2010,1.982,74.4710975609756,177397 225 | 362,"LCA",2015,1.869,75.184512195122,184999 226 | 227,"LIE",2010,1.4,81.8414634146342,36276 227 | 226,"LIE",2015,1.59,82.0731707317073,37531 228 | 359,"LKA",2010,2.203,74.339243902439,20119000 229 | 358,"LKA",2015,2.062,74.9531951219512,20966000 230 | 221,"LSO",2010,3.303,47.4834146341463,2010586 231 | 220,"LSO",2015,3.142,49.9612195121951,2135022 232 | 229,"LTU",2010,1.5,73.2682926829268,3097282 233 | 228,"LTU",2015,1.63,75.119512195122,2904910 234 | 231,"LUX",2010,1.63,80.6317073170732,506953 235 | 230,"LUX",2015,1.5,82.2292682926829,569604 236 | 217,"LVA",2010,1.36,73.4829268292683,2097555 237 | 216,"LVA",2015,1.64,74.1243902439024,1977527 238 | 233,"MAC",2010,1.061,79.6903902439024,534626 239 | 232,"MAC",2015,1.276,80.7660731707317,587606 240 | 365,"MAF",2010,1.82,78.7219512195122,30235 241 | 364,"MAF",2015,1.81,79.4707317073171,31754 242 | 267,"MAR",2010,2.535,72.5769268292683,32107739 243 | 266,"MAR",2015,2.486,74.2893170731707,34377511 244 | 261,"MCO",2010,,,36845 245 | 260,"MCO",2015,,,37731 246 | 259,"MDA",2010,1.274,69.7092682926829,3562045 247 | 258,"MDA",2015,1.248,71.6264390243903,3554108 248 | 237,"MDG",2010,4.654,63.3617317073171,21079532 249 | 236,"MDG",2015,4.35,65.4827804878049,24235390 250 | 243,"MDV",2010,2.209,76.2004878048781,367000 251 | 242,"MDV",2015,2.088,76.979,409163 252 | 255,"MEX",2010,2.356,76.0267804878049,118617542 253 | 254,"MEX",2015,2.213,76.9206829268293,127017224 254 | 249,"MHL",2010,,,52428 255 | 248,"MHL",2015,,,52993 256 | 235,"MKD",2010,1.471,74.7226341463415,2062443 257 | 234,"MKD",2015,1.535,75.4953414634146,2078453 258 | 245,"MLI",2010,6.547,56.1798048780488,15167286 259 | 244,"MLI",2015,6.143,58.4572195121951,17599694 260 | 247,"MLT",2010,1.36,81.3975609756098,414508 261 | 246,"MLT",2015,1.42,81.9463414634146,431874 262 | 271,"MMR",2010,2.386,64.9174878048781,51733013 263 | 270,"MMR",2015,2.177,66.0420731707317,53897154 264 | 265,"MNE",2010,1.767,75.0452926829268,619428 265 | 264,"MNE",2015,1.676,76.3377073170732,622159 266 | 263,"MNG",2010,2.555,67.6038292682927,2712657 267 | 262,"MNG",2015,2.638,69.8212682926829,2959134 268 | 291,"MNP",2010,,,53860 269 | 290,"MNP",2015,,,55070 270 | 269,"MOZ",2010,5.564,53.2269024390244,24321457 271 | 268,"MOZ",2015,5.295,55.371243902439,27977863 272 | 251,"MRT",2010,4.835,62.0061707317073,3591400 273 | 250,"MRT",2015,4.543,63.2028292682927,4067564 274 | 253,"MUS",2010,1.57,72.9673170731707,1250400 275 | 252,"MUS",2015,1.36,74.3531707317073,1262605 276 | 239,"MWI",2010,5.531,56.836243902439,14769824 277 | 238,"MWI",2015,5.048,63.7968536585366,17215232 278 | 241,"MYS",2010,1.998,74.1577804878049,28119500 279 | 240,"MYS",2015,1.931,74.8751707317073,30331007 280 | 273,"NAM",2010,3.605,62.4802926829268,2193643 281 | 272,"NAM",2015,3.473,64.9154390243903,2458830 282 | 281,"NCL",2010,2.17,77.4731707317073,250000 283 | 280,"NCL",2015,2.22,77.7731707317073,273000 284 | 287,"NER",2010,7.667,58.259,16291990 285 | 286,"NER",2015,7.567,61.9690243902439,19899120 286 | 289,"NGA",2010,5.84,51.329512195122,159424742 287 | 288,"NGA",2015,5.587,53.0488780487805,182201962 288 | 285,"NIC",2010,2.428,73.5817317073171,5737722 289 | 284,"NIC",2015,2.231,75.0981219512195,6082032 290 | 279,"NLD",2010,1.79,80.7024390243902,16615394 291 | 278,"NLD",2015,1.71,81.7073170731707,16939923 292 | 293,"NOR",2010,1.95,80.9975609756098,4889252 293 | 292,"NOR",2015,1.75,82.1,5190239 294 | 277,"NPL",2010,2.606,67.9714878048781,26875910 295 | 276,"NPL",2015,2.167,69.9733414634147,28513700 296 | 275,"NRU",2010,,,10025 297 | 274,"NRU",2015,,,12475 298 | 283,"NZL",2010,2.17,80.7024390243902,4350700 299 | 282,"NZL",2015,1.99,81.4568292682927,4595700 300 | 295,"OMN",2010,2.888,76.0528048780488,2943747 301 | 294,"OMN",2015,2.712,77.3241951219512,4490541 302 | 297,"PAK",2010,3.855,65.1625609756098,170043918 303 | 296,"PAK",2015,3.55,66.3769756097561,188924874 304 | 301,"PAN",2010,2.513,76.8636341463415,3620506 305 | 300,"PAN",2015,2.421,77.7672926829268,3929141 306 | 307,"PER",2010,2.545,73.6398048780488,29373644 307 | 306,"PER",2015,2.427,74.7807317073171,31376670 308 | 309,"PHL",2010,3.133,67.7833170731708,93038902 309 | 308,"PHL",2015,2.944,68.406756097561,100699395 310 | 299,"PLW",2010,,,20470 311 | 298,"PLW",2015,2.21,,21291 312 | 303,"PNG",2010,3.985,61.9948292682927,6847517 313 | 302,"PNG",2015,3.705,62.7766829268293,7619321 314 | 311,"POL",2010,1.41,76.2463414634146,38042794 315 | 310,"POL",2015,1.32,78.2048780487805,37986412 316 | 315,"PRI",2010,1.6235,78.4116341463415,3721526 317 | 314,"PRI",2015,1.432,79.5723170731708,3474182 318 | 205,"PRK",2010,2.003,68.9000243902439,24500506 319 | 204,"PRK",2015,1.968,70.3379268292683,25155317 320 | 313,"PRT",2010,1.39,79.0268292682927,10573100 321 | 312,"PRT",2015,1.23,81.5219512195122,10358076 322 | 305,"PRY",2010,2.73,72.3012926829268,6209877 323 | 304,"PRY",2015,2.509,73.0256341463415,6639123 324 | 427,"PSE",2010,4.433,72.2149268292683,3811102 325 | 426,"PSE",2015,4.11,73.0741951219512,4422143 326 | 137,"PYF",2010,2.11,75.6953902439025,268065 327 | 136,"PYF",2015,2.027,76.7524146341463,282764 328 | 317,"QAT",2010,2.104,77.825512195122,1765513 329 | 316,"QAT",2015,2.007,78.7625853658537,2235355 330 | 319,"ROU",2010,1.59,73.4585365853659,20246871 331 | 318,"ROU",2015,1.52,74.9609756097561,19815308 332 | 321,"RUS",2010,1.567,68.8412195121951,142849449 333 | 320,"RUS",2015,1.75,70.9085365853659,144096870 334 | 323,"RWA",2010,4.441,61.4017804878049,10293669 335 | 322,"RWA",2015,3.8,64.5245365853659,11609666 336 | 331,"SAU",2010,2.987,73.7016097560976,28090647 337 | 330,"SAU",2015,2.713,74.4933414634146,31540372 338 | 369,"SDN",2010,4.636,62.0425853658537,36114885 339 | 368,"SDN",2015,4.286,63.7107317073171,40234882 340 | 333,"SEN",2010,5.174,64.0144390243903,12956791 341 | 332,"SEN",2015,5.031,66.8044146341463,15129273 342 | 341,"SGP",2010,1.15,81.5414634146342,5076732 343 | 340,"SGP",2015,1.24,82.5951219512195,5535002 344 | 349,"SLB",2010,4.236,67.0656585365854,526177 345 | 348,"SLB",2015,3.904,68.146243902439,583591 346 | 339,"SLE",2010,5.151,48.2289512195122,5775902 347 | 338,"SLE",2015,4.516,51.3081707317073,6453184 348 | 120,"SLV",2010,2.078,71.6706097560976,6038306 349 | 119,"SLV",2015,1.909,73.0010975609756,6126583 350 | 327,"SMR",2010,,83.1593791574279,30690 351 | 326,"SMR",2015,,,31781 352 | 351,"SOM",2010,6.868,54.0236585365854,9581714 353 | 350,"SOM",2015,6.364,55.6855853658537,10787104 354 | 335,"SRB",2010,1.4,74.3365853658537,7291436 355 | 334,"SRB",2015,1.46,75.4878048780488,7095383 356 | 355,"SSD",2010,5.376,53.6649024390244,10056475 357 | 354,"SSD",2015,4.937,56.111512195122,12339812 358 | 329,"STP",2010,4.789,65.8546829268293,170880 359 | 328,"STP",2015,4.516,66.5137073170732,190344 360 | 371,"SUR",2010,2.465,70.3627317073171,518141 361 | 370,"SUR",2015,2.336,71.2941707317073,542975 362 | 345,"SVK",2010,1.43,75.1121951219512,5391428 363 | 344,"SVK",2015,1.37,77.2121951219512,5423801 364 | 347,"SVN",2010,1.57,79.4219512195122,2048583 365 | 346,"SVN",2015,1.58,81.0780487804878,2063531 366 | 375,"SWE",2010,1.98,81.4512195121951,9378126 367 | 374,"SWE",2015,1.88,82.5512195121951,9799186 368 | 373,"SWZ",2010,3.559,48.345756097561,1193148 369 | 372,"SWZ",2015,3.201,48.8739512195122,1286970 370 | 343,"SXM",2010,,,35474 371 | 342,"SXM",2015,,,38824 372 | 337,"SYC",2010,2.1,73.1975609756098,89770 373 | 336,"SYC",2015,2.3,73.2292682926829,93419 374 | 379,"SYR",2010,3.093,72.3074390243903,20720602 375 | 378,"SYR",2015,2.903,70.0893170731707,18502413 376 | 401,"TCA",2010,,,30993 377 | 400,"TCA",2015,,,34339 378 | 78,"TCD",2010,6.594,49.8620731707317,11896380 379 | 77,"TCD",2015,6.05,51.8733170731707,14037472 380 | 389,"TGO",2010,4.868,57.2815609756098,6390851 381 | 388,"TGO",2015,4.514,60.120756097561,7304578 382 | 385,"THA",2010,1.547,73.6943658536586,66692024 383 | 384,"THA",2015,1.497,74.6011951219512,67959359 384 | 381,"TJK",2010,3.514,68.5633902439025,7581696 385 | 380,"TJK",2015,3.454,69.7684390243903,8481855 386 | 399,"TKM",2010,2.411,65.021243902439,5041995 387 | 398,"TKM",2015,2.275,65.7364390243903,5373502 388 | 387,"TLS",2010,6.235,67.3083902439025,1057122 389 | 386,"TLS",2015,5.615,68.5264146341463,1184765 390 | 391,"TON",2010,3.913,72.1826097560976,103947 391 | 390,"TON",2015,3.678,72.9440487804878,106170 392 | 393,"TTO",2010,1.806,69.7975609756098,1328095 393 | 392,"TTO",2015,1.766,70.5577073170732,1360088 394 | 395,"TUN",2010,2.098,74.6117073170732,10639194 395 | 394,"TUN",2015,2.132,74.9759756097561,11253554 396 | 397,"TUR",2010,2.134,74.0909268292683,72310416 397 | 396,"TUR",2015,2.052,75.4262195121951,78665830 398 | 403,"TUV",2010,,,9827 399 | 402,"TUV",2015,,,9916 400 | 383,"TZA",2010,5.427,61.6256097560976,45648525 401 | 382,"TZA",2015,5.078,65.4874878048781,53470420 402 | 405,"UGA",2010,6.154,55.8366585365854,33149417 403 | 404,"UGA",2015,5.682,59.1790731707317,39032383 404 | 407,"UKR",2010,1.443,70.2653658536586,45870700 405 | 406,"UKR",2015,1.506,71.189512195122,45154029 406 | 415,"URY",2010,2.078,76.3946097560976,3374414 407 | 414,"URY",2015,2.007,77.1382195121951,3431555 408 | 413,"USA",2010,1.931,78.5414634146342,309346863 409 | 412,"USA",2015,1.843,78.7414634146342,321418820 410 | 417,"UZB",2010,2.342,67.8612926829268,28562400 411 | 416,"UZB",2015,2.491,68.4530731707317,31298900 412 | 367,"VCT",2010,2.07,72.3463902439024,109316 413 | 366,"VCT",2015,1.952,73.0523658536585,109462 414 | 421,"VEN",2010,2.472,73.6716097560976,28995745 415 | 420,"VEN",2015,2.34,74.4096097560976,31108083 416 | 56,"VGB",2010,,,27223 417 | 55,"VGB",2015,,,30117 418 | 425,"VIR",2010,1.81,79.1731707317073,106267 419 | 424,"VIR",2015,1.74,79.8731707317073,103574 420 | 423,"VNM",2010,1.946,74.9903658536585,86932500 421 | 422,"VNM",2015,1.96,75.7777317073171,91713300 422 | 419,"VUT",2010,3.499,70.8499512195122,236299 423 | 418,"VUT",2015,3.31,72.1573658536585,264652 424 | 325,"WSM",2010,4.338,72.417,186029 425 | 324,"WSM",2015,4.028,73.7648780487805,193228 426 | 209,"XKX",2010,2.29,69.9,1775680 427 | 208,"XKX",2015,2.09,71.3463414634146,1801800 428 | 429,"YEM",2010,4.703,62.7687317073171,23591972 429 | 428,"YEM",2015,4.043,64.0313902439024,26832215 430 | 353,"ZAF",2010,2.467,54.390756097561,50979432 431 | 352,"ZAF",2015,2.339,57.4409024390244,55011977 432 | 431,"ZMB",2010,5.687,56.3838536585366,13917439 433 | 430,"ZMB",2015,5.284,60.7856829268293,16211767 434 | 433,"ZWE",2010,4.048,49.5746585365854,13973897 435 | 432,"ZWE",2015,3.856,59.1610731707317,15602751 436 | -------------------------------------------------------------------------------- /countries/countries.csv: -------------------------------------------------------------------------------- 1 | "code","country_name","continent","region","surface_area","indep_year","local_name","gov_form","capital","cap_long","cap_lat" 2 | "AFG","Afghanistan","Asia","Southern and Central Asia",652090,1919,"Afganistan/Afqanestan","Islamic Emirate","Kabul",69.1761,34.5228 3 | "NLD","Netherlands","Europe","Western Europe",41526,1581,"Nederland","Constitutional Monarchy","Amsterdam",4.89095,52.3738 4 | "ALB","Albania","Europe","Southern Europe",28748,1912,"Shqiperia","Republic","Tirane",19.8172,41.3317 5 | "DZA","Algeria","Africa","Northern Africa",2381740,1962,"Al-Jaza’ir/Algerie","Republic","Algiers",3.05097,36.7397 6 | "ASM","American Samoa","Oceania","Polynesia",199,,"Amerika Samoa","US Territory","Pago Pago",-170.691,-14.2846 7 | "AND","Andorra","Europe","Southern Europe",468,1278,"Andorra","Parliamentary Coprincipality","Andorra la Vella",1.5218,42.5075 8 | "AGO","Angola","Africa","Central Africa",1246700,1975,"Angola","Republic","Luanda",13.242,-8.81155 9 | "ATG","Antigua and Barbuda","North America","Caribbean",442,1981,"Antigua and Barbuda","Constitutional Monarchy","Saint John's",-61.8456,17.1175 10 | "ARE","United Arab Emirates","Asia","Middle East",83600,1971,"Al-Imarat al-´Arabiya al-Muttahida","Emirate Federation","Abu Dhabi",54.3705,24.4764 11 | "ARG","Argentina","South America","South America",2780400,1816,"Argentina","Federal Republic","Buenos Aires",-58.4173,-34.6118 12 | "ARM","Armenia","Asia","Middle East",29800,1991,"Hajastan","Republic","Yerevan",44.509,40.1596 13 | "ABW","Aruba","North America","Caribbean",193,,"Aruba","Nonmetropolitan Territory of The Netherlands","Oranjestad",-70.0167,12.5167 14 | "AUS","Australia","Oceania","Australia and New Zealand",7741220,1901,"Australia","Constitutional Monarchy, Federation","Canberra",149.129,-35.282 15 | "AZE","Azerbaijan","Asia","Middle East",86600,1991,"Azarbaycan","Federal Republic","Baku",49.8932,40.3834 16 | "BHS","Bahamas","North America","Caribbean",13878,1973,"The Bahamas","Constitutional Monarchy","Nassau",-77.339,25.0661 17 | "BHR","Bahrain","Asia","Middle East",694,1971,"Al-Bahrayn","Monarchy (Emirate)","Manama",50.5354,26.1921 18 | "BGD","Bangladesh","Asia","Southern and Central Asia",143998,1971,"Bangladesh","Republic","Dhaka",90.4113,23.7055 19 | "BRB","Barbados","North America","Caribbean",430,1966,"Barbados","Constitutional Monarchy","Bridgetown",-59.6105,13.0935 20 | "BEL","Belgium","Europe","Western Europe",30518,1830,"Belgie/Belgique","Constitutional Monarchy, Federation","Brussels",4.36761,50.8371 21 | "BLZ","Belize","North America","Central America",22696,1981,"Belize","Constitutional Monarchy","Belmopan",-88.7713,17.2534 22 | "BEN","Benin","Africa","Western Africa",112622,1960,"Benin","Republic","Porto-Novo",2.6323,6.4779 23 | "BMU","Bermuda","North America","North America",53,,"Bermuda","Dependent Territory of the UK","Hamilton",-64.706,32.3293 24 | "BTN","Bhutan","Asia","Southern and Central Asia",47000,1910,"Druk-Yul","Monarchy","Thimphu",89.6177,27.5768 25 | "BOL","Bolivia","South America","South America",1098580,1825,"Bolivia","Republic","La Paz",-66.1936,-13.9908 26 | "BIH","Bosnia and Herzegovina","Europe","Southern Europe",51197,1992,"Bosna i Hercegovina","Federal Republic","Sarajevo",18.4214,43.8607 27 | "BWA","Botswana","Africa","Southern Africa",581730,1966,"Botswana","Republic","Gaborone",25.9201,-24.6544 28 | "BRA","Brazil","South America","South America",8547400,1822,"Brasil","Federal Republic","Brasilia",-47.9292,-15.7801 29 | "GBR","United Kingdom","Europe","British Islands",242900,1066,"United Kingdom","Constitutional Monarchy","London",-0.126236,51.5002 30 | "VGB","Virgin Islands, British","North America","Caribbean",151,,"British Virgin Islands","Dependent Territory of the UK","Road Town",-64.623056,18.431389 31 | "BRN","Brunei","Asia","Southeast Asia",5765,1984,"Brunei Darussalam","Monarchy (Sultanate)","Bandar Seri Begawan",114.946,4.94199 32 | "BGR","Bulgaria","Europe","Eastern Europe",110994,1908,"Balgarija","Republic","Sofia",23.3238,42.7105 33 | "BFA","Burkina Faso","Africa","Western Africa",274000,1960,"Burkina Faso","Republic","Ouagadougou",-1.53395,12.3605 34 | "BDI","Burundi","Africa","Eastern Africa",27834,1962,"Burundi/Uburundi","Republic","Bujumbura",29.3639,-3.3784 35 | "CYM","Cayman Islands","North America","Caribbean",264,,"Cayman Islands","Dependent Territory of the UK","George Town",-81.3857,19.3022 36 | "CHL","Chile","South America","South America",756626,1810,"Chile","Republic","Santiago",-70.6475,-33.475 37 | "CRI","Costa Rica","North America","Central America",51100,1821,"Costa Rica","Republic","San Jose",-84.0089,9.63701 38 | "DJI","Djibouti","Africa","Eastern Africa",23200,1977,"Djibouti/Jibuti","Republic","Djibouti",43.1425,11.5806 39 | "DMA","Dominica","North America","Caribbean",751,1978,"Dominica","Republic","Roseau",-61.39,15.2976 40 | "DOM","Dominican Republic","North America","Caribbean",48511,1844,"Republica Dominicana","Republic","Santo Domingo",-69.8908,18.479 41 | "ECU","Ecuador","South America","South America",283561,1822,"Ecuador","Republic","Quito",-78.5243,-0.229498 42 | "EGY","Egypt","Africa","Northern Africa",1001450,1922,"Misr","Republic","Cairo",31.2461,30.0982 43 | "SLV","El Salvador","North America","Central America",21041,1841,"El Salvador","Republic","San Salvador",-89.2073,13.7034 44 | "ERI","Eritrea","Africa","Eastern Africa",117600,1993,"Ertra","Republic","Asmara",38.9183,15.3315 45 | "ESP","Spain","Europe","Southern Europe",505992,1492,"Espana","Constitutional Monarchy","Madrid",-3.70327,40.4167 46 | "ZAF","South Africa","Africa","Southern Africa",1221040,1910,"South Africa","Republic","Pretoria",28.1871,-25.746 47 | "ETH","Ethiopia","Africa","Eastern Africa",1104300,-1000,"YeItyop´iya","Republic","Addis Ababa",38.7468,9.02274 48 | "FJI","Fiji Islands","Oceania","Melanesia",18274,1970,"Fiji Islands","Republic","Suva",178.399,-18.1149 49 | "PHL","Philippines","Asia","Southeast Asia",300000,1946,"Pilipinas","Republic","Manila",121.035,14.5515 50 | "FRO","Faroe Islands","Europe","Nordic Countries",1399,,"Foroyar","Part of Denmark","Torshavn",-6.91181,61.8926 51 | "GAB","Gabon","Africa","Central Africa",267668,1960,"Le Gabon","Republic","Libreville",9.45162,0.38832 52 | "GMB","Gambia","Africa","Western Africa",11295,1965,"The Gambia","Republic","Banjul",-16.5885,13.4495 53 | "GEO","Georgia","Asia","Middle East",69700,1991,"Sakartvelo","Republic","Tbilisi",44.793,41.71 54 | "GHA","Ghana","Africa","Western Africa",238533,1957,"Ghana","Republic","Accra",-0.20795,5.57045 55 | "GIB","Gibraltar","Europe","Southern Europe",6,,"Gibraltar","Dependent Territory of the UK",,, 56 | "GRD","Grenada","North America","Caribbean",344,1974,"Grenada","Constitutional Monarchy","Saint George's",-61.7449,12.0653 57 | "GRL","Greenland","North America","North America",2166090,,"Kalaallit Nunaat/Gronland","Part of Denmark","Nuuk",-51.7214,64.1836 58 | "GUM","Guam","Oceania","Micronesia",549,,"Guam","US Territory","Agana",144.794,13.4443 59 | "GTM","Guatemala","North America","Central America",108889,1821,"Guatemala","Republic","Guatemala City",-90.5328,14.6248 60 | "GIN","Guinea","Africa","Western Africa",245857,1958,"Guinee","Republic","Conakry",-13.7,9.51667 61 | "GNB","Guinea-Bissau","Africa","Western Africa",36125,1974,"Guine-Bissau","Republic","Bissau",-15.1804,11.8037 62 | "GUY","Guyana","South America","South America",214969,1966,"Guyana","Republic","Georgetown",-58.1548,6.80461 63 | "HTI","Haiti","North America","Caribbean",27750,1804,"Haiti/Dayti","Republic","Port-au-Prince",-72.3288,18.5392 64 | "HND","Honduras","North America","Central America",112088,1838,"Honduras","Republic","Tegucigalpa",-87.4667,15.1333 65 | "HKG","Hong Kong","Asia","Eastern Asia",1075,,"Xianggang/Hong Kong","Special Administrative Region of China",,114.109,22.3964 66 | "IDN","Indonesia","Asia","Southeast Asia",1904570,1945,"Indonesia","Republic","Jakarta",106.83,-6.19752 67 | "IND","India","Asia","Southern and Central Asia",3287260,1947,"Bharat/India","Federal Republic","New Delhi",77.225,28.6353 68 | "IRQ","Iraq","Asia","Middle East",438317,1932,"Al-´Iraq","Republic","Baghdad",44.394,33.3302 69 | "IRN","Iran","Asia","Southern and Central Asia",1648200,1906,"Iran","Islamic Republic","Tehran",51.4447,35.6878 70 | "IRL","Ireland","Europe","British Islands",70273,1921,"Ireland/Eire","Republic","Dublin",-6.26749,53.3441 71 | "ISL","Iceland","Europe","Nordic Countries",103000,1944,"Island","Republic","Reykjavik",-21.8952,64.1353 72 | "ISR","Israel","Asia","Middle East",21056,1948,"Yisra’el/Isra’il","Republic",,35.2035,31.7717 73 | "ITA","Italy","Europe","Southern Europe",301316,1861,"Italia","Republic","Rome",12.4823,41.8955 74 | "AUT","Austria","Europe","Western Europe",83859,1918,"Osterreich","Federal Republic","Vienna",16.3798,48.2201 75 | "JAM","Jamaica","North America","Caribbean",10990,1962,"Jamaica","Constitutional Monarchy","Kingston",-76.792,17.9927 76 | "JPN","Japan","Asia","Eastern Asia",377829,-660,"Nihon/Nippon","Constitutional Monarchy","Tokyo",139.77,35.67 77 | "YEM","Yemen","Asia","Middle East",527968,1918,"Al-Yaman","Republic","Sana'a",44.2075,15.352 78 | "JOR","Jordan","Asia","Middle East",88946,1946,"Al-Urdunn","Constitutional Monarchy","Amman",35.9263,31.9497 79 | "KHM","Cambodia","Asia","Southeast Asia",181035,1953,"Kampuchea","Constitutional Monarchy","Phnom Penh",104.874,11.5556 80 | "CMR","Cameroon","Africa","Central Africa",475442,1960,"Cameroun/Cameroon","Republic","Yaounde",11.5174,3.8721 81 | "CAN","Canada","North America","North America",9970610,1867,"Canada","Constitutional Monarchy, Federation","Ottawa",-75.6919,45.4215 82 | "CPV","Cape Verde","Africa","Western Africa",4033,1975,"Cabo Verde","Republic","Praia",-23.5087,14.9218 83 | "KAZ","Kazakhstan","Asia","Southern and Central Asia",2724900,1991,"Qazaqstan","Republic","Astana",71.4382,51.1879 84 | "KEN","Kenya","Africa","Eastern Africa",580367,1963,"Kenya","Republic","Nairobi",36.8126,-1.27975 85 | "CAF","Central African Republic","Africa","Central Africa",622984,1960,"Centrafrique/Be-Afrika","Republic","Bangui",21.6407,5.63056 86 | "CHN","China","Asia","Eastern Asia",9572900,-1523,"Zhongquo","People'sRepublic","Beijing",116.286,40.0495 87 | "KGZ","Kyrgyzstan","Asia","Southern and Central Asia",199900,1991,"Kyrgyzstan","Republic","Bishkek",74.6057,42.8851 88 | "KIR","Kiribati","Oceania","Micronesia",726,1979,"Kiribati","Republic","Tarawa",172.979,1.32905 89 | "COL","Colombia","South America","South America",1138910,1810,"Colombia","Republic","Bogota",-74.082,4.60987 90 | "COM","Comoros","Africa","Eastern Africa",1862,1975,"Komori/Comores","Republic","Moroni",43.2418,-11.6986 91 | "COG","Congo","Africa","Central Africa",342000,1960,"Congo","Republic","Brazzaville",15.2662,-4.2767 92 | "COD","Congo, The Democratic Republic of the","Africa","Central Africa",2344860,1960,"Republique Democratique du Congo","Republic","Kinshasa",15.3222,-4.325 93 | "PRK","North Korea","Asia","Eastern Asia",120538,1948,"Choson Minjujuui In´min Konghwaguk (Bukhan)","Socialistic Republic","Pyongyang",125.754,39.0319 94 | "KOR","South Korea","Asia","Eastern Asia",99434,1948,"Taehan Min’guk (Namhan)","Republic","Seoul",126.957,37.5323 95 | "GRC","Greece","Europe","Southern Europe",131626,1830,"Ellada","Republic","Athens",23.7166,37.9792 96 | "HRV","Croatia","Europe","Southern Europe",56538,1991,"Hrvatska","Republic","Zagreb",15.9614,45.8069 97 | "CUB","Cuba","North America","Caribbean",110861,1902,"Cuba","Socialistic Republic","Havana",-82.3667,23.1333 98 | "KWT","Kuwait","Asia","Middle East",17818,1961,"Al-Kuwayt","Constitutional Monarchy (Emirate)","Kuwait City",47.9824,29.3721 99 | "CYP","Cyprus","Asia","Middle East",9251,1960,"Kypros/Kibris","Republic","Nicosia",33.3736,35.1676 100 | "LAO","Laos","Asia","Southeast Asia",236800,1953,"Lao","Republic","Vientiane",102.177,18.5826 101 | "LVA","Latvia","Europe","Baltic Countries",64589,1991,"Latvija","Republic","Riga",24.1048,56.9465 102 | "LSO","Lesotho","Africa","Southern Africa",30355,1966,"Lesotho","Constitutional Monarchy","Maseru",27.7167,-29.5208 103 | "LBN","Lebanon","Asia","Middle East",10400,1941,"Lubnan","Republic","Beirut",35.5134,33.8872 104 | "LBR","Liberia","Africa","Western Africa",111369,1847,"Liberia","Republic","Monrovia",-10.7957,6.30039 105 | "LBY","Libya","Africa","Northern Africa",1759540,1951,"Libiya","Socialistic State","Tripoli",13.1072,32.8578 106 | "LIE","Liechtenstein","Europe","Western Europe",160,1806,"Liechtenstein","Constitutional Monarchy","Vaduz",9.52148,47.1411 107 | "LTU","Lithuania","Europe","Baltic Countries",65301,1991,"Lietuva","Republic","Vilnius",25.2799,54.6896 108 | "LUX","Luxembourg","Europe","Western Europe",2586,1867,"Luxembourg/Letzebuerg","Constitutional Monarchy","Luxembourg",6.1296,49.61 109 | "MAC","Macao","Asia","Eastern Asia",18,,"Macau/Aomen","Special Administrative Region of China",,113.55,22.1667 110 | "MDG","Madagascar","Africa","Eastern Africa",587041,1960,"Madagasikara/Madagascar","Federal Republic","Antananarivo",45.7167,-20.4667 111 | "MKD","Macedonia","Europe","Southern Europe",25713,1991,"Makedonija","Republic","Skopje",21.4361,42.0024 112 | "MWI","Malawi","Africa","Eastern Africa",118484,1964,"Malawi","Republic","Lilongwe",33.7703,-13.9899 113 | "MDV","Maldives","Asia","Southern and Central Asia",298,1965,"Dhivehi Raajje/Maldives","Republic","Male",73.5109,4.1742 114 | "MYS","Malaysia","Asia","Southeast Asia",329758,1957,"Malaysia","Constitutional Monarchy, Federation","Kuala Lumpur",101.684,3.12433 115 | "MLI","Mali","Africa","Western Africa",1240190,1960,"Mali","Republic","Bamako",-7.50034,13.5667 116 | "MLT","Malta","Europe","Southern Europe",316,1964,"Malta","Republic","Valletta",14.5189,35.9042 117 | "MAR","Morocco","Africa","Northern Africa",446550,1956,"Al-Maghrib","Constitutional Monarchy","Rabat",-6.8704,33.9905 118 | "MHL","Marshall Islands","Oceania","Micronesia",181,1990,"Marshall Islands/Majol","Republic","Majuro",171.135,7.11046 119 | "MRT","Mauritania","Africa","Western Africa",1025520,1960,"Muritaniya/Mauritanie","Republic","Nouakchott",-15.9824,18.2367 120 | "MUS","Mauritius","Africa","Eastern Africa",2040,1968,"Mauritius","Republic","Port Louis",57.4977,-20.1605 121 | "MEX","Mexico","North America","Central America",1958200,1810,"Mexico","Federal Republic","Mexico City",-99.1276,19.427 122 | "FSM","Micronesia, Federated States of","Oceania","Micronesia",702,1990,"Micronesia","Federal Republic","Palikir",158.185,6.91771 123 | "MDA","Moldova","Europe","Eastern Europe",33851,1991,"Moldova","Republic","Chisinau",28.8497,47.0167 124 | "MCO","Monaco","Europe","Western Europe",1.5,1861,"Monaco","Constitutional Monarchy","Monaco",7.41891,43.7325 125 | "MNG","Mongolia","Asia","Eastern Asia",1566500,1921,"Mongol Uls","Republic","Ulaanbaatar",106.937,47.9129 126 | "MOZ","Mozambique","Africa","Eastern Africa",801590,1975,"Mocambique","Republic","Maputo",32.5713,-25.9664 127 | "MMR","Myanmar","Asia","Southeast Asia",676578,1948,"Myanma Pye","Republic","Naypyidaw",95.9562,21.914 128 | "NAM","Namibia","Africa","Southern Africa",824292,1990,"Namibia","Republic","Windhoek",17.0931,-22.5648 129 | "NRU","Nauru","Oceania","Micronesia",21,1968,"Naoero/Nauru","Republic","Yaren District",166.920867,-0.5477 130 | "NPL","Nepal","Asia","Southern and Central Asia",147181,1769,"Nepal","Constitutional Monarchy","Kathmandu",85.3157,27.6939 131 | "NIC","Nicaragua","North America","Central America",130000,1838,"Nicaragua","Republic","Managua",-86.2734,12.1475 132 | "NER","Niger","Africa","Western Africa",1267000,1960,"Niger","Republic","Niamey",2.1073,13.514 133 | "NGA","Nigeria","Africa","Western Africa",923768,1960,"Nigeria","Federal Republic","Abuja",7.48906,9.05804 134 | "NOR","Norway","Europe","Nordic Countries",323877,1905,"Norge","Constitutional Monarchy","Oslo",10.7387,59.9138 135 | "CIV","Cote d'Ivoire","Africa","Western Africa",322463,1960,"Cote d’Ivoire","Republic","Yamoussoukro",-4.0305,5.332 136 | "OMN","Oman","Asia","Middle East",309500,1951,"´Uman","Monarchy (Sultanate)","Muscat",58.5874,23.6105 137 | "PAK","Pakistan","Asia","Southern and Central Asia",796095,1947,"Pakistan","Republic","Islamabad",72.8,30.5167 138 | "PLW","Palau","Oceania","Micronesia",459,1994,"Belau/Palau","Republic","Koror",134.479,7.34194 139 | "PAN","Panama","North America","Central America",75517,1903,"Panama","Republic","Panama City",-79.5188,8.99427 140 | "PNG","Papua New Guinea","Oceania","Melanesia",462840,1975,"Papua New Guinea/Papua Niugini","Constitutional Monarchy","Port Moresby",147.194,-9.47357 141 | "PRY","Paraguay","South America","South America",406752,1811,"Paraguay","Republic","Asuncion",-57.6362,-25.3005 142 | "PER","Peru","South America","South America",1285220,1821,"Peru/Piruw","Republic","Lima",-77.0465,-12.0931 143 | "MNP","Northern Mariana Islands","Oceania","Micronesia",464,,"Northern Mariana Islands","Commonwealth of the US","Saipan",145.765,15.1935 144 | "PRT","Portugal","Europe","Southern Europe",91982,1143,"Portugal","Republic","Lisbon",-9.13552,38.7072 145 | "PRI","Puerto Rico","North America","Caribbean",8875,,"Puerto Rico","Commonwealth of the US","San Juan",-66,18.23 146 | "POL","Poland","Europe","Eastern Europe",323250,1918,"Polska","Republic","Warsaw",21.02,52.26 147 | "GNQ","Equatorial Guinea","Africa","Central Africa",28051,1968,"Guinea Ecuatorial","Republic","Malabo",8.7741,3.7523 148 | "QAT","Qatar","Asia","Middle East",11000,1971,"Qatar","Monarchy","Doha",51.5082,25.2948 149 | "FRA","France","Europe","Western Europe",551500,843,"France","Republic","Paris",2.35097,48.8566 150 | "PYF","French Polynesia","Oceania","Polynesia",4000,,"Polynesie francaise","Nonmetropolitan Territory of France","Papeete",-149.57,-17.535 151 | "RWA","Rwanda","Africa","Eastern Africa",26338,1962,"Rwanda/Urwanda","Republic","Kigali",30.0587,-1.95325 152 | "SWE","Sweden","Europe","Nordic Countries",449964,836,"Sverige","Constitutional Monarchy","Stockholm",18.0645,59.3327 153 | "KNA","Saint Kitts and Nevis","North America","Caribbean",261,1983,"Saint Kitts and Nevis","Constitutional Monarchy","Basseterre",-62.7309,17.3 154 | "LCA","Saint Lucia","North America","Caribbean",622,1979,"Saint Lucia","Constitutional Monarchy","Castries",-60.9832,14 155 | "VCT","Saint Vincent and the Grenadines","North America","Caribbean",388,1979,"Saint Vincent and the Grenadines","Constitutional Monarchy","Kingstown",-61.2653,13.2035 156 | "DEU","Germany","Europe","Western Europe",357022,1955,"Deutschland","Federal Republic","Berlin",13.4115,52.5235 157 | "SLB","Solomon Islands","Oceania","Melanesia",28896,1978,"Solomon Islands","Constitutional Monarchy","Honiara",159.949,-9.42676 158 | "ZMB","Zambia","Africa","Eastern Africa",752618,1964,"Zambia","Republic","Lusaka",28.2937,-15.3982 159 | "WSM","Samoa","Oceania","Polynesia",2831,1962,"Samoa","Parlementary Monarchy","Apia",-171.752,-13.8314 160 | "SMR","San Marino","Europe","Southern Europe",61,885,"San Marino","Republic","San Marino",12.4486,43.9322 161 | "STP","Sao Tome and Principe","Africa","Central Africa",964,1975,"Sao Tome e Principe","Republic","Sao Tome",6.6071,0.20618 162 | "SAU","Saudi Arabia","Asia","Middle East",2149690,1932,"Al-´Arabiya as-Sa´udiya","Monarchy","Riyadh",46.6977,24.6748 163 | "SEN","Senegal","Africa","Western Africa",196722,1960,"Senegal/Sounougal","Republic","Dakar",-17.4734,14.7247 164 | "SYC","Seychelles","Africa","Eastern Africa",455,1976,"Sesel/Seychelles","Republic","Victoria",55.4466,-4.6309 165 | "SLE","Sierra Leone","Africa","Western Africa",71740,1961,"Sierra Leone","Republic","Freetown",-13.2134,8.4821 166 | "SGP","Singapore","Asia","Southeast Asia",618,1965,"Singapore/Singapura/Xinjiapo/Singapur","Republic","Singapore",103.85,1.28941 167 | "SVK","Slovakia","Europe","Eastern Europe",49012,1993,"Slovensko","Republic","Bratislava",17.1073,48.1484 168 | "SVN","Slovenia","Europe","Southern Europe",20256,1991,"Slovenija","Republic","Ljubljana",14.5044,46.0546 169 | "SOM","Somalia","Africa","Eastern Africa",637657,1960,"Soomaaliya","Republic","Mogadishu",45.3254,2.07515 170 | "LKA","Sri Lanka","Asia","Southern and Central Asia",65610,1948,"Sri Lanka/Ilankai","Republic","Colombo",79.8528,6.92148 171 | "SDN","Sudan","Africa","Northern Africa",2505810,1956,"As-Sudan","Islamic Republic","Khartoum",32.5363,15.5932 172 | "FIN","Finland","Europe","Nordic Countries",338145,1917,"Suomi","Republic","Helsinki",24.9525,60.1608 173 | "SUR","Suriname","South America","South America",163265,1975,"Suriname","Republic","Paramaribo",-55.1679,5.8232 174 | "SWZ","Swaziland","Africa","Southern Africa",17364,1968,"kaNgwane","Monarchy","Mbabane",31.4659,-26.5225 175 | "CHE","Switzerland","Europe","Western Europe",41284,1499,"Schweiz/Suisse/Svizzera/Svizra","Federation","Bern",7.44821,46.948 176 | "SYR","Syria","Asia","Middle East",185180,1941,"Suriya","Republic","Damascus",36.3119,33.5146 177 | "TJK","Tajikistan","Asia","Southern and Central Asia",143100,1991,"Tocikiston","Republic","Dushanbe",68.7864,38.5878 178 | "TZA","Tanzania","Africa","Eastern Africa",883749,1961,"Tanzania","Republic","Dodoma",35.7382,-6.17486 179 | "DNK","Denmark","Europe","Nordic Countries",43094,800,"Danmark","Constitutional Monarchy","Copenhagen",12.5681,55.6763 180 | "THA","Thailand","Asia","Southeast Asia",513115,1350,"Prathet Thai","Constitutional Monarchy","Bangkok",100.521,13.7308 181 | "TGO","Togo","Africa","Western Africa",56785,1960,"Togo","Republic","Lome",1.2255,6.1228 182 | "TON","Tonga","Oceania","Polynesia",650,1970,"Tonga","Monarchy","Nuku'alofa",-175.216,-21.136 183 | "TTO","Trinidad and Tobago","North America","Caribbean",5130,1962,"Trinidad and Tobago","Republic","Port-of-Spain",-61.4789,10.6596 184 | "TCD","Chad","Africa","Central Africa",1284000,1960,"Tchad/Tshad","Republic","N'Djamena",15.0445,12.1048 185 | "CZE","Czech Republic","Europe","Eastern Europe",78866,1993,"¸esko","Republic","Prague",14.4205,50.0878 186 | "TUN","Tunisia","Africa","Northern Africa",163610,1956,"Tunis/Tunisie","Republic","Tunis",10.21,36.7899 187 | "TUR","Turkey","Asia","Middle East",774815,1923,"Turkiye","Republic","Ankara",32.3606,39.7153 188 | "TKM","Turkmenistan","Asia","Southern and Central Asia",488100,1991,"Turkmenostan","Republic","Ashgabat",58.3794,37.9509 189 | "TCA","Turks and Caicos Islands","North America","Caribbean",430,,"The Turks and Caicos Islands","Dependent Territory of the UK","Grand Turk",-71.141389,21.4602778 190 | "TUV","Tuvalu","Oceania","Polynesia",26,1978,"Tuvalu","Constitutional Monarchy","Funafuti",179.089567,-8.6314877 191 | "UGA","Uganda","Africa","Eastern Africa",241038,1962,"Uganda","Republic","Kampala",32.5729,0.314269 192 | "UKR","Ukraine","Europe","Eastern Europe",603700,1991,"Ukrajina","Republic","Kiev",30.5038,50.4536 193 | "HUN","Hungary","Europe","Eastern Europe",93030,1918,"Magyarorszag","Republic","Budapest",19.0408,47.4984 194 | "URY","Uruguay","South America","South America",175016,1828,"Uruguay","Republic","Montevideo",-56.0675,-34.8941 195 | "NCL","New Caledonia","Oceania","Melanesia",18575,,"Nouvelle-Caledonie","Nonmetropolitan Territory of France","Noum'ea",166.464,-22.2677 196 | "NZL","New Zealand","Oceania","Australia and New Zealand",270534,1907,"New Zealand/Aotearoa","Constitutional Monarchy","Wellington",174.776,-41.2865 197 | "UZB","Uzbekistan","Asia","Southern and Central Asia",447400,1991,"Uzbekiston","Republic","Tashkent",69.269,41.3052 198 | "BLR","Belarus","Europe","Eastern Europe",207600,1991,"Belarus","Republic","Minsk",27.5766,53.9678 199 | "VUT","Vanuatu","Oceania","Melanesia",12189,1980,"Vanuatu","Republic","Port-Vila",168.321,-17.7404 200 | "VEN","Venezuela","South America","South America",912050,1811,"Venezuela","Federal Republic","Caracas",-69.8371,9.08165 201 | "RUS","Russian Federation","Europe","Eastern Europe",17075400,1991,"Rossija","Federal Republic","Moscow",37.6176,55.7558 202 | "VNM","Vietnam","Asia","Southeast Asia",331689,1945,"Viet Nam","Socialistic Republic","Hanoi",105.825,21.0069 203 | "EST","Estonia","Europe","Baltic Countries",45227,1991,"Eesti","Republic","Tallinn",24.7586,59.4392 204 | "USA","United States","North America","North America",9363520,1776,"United States","Federal Republic","Washington D.C.",-77.032,38.8895 205 | "VIR","Virgin Islands, U.S.","North America","Caribbean",347,,"Virgin Islands of the United States","US Territory","Charlotte Amalie",-64.8963,18.3358 206 | "ZWE","Zimbabwe","Africa","Eastern Africa",390757,1980,"Zimbabwe","Republic","Harare",31.0672,-17.8312 207 | "PSE","Palestine","Asia","Middle East",6257,,"Filastin","Autonomous Area",,, 208 | -------------------------------------------------------------------------------- /countries/economies.csv: -------------------------------------------------------------------------------- 1 | "econ_id","code","year","income_group","gdp_percapita","gross_savings","inflation_rate","total_investment","unemployment_rate","exports","imports" 2 | 1,"AFG",2010,"Low income",539.667,37.133,2.179,30.402,,46.394,24.381 3 | 2,"AFG",2015,"Low income",615.091,21.466,-1.549,18.602,,-49.11,-7.294 4 | 3,"AGO",2010,"Upper middle income",3599.27,23.534,14.48,14.433,,-3.266,-21.076 5 | 4,"AGO",2015,"Upper middle income",3876.2,-0.425,10.287,9.552,,6.721,-21.778 6 | 5,"ALB",2010,"Upper middle income",4098.13,20.011,3.605,31.305,14,10.645,-8.013 7 | 6,"ALB",2015,"Upper middle income",3943.22,13.84,1.896,24.598,17.1,1.827,0.574 8 | 7,"ARE",2010,"High income",34628.63,27.073,0.878,27.372,,3.843,-0.981 9 | 8,"ARE",2015,"High income",38649.91,34.106,4.07,27.477,,7.32,2.17 10 | 9,"ARG",2010,"Upper middle income",10412.95,17.361,10.461,17.706,7.75,13.931,39.877 11 | 10,"ARG",2015,"Upper middle income",14643.92,14.111,,16.89,,-1.658,3.105 12 | 11,"ARM",2010,"Lower middle income",3121.78,15.797,7.274,29.419,19,30.183,4.09 13 | 12,"ARM",2015,"Lower middle income",3520.95,18.306,3.731,20.956,18.5,15.729,-9.647 14 | 13,"ATG",2010,"High income",13531.78,13.398,3.37,,,-3.241,-14.113 15 | 14,"ATG",2015,"High income",15155.16,18.754,0.969,,,6.026,-24.307 16 | 15,"AUS",2010,"High income",56362.84,23.584,2.863,27.089,5.208,5.782,15.208 17 | 16,"AUS",2015,"High income",51363.9,22.111,1.461,26.304,6.058,6.022,1.99 18 | 17,"AUT",2010,"High income",46757.13,25.521,1.694,22.654,4.8,13.84,11.989 19 | 18,"AUT",2015,"High income",43749.55,25.353,0.81,23.507,5.75,3.558,3.382 20 | 19,"AZE",2010,"Upper middle income",5847.26,46.567,5.666,18.532,6.048,-1.792,-1.459 21 | 20,"AZE",2015,"Upper middle income",5396.41,26.4,4.049,26.783,6.048,4.08,0.186 22 | 21,"BDI",2010,"Low income",242.84,3.723,6.496,15.086,,33.917,86.968 23 | 22,"BDI",2015,"Low income",318.611,-11.014,5.553,11,,-8.678,-20.535 24 | 23,"BEL",2010,"High income",44691.32,24.456,2.334,22.692,8.317,8.121,6.385 25 | 24,"BEL",2015,"High income",40520.1,23.653,0.62,23.211,8.492,1.154,-0.093 26 | 25,"BEN",2010,"Low income",734.278,14.905,2.179,23.132,,-1.008,9.397 27 | 26,"BEN",2015,"Low income",763.882,17.567,0.271,25.972,,-8.991,-19.18 28 | 27,"BFA",2010,"Low income",588.584,15.788,-0.608,18.02,,175.541,44.066 29 | 28,"BFA",2015,"Low income",619.861,5.31,0.914,13.34,,-14.969,-0.968 30 | 29,"BGD",2010,"Lower middle income",807.531,29.141,9.365,26.874,,18.81,22.43 31 | 30,"BGD",2015,"Lower middle income",1292.93,29.707,6.161,29.149,,8.787,10.5 32 | 31,"BGR",2010,"Upper middle income",6743.74,20.845,3.039,22.568,10.306,11.046,-0.932 33 | 32,"BGR",2015,"Upper middle income",7017.11,21.056,-1.067,21.19,9.235,5.737,5.443 34 | 33,"BHR",2010,"High income",20823.22,36.206,1.97,27.286,3.6,2.083,5.06 35 | 34,"BHR",2015,"High income",24057.58,21.955,1.836,24.372,,0.397,-14.177 36 | 35,"BHS",2010,"High income",22957.79,15.141,1.621,25.214,15.082,2.549,-4.618 37 | 36,"BHS",2015,"High income",24309.57,11.243,1.879,27.222,13.379,-9.46,-5.834 38 | 37,"BIH",2010,"Upper middle income",4404.37,10.115,2.123,15.553,27.202,11.05,-1.953 39 | 38,"BIH",2015,"Upper middle income",4206.69,10.217,-1.018,15.907,27.7,7.606,2.101 40 | 39,"BLR",2010,"Upper middle income",6023.15,26.186,7.743,40.656,0.827,7.669,12.225 41 | 40,"BLR",2015,"Upper middle income",5941.24,25.419,13.523,29.035,0.912,1.304,-12.183 42 | 41,"BLZ",2010,"Upper middle income",4321.29,10.33,0.918,12.792,13.502,8.491,6.964 43 | 42,"BLZ",2015,"Upper middle income",4757.11,12.155,-0.862,22.014,10.114,2.025,6.743 44 | 43,"BOL",2010,"Lower middle income",1994.91,24.969,2.502,17.007,4.375,28.526,8.836 45 | 44,"BOL",2015,"Lower middle income",3099.22,13.31,4.061,19.237,4,-8.427,-2.965 46 | 45,"BRA",2010,"Upper middle income",11297.84,18.368,5.039,21.801,8.556,7.124,34.532 47 | 46,"BRA",2015,"Upper middle income",8810.5,15.865,9.03,19.133,8.3,8.085,-13.47 48 | 47,"BRB",2010,"High income",16079.89,8.12,5.824,13.564,10.25,4.769,-0.489 49 | 48,"BRB",2015,"High income",15808.09,7.473,-1.061,13.391,11.3,6.952,12.81 50 | 49,"BRN",2010,"High income",35437.22,,0.216,41.711,,11.705,-3.108 51 | 50,"BRN",2015,"High income",30994.98,,-0.423,35.247,6.9,-13.765,-24.068 52 | 51,"BTN",2010,"Lower middle income",1998.75,44.674,5.726,66.906,3.3,-0.579,25.991 53 | 52,"BTN",2015,"Lower middle income",2603.1,32.024,6.336,60.362,3.2,1.505,15.832 54 | 53,"BWA",2010,"Upper middle income",6853.67,32.162,6.95,35.353,,16.022,6.481 55 | 54,"BWA",2015,"Upper middle income",6780.97,40.026,3.054,32.11,,-17.111,0.37 56 | 55,"CAF",2010,"Low income",456.564,4.115,1.491,14.266,,10.301,13.882 57 | 56,"CAF",2015,"Low income",332.366,4.882,4.5,13.923,,0.465,12.874 58 | 57,"CAN",2010,"High income",47512.68,19.898,1.769,23.508,8,6.645,13.774 59 | 58,"CAN",2015,"High income",43349.62,20.416,1.132,23.817,6.9,3.393,0.336 60 | 59,"CHE",2010,"High income",74570.66,38.881,0.684,24.027,3.516,12.547,7.882 61 | 60,"CHE",2015,"High income",81410.02,34.52,-1.14,22.995,3.178,2.168,4.303 62 | 61,"CHL",2010,"High income",12789.76,24.839,1.408,23.144,8.153,2.357,25.554 63 | 62,"CHL",2015,"High income",13469.47,21.306,4.349,23.291,6.214,-1.872,-2.802 64 | 63,"CHN",2010,"Upper middle income",4524.06,51.802,3.3,47.881,4.14,25.641,19.925 65 | 64,"CHN",2015,"Upper middle income",8166.76,47.457,1.441,44.748,4.05,-2.216,-0.478 66 | 65,"CIV",2010,"Lower middle income",1195.44,16.765,1.366,14.901,,-7.681,1.856 67 | 66,"CIV",2015,"Lower middle income",1381.81,16.82,1.244,17.804,,2.774,19.427 68 | 67,"CMR",2010,"Lower middle income",1158.78,17.524,1.279,20.281,,-4.699,-1.617 69 | 68,"CMR",2015,"Lower middle income",1230.38,17.088,2.683,21.336,,16.087,2.879 70 | 69,"COD",2010,"Low income",292.955,15.574,23.464,13.75,,54.001,35.575 71 | 70,"COD",2015,"Low income",471.306,16.495,0.959,20.403,,-4.995,-3.984 72 | 71,"COG",2010,"Lower middle income",3183.68,27.651,0.392,19.848,,13.299,21.024 73 | 72,"COG",2015,"Lower middle income",1958.1,-8.049,2.742,34.83,,-6.289,2.196 74 | 73,"COL",2010,"Upper middle income",6305.29,19.107,2.272,22.126,11.792,1.264,10.845 75 | 74,"COL",2015,"Upper middle income",6047.97,20.23,4.99,26.72,8.925,-3.225,-6.321 76 | 75,"COM",2010,"Low income",789.466,15.22,3.899,15.403,,8.524,2.157 77 | 76,"COM",2015,"Low income",736.406,19.221,2,18.411,,7.238,-3.58 78 | 77,"CPV",2010,"Lower middle income",3413.26,25.257,2.079,37.684,10.7,0.873,-0.6 79 | 78,"CPV",2015,"Lower middle income",3001.29,37.094,0.125,41.483,10,-4.248,-19.31 80 | 79,"CRI",2010,"Upper middle income",8300.69,16.489,5.665,19.715,7.345,9.099,18.711 81 | 80,"CRI",2015,"Upper middle income",11435.97,15.725,0.802,20.218,9.249,0.001,4.629 82 | 81,"CYP",2010,"High income",31262.53,12.507,2.557,23.663,6.283,4.452,7.965 83 | 82,"CYP",2015,"High income",23105.4,11.55,-1.539,13.956,14.892,0.032,2.128 84 | 83,"CZE",2010,"High income",19787.29,23.588,1.491,27.174,7.279,14.847,14.899 85 | 84,"CZE",2015,"High income",17569.89,28.266,0.335,27.357,5.046,7.703,8.22 86 | 85,"DEU",2010,"High income",42641.68,25.241,1.149,19.626,6.942,14.534,12.85 87 | 86,"DEU",2015,"High income",41197.41,27.571,0.134,19.243,4.608,5.161,5.467 88 | 87,"DJI",2010,"Lower middle income",1306.54,24.089,3.954,21.259,,1.368,-20.199 89 | 88,"DJI",2015,"Lower middle income",1788.36,19.039,2.104,50.82,,12.843,31.171 90 | 89,"DMA",2010,"Upper middle income",6975.99,2.462,2.81,18.38,,11.788,-6.675 91 | 90,"DMA",2015,"Upper middle income",7311.65,8.814,-0.794,16.787,,8.783,5.578 92 | 91,"DNK",2010,"High income",58177.16,24.639,2.311,18.076,7.483,2.94,0.541 93 | 92,"DNK",2015,"High income",53237.28,28.91,0.452,19.755,6.192,1.833,1.261 94 | 93,"DOM",2010,"Upper middle income",5685.77,18.745,6.33,26.178,5.001,12.363,14.755 95 | 94,"DOM",2015,"Upper middle income",6833.24,21.447,0.837,23.494,5.94,7.284,10.571 96 | 95,"DZA",2010,"Upper middle income",4480.72,49.869,3.913,42.328,9.961,-3.218,-1.781 97 | 96,"DZA",2015,"Upper middle income",4123.3,34.738,4.784,51.299,11.214,5.733,-7.507 98 | 97,"ECU",2010,"Upper middle income",4633.25,25.757,3.552,28.037,5.019,1.109,14.283 99 | 98,"ECU",2015,"Upper middle income",6153.8,24.657,3.97,26.854,4.77,2.195,-7.794 100 | 99,"EGY",2010,"Lower middle income",2921.76,19.421,11.69,21.298,9.21,3.628,11.663 101 | 100,"EGY",2015,"Lower middle income",3731.18,10.62,10.994,14.289,12.859,12.456,10.42 102 | 101,"ERI",2010,"Low income",395.645,-9.257,11.228,9.299,,18.085,11.854 103 | 102,"ERI",2015,"Low income",741.363,1.329,9,7.614,,-16.905,0.809 104 | 103,"ESP",2010,"High income",30802.85,19.628,1.799,23.549,19.858,9.43,6.92 105 | 104,"ESP",2015,"High income",25717.56,21.429,-0.497,20.06,22.058,4.862,5.637 106 | 105,"EST",2010,"High income",14654.28,23.087,2.741,21.265,16.707,24.282,21.218 107 | 106,"EST",2015,"High income",17111.3,25.422,0.068,24.745,6.104,-0.61,-1.404 108 | 107,"ETH",2010,"Low income",360.829,24.494,8.134,25.524,,15.711,33.327 109 | 108,"ETH",2015,"Low income",720.617,31.269,10.115,39.417,,2.161,26.761 110 | 109,"FIN",2010,"High income",46391.71,22.843,1.686,21.6,8.5,6.179,6.5 111 | 110,"FIN",2015,"High income",42487.05,20.728,-0.156,21.144,9.375,2.004,3.123 112 | 111,"FJI",2010,"Upper middle income",3780.24,,3.689,18.102,8.9,, 113 | 112,"FJI",2015,"Upper middle income",4928.9,,1.376,16.281,8.75,, 114 | 113,"FRA",2010,"High income",42249.06,21.075,1.737,21.911,9.258,9.016,8.865 115 | 114,"FRA",2015,"High income",37612.91,22.163,0.09,22.363,10.367,6.149,6.633 116 | 115,"FSM",2010,"Lower middle income",2888.18,,3.701,,,, 117 | 116,"FSM",2015,"Lower middle income",3079.22,,-0.158,,,, 118 | 117,"GAB",2010,"Upper middle income",8917.32,41.009,1.447,26.105,,8.5,12.244 119 | 118,"GAB",2015,"Upper middle income",7746.75,29.315,-0.143,34.821,,19.776,-10.492 120 | 119,"GBR",2010,"High income",38737.56,13.233,3.302,15.976,7.9,5.793,8.155 121 | 120,"GBR",2015,"High income",43976.42,12.952,0.05,17.18,5.4,6.064,5.505 122 | 121,"GEO",2010,"Upper middle income",2951.24,11.64,7.111,21.586,16.291,5.994,-0.239 123 | 122,"GEO",2015,"Upper middle income",3761.91,20.136,4.005,32.06,11.95,1.772,9.838 124 | 123,"GHA",2010,"Lower middle income",1357.64,17.276,6.698,25.885,,13.58,32.634 125 | 124,"GHA",2015,"Lower middle income",1390.11,17.146,17.153,24.83,,-8.625,-1.159 126 | 125,"GIN",2010,"Low income",435.728,0.135,15.466,9.42,,-9.893,9.111 127 | 126,"GIN",2015,"Low income",545.779,-9.697,8.151,10.538,,-0.851,12.326 128 | 127,"GMB",2010,"Low income",562.2,5.026,5.049,21.319,,0.299,7.804 129 | 128,"GMB",2015,"Low income",448.158,4.687,6.808,19.699,,-11.794,6.161 130 | 129,"GNB",2010,"Low income",582.54,-2.057,1.071,6.579,,1.986,8.125 131 | 130,"GNB",2015,"Low income",639.508,9.374,1.481,9.912,,-6.844,10.651 132 | 131,"GNQ",2010,"Upper middle income",23411.83,41.231,5.32,70.449,,-5.481,33.042 133 | 132,"GNQ",2015,"Upper middle income",17286.92,54.939,1.695,74.17,,0.924,8.22 134 | 133,"GRC",2010,"High income",26972.87,5.664,4.704,17.048,12.725,4.861,-3.431 135 | 134,"GRC",2015,"High income",17955.19,9.783,-1.094,9.829,24.9,3.359,0.309 136 | 135,"GRD",2010,"Upper middle income",7365.67,-1.702,3.437,22.012,,-11.5,0.642 137 | 136,"GRD",2015,"Upper middle income",9221.75,0.231,-0.589,17.966,,5.952,17.768 138 | 137,"GTM",2010,"Lower middle income",2875.31,12.575,3.86,13.938,,3.667,9.244 139 | 138,"GTM",2015,"Lower middle income",3921.87,13.115,2.389,13.433,,4.29,15.124 140 | 139,"GUY",2010,"Upper middle income",3004.23,7.88,4.302,17.484,,-4.566,2.84 141 | 140,"GUY",2015,"Upper middle income",4150.57,8.214,-0.865,13.911,,7.358,21.614 142 | 141,"HKG",2010,"High income",32421.07,30.892,2.312,23.89,4.322,17.57,18.228 143 | 142,"HKG",2015,"High income",42327.59,24.858,3.037,21.541,3.296,-1.377,-1.751 144 | 143,"HND",2010,"Lower middle income",2096.2,17.547,4.699,21.88,4.8,19.957,3.68 145 | 144,"HND",2015,"Lower middle income",2567.05,18.403,3.158,24.633,4,1.977,9.353 146 | 145,"HRV",2010,"High income",13505.03,20.278,1.031,21.35,17.167,6.168,-2.468 147 | 146,"HRV",2015,"High income",11578.54,23.894,-0.464,18.794,17.067,10.046,9.429 148 | 147,"HTI",2010,"Low income",662.013,23.869,4.136,25.407,,-4.112,40.547 149 | 148,"HTI",2015,"Low income",809.672,29.277,7.524,32.399,,7.658,10.177 150 | 149,"HUN",2010,"High income",13007.56,20.992,4.867,20.713,11.251,11.304,10.154 151 | 150,"HUN",2015,"High income",12344.16,25.102,-0.07,21.715,6.848,7.671,6.104 152 | 151,"IDN",2010,"Lower middle income",3178.13,33.582,5.14,32.88,7.14,3.109,18.251 153 | 152,"IDN",2015,"Lower middle income",3370.93,32.14,6.363,34.174,6.18,0.397,-6.225 154 | 153,"IND",2010,"Lower middle income",1429.6,33.689,9.497,36.502,,26.023,14.74 155 | 154,"IND",2015,"Lower middle income",1615.79,31.689,4.908,32.747,,-4.437,1.961 156 | 155,"IRL",2010,"High income",48439.1,16.039,-1.636,17.24,13.917,5.71,0.813 157 | 156,"IRL",2015,"High income",60896.18,31.998,-0.017,21.763,9.442,34.452,21.674 158 | 157,"IRN",2010,"Upper middle income",6252.52,41.522,12.403,37.131,13.5,5.768,-0.075 159 | 158,"IRN",2015,"Upper middle income",4709.65,34.511,11.915,32.101,11,23.77,-8.313 160 | 159,"IRQ",2010,"Upper middle income",4473.71,23.736,2.445,,,, 161 | 160,"IRQ",2015,"Upper middle income",5114.49,17.971,1.393,,,, 162 | 161,"ISL",2010,"High income",41622.66,7.256,5.396,13.857,7.558,0.984,4.408 163 | 162,"ISL",2015,"High income",50472.94,24.552,1.633,19.081,3.992,9.172,13.503 164 | 163,"ISR",2010,"High income",30673.39,22.064,2.694,18.499,8.25,15.195,15.116 165 | 164,"ISR",2015,"High income",35743.46,24.296,-0.632,19.948,5.275,-4.3,-0.501 166 | 165,"ITA",2010,"High income",35969.19,17.121,1.62,20.538,8.35,11.786,12.392 167 | 166,"ITA",2015,"High income",30032.11,18.934,0.108,17.314,11.908,4.352,6.821 168 | 167,"JAM",2010,"Upper middle income",4812.07,13.41,12.613,20.199,12.375,-14.814,-17.316 169 | 168,"JAM",2015,"Upper middle income",5052.68,12.111,3.683,14.614,13.5,21.67,20.353 170 | 169,"JOR",2010,"Upper middle income",4322.82,18.381,4.846,25.514,12.5,12.452,-4.01 171 | 170,"JOR",2015,"Upper middle income",5505.7,10.146,-0.877,19.243,13.075,-7.433,-3.135 172 | 171,"JPN",2010,"High income",44673.61,25.174,-0.721,21.298,5.058,24.911,11.173 173 | 172,"JPN",2015,"High income",34513.36,26.99,0.793,23.896,3.375,3.03,0.128 174 | 173,"KAZ",2010,"Upper middle income",9008.71,26.309,7.126,25.374,5.783,24.996,8.207 175 | 174,"KAZ",2015,"Upper middle income",10427.66,26.533,6.656,29.496,5.042,-28.015,-6.335 176 | 175,"KEN",2010,"Lower middle income",1038.95,14.809,4.309,20.735,,8.744,8.113 177 | 176,"KEN",2015,"Lower middle income",1439.46,14.392,6.582,21.206,,-0.863,-1.168 178 | 177,"KGZ",2010,"Lower middle income",875.264,24.869,7.968,27.054,8.644,-11.447,-13.785 179 | 178,"KGZ",2015,"Lower middle income",1109.43,18.333,6.503,29.407,7.554,-6.98,-14.544 180 | 179,"KHM",2010,"Lower middle income",781.912,10.521,3.997,17.368,,33.854,8.385 181 | 180,"KHM",2015,"Lower middle income",1144.5,11.798,1.225,22.4,,12.522,12.504 182 | 181,"KIR",2010,"Lower middle income",1490.9,,-3.9,,,-17.912,-9.924 183 | 182,"KIR",2015,"Lower middle income",1409.63,,0.572,,,4.058,9.646 184 | 183,"KNA",2010,"High income",13466.83,13.133,0.851,33.552,,13.827,-4.746 185 | 184,"KNA",2015,"High income",15765.53,17.742,-2.302,26.209,,13.052,10.902 186 | 185,"KOR",2010,"High income",22086.95,34.659,2.939,32.023,3.725,12.697,17.256 187 | 186,"KOR",2015,"High income",27105.08,36.58,0.706,28.918,3.642,-0.131,2.094 188 | 187,"KWT",2010,"High income",32216.41,50.831,4.496,17.659,2.072,-0.497,6.33 189 | 188,"KWT",2015,"High income",27756.41,31.649,3.233,25.004,2.072,0.961,5.095 190 | 189,"LAO",2010,"Lower middle income",1069.75,,5.984,,,15.707,9.241 191 | 190,"LAO",2015,"Lower middle income",1786.94,,1.292,,,6.652,-0.952 192 | 191,"LBN",2010,"Upper middle income",8755.85,3.847,3.983,,,-18.267,-1.825 193 | 192,"LBN",2015,"Upper middle income",11156.01,3.82,-3.749,,,14.12,9.557 194 | 193,"LBR",2010,"Low income",341.985,,7.291,,,-0.398,10.189 195 | 194,"LBR",2015,"Low income",474.357,,7.742,,,0.328,-2.613 196 | 195,"LBY",2010,"Upper middle income",12149.59,,2.458,39.086,,-0.838,9.906 197 | 196,"LBY",2015,"Upper middle income",4708.14,,9.839,44.578,,-12.88,17.56 198 | 197,"LCA",2010,"Upper middle income",7491.66,11.734,3.25,28.06,,5.423,18.427 199 | 198,"LCA",2015,"Upper middle income",8256.22,17.103,-0.985,19.671,,12.683,1.26 200 | 199,"LKA",2010,"Lower middle income",2779.74,28.457,6.218,30.352,5,13.791,16.52 201 | 200,"LKA",2015,"Lower middle income",3849.22,27.586,0.932,30.059,4,2.715,16.55 202 | 201,"LSO",2010,"Lower middle income",1364.36,16.421,3.382,8.992,,6.135,2.384 203 | 202,"LSO",2015,"Lower middle income",1223.37,30.116,4.958,9.442,,14.6,9.266 204 | 203,"LTU",2010,"High income",12010.68,17.671,1.191,18,17.814,18.942,18.671 205 | 204,"LTU",2015,"High income",14259.6,17.555,-0.677,19.89,9.119,-0.376,6.2 206 | 205,"LUX",2010,"High income",105573.58,24.899,2.795,18.19,5.867,6.498,6.775 207 | 206,"LUX",2015,"High income",100950.49,24.865,0.061,19.625,6.804,12.812,14.046 208 | 207,"LVA",2010,"High income",11228.13,21.365,-1.224,19.314,19.467,13.443,12.412 209 | 208,"LVA",2015,"High income",13614.47,21.325,0.213,22.091,9.877,2.576,2.07 210 | 209,"MAC",2010,"High income",50921.11,,2.795,13.302,2.825,, 211 | 210,"MAC",2015,"High income",70214.9,,4.564,25.087,1.825,, 212 | 211,"MAR",2010,"Lower middle income",2926.67,29.7,0.994,34.074,9.063,24.673,-1.514 213 | 212,"MAR",2015,"Lower middle income",3002.5,28.079,1.545,30.232,9.707,1.753,-2.077 214 | 213,"MDA",2010,"Lower middle income",1632.78,16.001,7.358,23.524,7.4,17,14 215 | 214,"MDA",2015,"Lower middle income",1828.37,17.961,9.628,22.917,4.9,1,-5 216 | 215,"MDG",2010,"Low income",414.143,13.74,9.247,23.424,,-5.288,-25.476 217 | 216,"MDG",2015,"Low income",402.067,11.15,7.404,13.057,,-3.018,-3.427 218 | 217,"MDV",2010,"Upper middle income",7259.49,6.844,6.159,15,,-1.116,31.342 219 | 218,"MDV",2015,"Upper middle income",9178.05,9.798,1.367,20,,-5.757,0.225 220 | 219,"MEX",2010,"Upper middle income",9199.8,21.555,4.155,22.056,5.273,20.547,20.461 221 | 220,"MEX",2015,"Upper middle income",9512.27,20.019,2.72,22.916,4.35,10.3,8.641 222 | 221,"MHL",2010,"Upper middle income",3113.18,,1.768,,,25.911, 223 | 222,"MHL",2015,"Upper middle income",3325.76,,-2.169,,,6.204, 224 | 223,"MKD",2010,"Upper middle income",4576.23,22.443,1.508,,32.05,23.68,10.367 225 | 224,"MKD",2015,"Upper middle income",4854.21,29.029,-0.3,,26.05,6.717,5.24 226 | 225,"MLI",2010,"Low income",764.957,13.306,1.289,24.026,,-2.423,18.875 227 | 226,"MLI",2015,"Low income",804.357,10.118,1.442,17.407,,17.083,44.032 228 | 227,"MLT",2010,"High income",21150.42,18.954,2.041,23.611,6.867,6.883,7.634 229 | 228,"MLT",2015,"High income",23972.98,29.024,1.176,23.796,5.408,4.099,7.48 230 | 229,"MMR",2010,"Lower middle income",996.632,23.184,8.223,16.013,4,10.299,15.211 231 | 230,"MMR",2015,"Lower middle income",1148.39,19.313,10.005,24.465,4,-2.507,4.986 232 | 231,"MNE",2010,"Upper middle income",6694.34,-1.246,0.576,21.77,,15.434,-2.994 233 | 232,"MNE",2015,"Upper middle income",6464.74,6.702,1.204,20.021,,9.405,9.443 234 | 233,"MNG",2010,"Lower middle income",2608.31,26.881,10.165,42.087,9.9,70.109,108.436 235 | 234,"MNG",2015,"Lower middle income",3946.25,21.122,5.889,25.125,8.011,-15.38,-25.959 236 | 235,"MOZ",2010,"Low income",429.948,8.081,12.699,18.728,,-24.696,-3.721 237 | 236,"MOZ",2015,"Low income",529.243,14.228,2.392,53.621,,2.259,-2.354 238 | 237,"MRT",2010,"Lower middle income",1318.07,30.703,6.262,39.193,,14.015,12.698 239 | 238,"MRT",2015,"Lower middle income",1307.15,18.915,0.486,38.652,,-0.456,-13.295 240 | 239,"MUS",2010,"Upper middle income",7772.13,14.27,2.929,23.726,7.8,12.231,7.111 241 | 240,"MUS",2015,"Upper middle income",9114.97,16.312,1.285,21.199,7.9,-6.845,4.532 242 | 241,"MWI",2010,"Low income",442.765,26.25,7.409,22.823,,41.052,42.722 243 | 242,"MWI",2015,"Low income",353.794,2.676,21.858,12.121,,-4.16,1.118 244 | 243,"MYS",2010,"Upper middle income",8920.48,33.468,1.72,23.386,3.3,3.622,12.117 245 | 244,"MYS",2015,"Upper middle income",9500.52,28.087,2.104,25.092,3.1,4.428,2.08 246 | 245,"NAM",2010,"Upper middle income",5410.98,20.709,4.875,24.124,,1.997,7.834 247 | 246,"NAM",2015,"Upper middle income",5041.11,20.514,3.396,34.186,,1.626,1.281 248 | 247,"NER",2010,"Low income",378.205,25.45,-2.786,49.524,,20.873,22.132 249 | 248,"NER",2015,"Low income",406.592,24.479,1.006,42.57,,-2.084,7.651 250 | 249,"NGA",2010,"Lower middle income",2365.01,20.843,13.742,17.291,5.092,10.744,23.227 251 | 250,"NGA",2015,"Lower middle income",2763.2,12.298,9.01,15.49,9,8.818,2.966 252 | 251,"NIC",2010,"Lower middle income",1523.48,15.542,5.455,24.585,8,9.801,8.664 253 | 252,"NIC",2015,"Lower middle income",2086.89,23.627,3.997,31.862,5.957,-1.763,11.665 254 | 253,"NLD",2010,"High income",50433.31,27.798,0.932,20.42,4.995,9.029,7.918 255 | 254,"NLD",2015,"High income",44322.83,27.854,0.22,19.272,6.891,4.957,5.749 256 | 255,"NOR",2010,"High income",87309.3,36.27,2.419,25.341,3.584,0.66,8.309 257 | 256,"NOR",2015,"High income",74264.43,36.88,2.171,28.208,4.374,3.728,1.612 258 | 257,"NPL",2010,"Low income",595.395,35.909,9.565,38.271,,, 259 | 258,"NPL",2015,"Low income",747.485,43.787,7.212,38.779,,, 260 | 259,"NRU",2010,"High income",4936.67,,-1.968,,,, 261 | 260,"NRU",2015,"High income",8052.68,,9.784,,,, 262 | 261,"NZL",2010,"High income",33221.93,24.648,2.302,20.235,6.15,3.287,10.795 263 | 262,"NZL",2015,"High income",37281.09,20.123,0.293,22.747,5.35,6.945,3.701 264 | 263,"OMN",2010,"High income",20327.06,33.761,3.256,25.418,,8.105,3.84 265 | 264,"OMN",2015,"High income",18186.31,18.347,0.065,33.822,,2.072,2.21 266 | 265,"PAK",2010,"Lower middle income",1026.63,13.577,10.104,15.805,5.55,5.557,-3.292 267 | 266,"PAK",2015,"Lower middle income",1427.56,14.48,4.526,15.479,5.9,3.716,12.254 268 | 267,"PAN",2010,"Upper middle income",7896.91,26.436,3.491,37.201,6.516,-8.446,10.822 269 | 268,"PAN",2015,"Upper middle income",13113.71,39.271,0.134,46.557,5.052,2.082,5.898 270 | 269,"PER",2010,"Upper middle income",5008.68,22.505,1.53,24.898,7.88,1.4,27.198 271 | 270,"PER",2015,"Upper middle income",6176.68,19.703,3.548,24.59,6.44,1.796,0.329 272 | 271,"PHL",2010,"Lower middle income",2155.41,24.138,3.784,20.541,7.325,19.567,16.515 273 | 272,"PHL",2015,"Lower middle income",2862.9,23.036,1.409,20.552,6.275,0.716,13.48 274 | 273,"PLW",2010,"Upper middle income",10059.33,,1.448,21.82,,13.287,-0.218 275 | 274,"PLW",2015,"Upper middle income",15907.4,,0.947,23.206,,6.673,9.784 276 | 275,"PNG",2010,"Lower middle income",2151.07,,5.102,,,4.768,50.69 277 | 276,"PNG",2015,"Lower middle income",2746.19,,5.996,,,14.205,-31.234 278 | 277,"POL",2010,"High income",12601.91,15.913,2.583,21.313,9.635,12.864,14.012 279 | 278,"POL",2015,"High income",12552.29,19.832,-0.933,20.447,7.499,7.694,6.608 280 | 279,"PRI",2010,"High income",26435.74,,2.474,9.16,16.4,, 281 | 280,"PRI",2015,"High income",29620.21,,-0.751,8.703,12,, 282 | 281,"PRT",2010,"High income",22580.68,10.709,1.391,21.081,10.77,0.704,-2.681 283 | 282,"PRT",2015,"High income",19225.67,15.521,0.508,15.451,12.444,6.199,7.972 284 | 283,"PRY",2010,"Upper middle income",3199.48,15.905,4.651,16.187,5.674,23.746,36.481 285 | 284,"PRY",2015,"Upper middle income",4038.42,15.781,3.129,16.835,5.337,-3.204,-0.298 286 | 285,"QAT",2010,"High income",76413.23,50.419,-2.406,,,31.268,-1.425 287 | 286,"QAT",2015,"High income",68004.02,46.556,1.814,,,-1.392,-9.173 288 | 287,"ROU",2010,"Upper middle income",8277.34,21.755,6.113,26.836,6.939,15.229,12.566 289 | 288,"ROU",2015,"Upper middle income",8934.01,23.747,-0.596,24.962,6.812,5.404,9.19 290 | 289,"RUS",2010,"Upper middle income",11445.13,24.417,6.854,20.3,7.3,8.475,28.987 291 | 290,"RUS",2015,"Upper middle income",9521.08,27.175,15.532,22.123,5.575,-0.412,-25.036 292 | 291,"RWA",2010,"Low income",577.411,6.369,2.306,22.958,,11.592,3.364 293 | 292,"RWA",2015,"Low income",732.372,8.687,2.507,26.511,,-3.727,11.987 294 | 293,"SAU",2010,"High income",19112.69,43.414,3.801,30.743,5.548,7.464,-0.402 295 | 294,"SAU",2015,"High income",21013.58,26.174,2.189,34.877,5.591,4.125,1.287 296 | 295,"SDN",2010,"Lower middle income",1627.5,17.259,12.99,19.323,13.733,7.895,2.199 297 | 296,"SDN",2015,"Lower middle income",2118.98,9.263,16.91,17.104,21.6,-1.006,23.193 298 | 297,"SEN",2010,"Low income",999.775,17.708,1.229,22.098,,-0.328,-5.261 299 | 298,"SEN",2015,"Low income",913.05,16.576,0.129,23.992,,-5.531,-5.84 300 | 299,"SGP",2010,"High income",46569.4,51.68,2.823,28.238,2.175,17.439,16.3 301 | 300,"SGP",2015,"High income",53628.76,44.88,-0.523,26.77,1.9,2.63,8.813 302 | 301,"SLB",2010,"Lower middle income",1275.88,12.799,0.951,46.154,,25.612,44.357 303 | 302,"SLB",2015,"Lower middle income",1922.78,17.332,-0.559,19.99,,2.767,3.494 304 | 303,"SLE",2010,"Low income",448.198,9.581,17.782,31.089,,12.41,62.114 305 | 304,"SLE",2015,"Low income",718.893,0.947,8.969,16.003,,-25.493,-25.162 306 | 305,"SLV",2010,"Lower middle income",3546.08,10.831,1.179,13.318,7.05,15.92,8.373 307 | 306,"SLV",2015,"Lower middle income",4217,10.425,-0.731,13.983,7,2.864,8.193 308 | 307,"SMR",2010,"High income",64631.16,,2.595,22.504,4.945,, 309 | 308,"SMR",2015,"High income",46185.02,,0.14,17.926,9.18,, 310 | 309,"SRB",2010,"Upper middle income",5353.56,12.102,6.143,18.469,20,12.054,2.482 311 | 310,"SRB",2015,"Upper middle income",5244.31,14.141,1.392,18.852,18.2,10.209,9.143 312 | 311,"SSD",2010,"Low income",,,,,,, 313 | 312,"SSD",2015,"Low income",1049.77,7.304,52.813,14.528,,, 314 | 313,"STP",2010,"Lower middle income",1107.87,32.965,13.339,55.894,13.711,5.791,10.419 315 | 314,"STP",2015,"Lower middle income",1566.7,19.363,5.256,32.313,13.033,-0.441,3.336 316 | 315,"SUR",2010,"Upper middle income",8224.07,50.552,6.948,37.539,7.565,9.858,-13.849 317 | 316,"SUR",2015,"Upper middle income",8767.97,50.155,6.896,66.722,8.333,-7.2,15.571 318 | 317,"SVK",2010,"High income",16634.74,19.303,0.699,24.013,14.475,15.735,14.719 319 | 318,"SVK",2015,"High income",16105.13,23.415,-0.336,23.202,11.492,7.001,8.123 320 | 319,"SVN",2010,"High income",23499.59,22.121,1.801,22.24,7.267,10.155,6.837 321 | 320,"SVN",2015,"High income",20746.9,25.243,-0.526,20.064,9,5.551,4.623 322 | 321,"SWE",2010,"High income",51869.16,28.876,1.907,22.913,8.575,11.144,11.676 323 | 322,"SWE",2015,"High income",50319.11,28.902,0.702,24.207,7.4,5.926,5.442 324 | 323,"SWZ",2010,"Lower middle income",4267.04,3.179,4.509,14.293,,3.792,-9.507 325 | 324,"SWZ",2015,"Lower middle income",3511.76,22.994,4.96,12.169,,7.584,-5.528 326 | 325,"SYC",2010,"High income",10805.1,17.241,-2.405,36.622,4.605,-11.214,-5.267 327 | 326,"SYC",2015,"High income",14554.42,15.005,4.042,33.851,2.684,15.03,7.161 328 | 327,"SYR",2010,"Lower middle income",2806.69,23.845,4.398,26.688,8.613,11.328,5.364 329 | 328,"SYR",2015,"Lower middle income",,,,,,, 330 | 329,"TCD",2010,"Low income",1046.89,25.871,-2.109,34.388,,-5.485,16.804 331 | 330,"TCD",2015,"Low income",946.877,14.605,6.758,26.905,,29.216,-21.443 332 | 331,"TGO",2010,"Low income",497.408,17.634,1.438,23.928,,-1.176,1.115 333 | 332,"TGO",2015,"Low income",569.764,15.912,1.8,26.983,,7.56,8.217 334 | 333,"THA",2010,"Upper middle income",5065.38,28.724,3.286,25.357,1.05,14.22,22.956 335 | 334,"THA",2015,"Upper middle income",5799.39,30.301,-0.9,22.248,0.889,1.831,0.853 336 | 335,"TJK",2010,"Lower middle income",740.733,6.999,6.463,16.575,2.2,25.161,0.948 337 | 336,"TJK",2015,"Lower middle income",926.877,12.495,5.781,18.478,,11.91,-7.859 338 | 337,"TKM",2010,"Upper middle income",4479.01,,4.447,,,23.823,-6.603 339 | 338,"TKM",2015,"Upper middle income",6690.38,,7.405,,,-3.957,-12.175 340 | 339,"TLS",2010,"Lower middle income",4001.28,,5.178,11.273,,, 341 | 340,"TLS",2015,"Lower middle income",2462.09,,0.553,20.701,,, 342 | 341,"TON",2010,"Lower middle income",3843.11,,3.865,,,13.224,10.736 343 | 342,"TON",2015,"Lower middle income",3973.68,,-0.283,,,-9.11,5.403 344 | 343,"TTO",2010,"High income",16683.99,13.168,10.525,,5.925,9.07,-17.689 345 | 344,"TTO",2015,"High income",17321.77,11.131,4.659,,3.425,-7.143,13.824 346 | 345,"TUN",2010,"Lower middle income",4176.93,20.825,3.339,25.631,13.048,5.476,-2.077 347 | 346,"TUN",2015,"Lower middle income",3884.35,12.528,4.851,21.447,15,-2.818,-2.54 348 | 347,"TUR",2010,"Upper middle income",10475.61,21.334,8.566,26.973,11.127,9.077,17.463 349 | 348,"TUR",2015,"Upper middle income",10909.69,24.743,7.671,28.347,10.279,1.472,1.258 350 | 349,"TUV",2010,"Upper middle income",3076.88,,-1.853,,,, 351 | 350,"TUV",2015,"Upper middle income",3020.4,,3.228,,,, 352 | 351,"TZA",2010,"Low income",725.765,21.248,7.192,27.296,,7.039,6.095 353 | 352,"TZA",2015,"Low income",957.105,24.079,5.588,27.875,,15.185,0.441 354 | 353,"UGA",2010,"Low income",594.461,18.7,3.716,26.734,,-12.216,-10.44 355 | 354,"UGA",2015,"Low income",629.536,17.888,5.416,24.534,,6.913,13.038 356 | 355,"UKR",2010,"Lower middle income",2982.81,18.654,9.365,20.873,8.097,9.293,15.014 357 | 356,"UKR",2015,"Lower middle income",2135.18,15.657,48.684,15.933,9.143,-12.687,-28.81 358 | 357,"URY",2010,"High income",11859.9,17.593,6.699,19.408,7.033,14.309,11.893 359 | 358,"URY",2015,"High income",15317.58,17.713,8.666,19.821,7.508,-6.231,-9.154 360 | 359,"USA",2010,"High income",48310.34,15.086,1.637,18.394,9.608,11.896,12.714 361 | 360,"USA",2015,"High income",56174.94,19.107,0.12,20.348,5.258,0.109,4.583 362 | 361,"UZB",2010,"Lower middle income",1367.13,37.267,12.304,30.667,,-3.105,-9.187 363 | 362,"UZB",2015,"Lower middle income",2111.74,30.29,8.464,30.834,,7.49,-2.499 364 | 363,"VCT",2010,"Upper middle income",6224.22,-1.591,0.752,28.988,,2.231,-8.083 365 | 364,"VCT",2015,"Upper middle income",6706.46,2.483,-1.726,23.637,,2.218,7.98 366 | 365,"VEN",2010,"Upper middle income",10316.83,31.591,28.187,21.972,8.508,-12.877,-2.891 367 | 366,"VEN",2015,"Upper middle income",8493.97,31.787,121.738,42.136,7.4,-0.863,-23.102 368 | 367,"VNM",2010,"Lower middle income",1297.23,31.902,9.21,35.694,4.29,6.577,4.404 369 | 368,"VNM",2015,"Lower middle income",2086.53,28.055,0.631,27.581,2.4,9.796,15.617 370 | 369,"VUT",2010,"Lower middle income",2923.25,,2.763,34.66,,, 371 | 370,"VUT",2015,"Lower middle income",2747.3,,2.483,42.363,,, 372 | 371,"WSM",2010,"Lower middle income",3434.1,,-0.201,,,, 373 | 372,"WSM",2015,"Lower middle income",4158.97,,1.923,,,, 374 | 373,"YEM",2010,"Lower middle income",1266.79,8.25,11.175,11.661,,6.907,-6.212 375 | 374,"YEM",2015,"Lower middle income",1334.12,-3.715,39.403,1.779,,-37.593,-15.092 376 | 375,"ZAF",2010,"Upper middle income",7361.94,18.012,4.264,19.513,24.875,7.718,10.794 377 | 376,"ZAF",2015,"Upper middle income",5721.15,16.46,4.575,20.892,25.35,3.858,5.367 378 | 377,"ZMB",2010,"Lower middle income",1456.16,37.404,8.5,29.878,,20.521,32.638 379 | 378,"ZMB",2015,"Lower middle income",1310.35,39.177,10.107,42.791,,-11.1,3.726 380 | 379,"ZWE",2010,"Low income",765.418,16.109,3.045,23.921,,, 381 | 380,"ZWE",2015,"Low income",1002.56,5.563,-2.41,13.822,,, 382 | -------------------------------------------------------------------------------- /countries/languages.csv: -------------------------------------------------------------------------------- 1 | "lang_id","code","name","percent","official" 2 | 1,"AFG","Dari",50,TRUE 3 | 2,"AFG","Pashto",35,TRUE 4 | 3,"AFG","Turkic",11,FALSE 5 | 4,"AFG","Other",4,FALSE 6 | 5,"ALB","Albanian",98.8,TRUE 7 | 6,"ALB","Greek",0.5,FALSE 8 | 7,"ALB","Other",0.6,FALSE 9 | 8,"ALB","unspecified",0.1,FALSE 10 | 9,"DZA","Arabic",,TRUE 11 | 10,"DZA","French",,FALSE 12 | 11,"DZA","Berber or Tamazight",,TRUE 13 | 12,"DZA","Shawiya",,FALSE 14 | 13,"DZA","Mzab",,FALSE 15 | 14,"DZA","Tuareg",,FALSE 16 | 15,"ASM","Samoan",88.6,FALSE 17 | 16,"ASM","English",3.9,FALSE 18 | 17,"ASM","Tongan",2.7,FALSE 19 | 18,"ASM","Other",3,FALSE 20 | 19,"ASM","Other",1.8,FALSE 21 | 20,"AND","Catalan",,TRUE 22 | 21,"AND","French",,FALSE 23 | 22,"AND","Castilian",,FALSE 24 | 23,"AND","Portuguese",,FALSE 25 | 24,"AGO","Portuguese",71.2,TRUE 26 | 25,"AGO","Umbundu",23,FALSE 27 | 26,"AGO","Kikongo",8.2,FALSE 28 | 27,"AGO","Kimbundu",7.8,FALSE 29 | 28,"AGO","Chokwe",6.5,FALSE 30 | 29,"AGO","Nhaneca",3.4,FALSE 31 | 30,"AGO","Nganguela",3.1,FALSE 32 | 31,"AGO","Fiote",2.4,FALSE 33 | 32,"AGO","Kwanhama",2.3,FALSE 34 | 33,"AGO","Muhumbi",2.1,FALSE 35 | 34,"AGO","Luvale",1,FALSE 36 | 35,"AGO","Other",3.6,FALSE 37 | 36,"AIA","English",,TRUE 38 | 37,"ATG","English",,TRUE 39 | 38,"ATG","Antiguan creole",,FALSE 40 | 39,"ARG","Spanish",,TRUE 41 | 40,"ARG","Italian",,FALSE 42 | 41,"ARG","English",,FALSE 43 | 42,"ARG","German",,FALSE 44 | 43,"ARG","French",,FALSE 45 | 44,"ARG","indigenous",,FALSE 46 | 45,"ARM","Armenian",97.9,TRUE 47 | 46,"ARM","Kurdish",1,FALSE 48 | 47,"ARM","Other",1,FALSE 49 | 48,"ABW","Papiamento",69.4,TRUE 50 | 49,"ABW","Spanish",13.7,FALSE 51 | 50,"ABW","English",7.1,FALSE 52 | 51,"ABW","Dutch",6.1,TRUE 53 | 52,"ABW","Chinese",1.5,FALSE 54 | 53,"ABW","Other",1.7,FALSE 55 | 54,"ABW","unspecified",0.4,FALSE 56 | 55,"AUS","English",76.8,FALSE 57 | 56,"AUS","Mandarin",1.6,FALSE 58 | 57,"AUS","Italian",1.4,FALSE 59 | 58,"AUS","Arabic",1.3,FALSE 60 | 59,"AUS","Greek",1.2,FALSE 61 | 60,"AUS","Cantonese",1.2,FALSE 62 | 61,"AUS","Vietnamese",1.1,FALSE 63 | 62,"AUS","Other",10.4,FALSE 64 | 63,"AUS","unspecified",5,FALSE 65 | 64,"AUT","German",88.6,TRUE 66 | 65,"AUT","Turkish",2.3,FALSE 67 | 66,"AUT","Serbian",2.2,FALSE 68 | 67,"AUT","Croatian",1.6,TRUE 69 | 68,"AUT","Other",5.3,FALSE 70 | 69,"AZE","Azerbaijani",92.5,TRUE 71 | 70,"AZE","Russian",1.4,FALSE 72 | 71,"AZE","Armenian",1.4,FALSE 73 | 72,"AZE","Other",4.7,FALSE 74 | 73,"BHS","English",,TRUE 75 | 74,"BHS","Creole",,FALSE 76 | 75,"BHR","Arabic",,TRUE 77 | 76,"BHR","English",,FALSE 78 | 77,"BHR","Farsi",,FALSE 79 | 78,"BHR","Urdu",,FALSE 80 | 79,"BGD","Bangla",98.8,TRUE 81 | 80,"BGD","Other",1.2,FALSE 82 | 81,"BRB","English",,TRUE 83 | 82,"BRB","Bajan",,FALSE 84 | 83,"BLR","Russian",70.2,TRUE 85 | 84,"BLR","Belarusian",23.4,TRUE 86 | 85,"BLR","Other",3.1,FALSE 87 | 86,"BLR","unspecified",3.3,FALSE 88 | 87,"BEL","Dutch",60,TRUE 89 | 88,"BEL","French",40,TRUE 90 | 89,"BEL","German",1,TRUE 91 | 90,"BLZ","English",62.9,TRUE 92 | 91,"BLZ","Spanish",56.6,FALSE 93 | 92,"BLZ","Creole",44.6,FALSE 94 | 93,"BLZ","Maya",10.5,FALSE 95 | 94,"BLZ","German",3.2,FALSE 96 | 95,"BLZ","Garifuna",2.9,FALSE 97 | 96,"BLZ","Other",1.8,FALSE 98 | 97,"BLZ","unknown",0.3,FALSE 99 | 98,"BLZ","none",0.2,FALSE 100 | 99,"BEN","French",,TRUE 101 | 100,"BEN","Fon and Yoruba",,FALSE 102 | 101,"BEN","Tribal Languages",,FALSE 103 | 102,"BMU","English",,TRUE 104 | 103,"BMU","Portuguese",,FALSE 105 | 104,"BTN","Sharchhopka",28,FALSE 106 | 105,"BTN","Dzongkha",24,TRUE 107 | 106,"BTN","Lhotshamkha",22,FALSE 108 | 107,"BTN","Other",26,FALSE 109 | 108,"BOL","Spanish",60.7,TRUE 110 | 109,"BOL","Quechua",21.2,TRUE 111 | 110,"BOL","Aymara",14.6,TRUE 112 | 111,"BOL","Foreign Languages",2.4,FALSE 113 | 112,"BOL","Guarani",0.6,TRUE 114 | 113,"BOL","Other",0.4,FALSE 115 | 114,"BOL","none",0.1,FALSE 116 | 115,"BIH","Bosnian",52.9,TRUE 117 | 116,"BIH","Serbian",30.8,TRUE 118 | 117,"BIH","Croatian",14.6,TRUE 119 | 118,"BIH","Other",1.6,FALSE 120 | 119,"BIH","No Answer",0.2,FALSE 121 | 120,"BWA","Setswana",77.3,FALSE 122 | 121,"BWA","Sekalanga",7.4,FALSE 123 | 122,"BWA","Shekgalagadi",3.4,FALSE 124 | 123,"BWA","English",2.8,TRUE 125 | 124,"BWA","Zezuru",2,FALSE 126 | 125,"BWA","Sesarwa",1.7,FALSE 127 | 126,"BWA","Sembukushu",1.6,FALSE 128 | 127,"BWA","Ndebele",1,FALSE 129 | 128,"BWA","Other",2.8,FALSE 130 | 129,"BRA","Portuguese",,TRUE 131 | 130,"BRN","Malay",,TRUE 132 | 131,"BRN","English",,FALSE 133 | 132,"BRN","Chinese",,FALSE 134 | 133,"BGR","Bulgarian",76.8,TRUE 135 | 134,"BGR","Turkish",8.2,FALSE 136 | 135,"BGR","Romani",3.8,FALSE 137 | 136,"BGR","Other",0.7,FALSE 138 | 137,"BGR","unspecified",10.5,FALSE 139 | 138,"BFA","French",,TRUE 140 | 139,"BFA","Sudanic family",90,FALSE 141 | 140,"MMR","Burmese",,TRUE 142 | 141,"BDI","Kirundi",38.8,TRUE 143 | 142,"BDI","French",0.3,TRUE 144 | 143,"BDI","Swahili",0.2,FALSE 145 | 144,"BDI","English",0.06,TRUE 146 | 145,"BDI","Other",3.7,FALSE 147 | 146,"BDI","unspecified",56.9,FALSE 148 | 147,"KHM","Khmer",96.3,TRUE 149 | 148,"KHM","Other",3.7,FALSE 150 | 149,"CMR","Other",,FALSE 151 | 150,"CMR","English",,TRUE 152 | 151,"CMR","French",,TRUE 153 | 152,"CAN","English",58.7,TRUE 154 | 153,"CAN","French",22,TRUE 155 | 154,"CAN","Punjabi",1.4,FALSE 156 | 155,"CAN","Italian",1.3,FALSE 157 | 156,"CAN","Spanish",1.3,FALSE 158 | 157,"CAN","German",1.3,FALSE 159 | 158,"CAN","Cantonese",1.2,FALSE 160 | 159,"CAN","Tagalog",1.2,FALSE 161 | 160,"CAN","Arabic",1.1,FALSE 162 | 161,"CAN","Other",10.5,FALSE 163 | 162,"CYM","English",90.9,TRUE 164 | 163,"CYM","Spanish",4,FALSE 165 | 164,"CYM","Filipino",3.3,FALSE 166 | 165,"CYM","Other",1.7,FALSE 167 | 166,"CYM","unspecified",0.1,FALSE 168 | 167,"CAF","French",,TRUE 169 | 168,"CAF","Sangho",,FALSE 170 | 169,"CAF","tribal",,FALSE 171 | 170,"TCD","French",,TRUE 172 | 171,"TCD","Arabic",,TRUE 173 | 172,"TCD","Sara",,FALSE 174 | 173,"TCD","Other",,FALSE 175 | 174,"CHL","Spanish",99.5,TRUE 176 | 175,"CHL","English",10.2,FALSE 177 | 176,"CHL","indigenous",1,FALSE 178 | 177,"CHL","Other",2.3,FALSE 179 | 178,"CHL","unspecified",0.2,FALSE 180 | 179,"CHN","Mandarin",,TRUE 181 | 180,"CHN","Yue",,FALSE 182 | 181,"CHN","Wu",,FALSE 183 | 182,"CHN","Minbei",,FALSE 184 | 183,"CHN","Minnan",,FALSE 185 | 184,"CHN","Xiang",,FALSE 186 | 185,"CHN","Gan",,FALSE 187 | 186,"CHN","Hakka",,FALSE 188 | 187,"CHN","Other",,FALSE 189 | 188,"CXR","English",,TRUE 190 | 189,"CXR","Chinese",,FALSE 191 | 190,"CXR","Malay",,FALSE 192 | 191,"CCK","Malay",,FALSE 193 | 192,"CCK","English",,FALSE 194 | 193,"COL","Spanish",,TRUE 195 | 194,"COM","Arabic",,TRUE 196 | 195,"COM","French",,TRUE 197 | 196,"COM","Shikomoro",,TRUE 198 | 197,"COD","French",,TRUE 199 | 198,"COD","Lingala",,FALSE 200 | 199,"COD","Kingwana",,FALSE 201 | 200,"COD","Kikongo",,FALSE 202 | 201,"COD","Tshiluba",,FALSE 203 | 202,"COG","French",,TRUE 204 | 203,"COG","Lingala",,FALSE 205 | 204,"COG","Other",,FALSE 206 | 205,"COK","English",86.4,TRUE 207 | 206,"COK","Rarotongan",76.2,TRUE 208 | 207,"COK","Other",8.3,FALSE 209 | 208,"CRI","Spanish",,TRUE 210 | 209,"CRI","English",,FALSE 211 | 210,"CIV","French",,TRUE 212 | 211,"CIV","Other",,FALSE 213 | 212,"HRV","Croatian",95.6,TRUE 214 | 213,"HRV","Serbian",1.2,FALSE 215 | 214,"HRV","Other",3,FALSE 216 | 215,"HRV","unspecified",0.2,FALSE 217 | 216,"CUB","Spanish",,TRUE 218 | 217,"CYP","Greek",80.9,TRUE 219 | 218,"CYP","Turkish",0.2,TRUE 220 | 219,"CYP","English",4.1,FALSE 221 | 220,"CYP","Romanian",2.9,FALSE 222 | 221,"CYP","Russian",2.5,FALSE 223 | 222,"CYP","Bulgarian",2.2,FALSE 224 | 223,"CYP","Arabic",1.2,FALSE 225 | 224,"CYP","Filipino",1.1,FALSE 226 | 225,"CYP","Other",4.3,FALSE 227 | 226,"CYP","unspecified",0.6,FALSE 228 | 227,"DNK","Danish",,FALSE 229 | 228,"DNK","Faroese",,FALSE 230 | 229,"DNK","Greenlandic",,FALSE 231 | 230,"DNK","German",,FALSE 232 | 231,"DJI","French",,TRUE 233 | 232,"DJI","Arabic",,TRUE 234 | 233,"DJI","Somali",,FALSE 235 | 234,"DJI","Afar",,FALSE 236 | 235,"DMA","English",,TRUE 237 | 236,"DMA","French patois",,FALSE 238 | 237,"DOM","Spanish",,TRUE 239 | 238,"ECU","Spanish",93,TRUE 240 | 239,"ECU","Quechua",4.1,FALSE 241 | 240,"ECU","Other",0.7,FALSE 242 | 241,"ECU","foreign",2.2,FALSE 243 | 242,"EGY","Arabic",,TRUE 244 | 243,"EGY","English",,FALSE 245 | 244,"SLV","Spanish",,TRUE 246 | 245,"SLV","Nawat",,FALSE 247 | 246,"GNQ","Spanish",67.6,TRUE 248 | 247,"GNQ","Other",,TRUE 249 | 248,"GNQ","Fang",,FALSE 250 | 249,"GNQ","Bubi",32.4,FALSE 251 | 250,"ERI","Tigrinya",,TRUE 252 | 251,"ERI","Arabic",,TRUE 253 | 252,"ERI","English",,TRUE 254 | 253,"ERI","Tigre",,FALSE 255 | 254,"ERI","Kunama",,FALSE 256 | 255,"ERI","Afar",,FALSE 257 | 256,"ERI","Other",,FALSE 258 | 257,"EST","Estonian",68.5,TRUE 259 | 258,"EST","Russian",29.6,FALSE 260 | 259,"EST","Ukrainian",0.6,FALSE 261 | 260,"EST","Other",1.2,FALSE 262 | 261,"EST","unspecified",0.1,FALSE 263 | 262,"ETH","Oromo",33.8,TRUE 264 | 263,"ETH","Amharic",29.3,TRUE 265 | 264,"ETH","Somali",6.2,TRUE 266 | 265,"ETH","Tigrigna",5.9,TRUE 267 | 266,"ETH","Sidamo",4,FALSE 268 | 267,"ETH","Wolaytta",2.2,FALSE 269 | 268,"ETH","Gurage",2,FALSE 270 | 269,"ETH","Afar",1.7,TRUE 271 | 270,"ETH","Hadiyya",1.7,FALSE 272 | 271,"ETH","Gamo",1.5,FALSE 273 | 272,"ETH","Gedeo",1.3,FALSE 274 | 273,"ETH","Opuuo",1.2,FALSE 275 | 274,"ETH","Kafa",1.1,FALSE 276 | 275,"ETH","Other",8.1,FALSE 277 | 276,"ETH","English",,FALSE 278 | 277,"ETH","Arabic",,FALSE 279 | 278,"FRO","Faroese",93.8,FALSE 280 | 279,"FRO","Danish",3.2,FALSE 281 | 280,"FRO","Other",3,FALSE 282 | 281,"FIN","Finnish",88.3,TRUE 283 | 282,"FIN","Swedish",5.3,TRUE 284 | 283,"FIN","Russian",1.4,FALSE 285 | 284,"FIN","Other",5,FALSE 286 | 285,"FRA","French",100,TRUE 287 | 286,"FRA","Provencal",,FALSE 288 | 287,"FRA","Breton",,FALSE 289 | 288,"FRA","Alsatian",,FALSE 290 | 289,"FRA","Corsican",,FALSE 291 | 290,"FRA","Catalan",,FALSE 292 | 291,"FRA","Basque",,FALSE 293 | 292,"FRA","Flemish",,FALSE 294 | 293,"FRA","Occitan",,FALSE 295 | 294,"FRA","Picard",,FALSE 296 | 295,"FRA","French",,FALSE 297 | 296,"FRA","Creole patois",,FALSE 298 | 297,"FRA","Mahorian",,FALSE 299 | 298,"PYF","French",70,TRUE 300 | 299,"PYF","Polynesian",28.2,TRUE 301 | 300,"PYF","Other",1.8,FALSE 302 | 301,"GAB","French",,TRUE 303 | 302,"GAB","Fang",,FALSE 304 | 303,"GAB","Myene",,FALSE 305 | 304,"GAB","Nzebi",,FALSE 306 | 305,"GAB","Bapounou/Eschira",,FALSE 307 | 306,"GAB","Bandjabi",,FALSE 308 | 307,"GMB","English",,TRUE 309 | 308,"GMB","Mandinka",,FALSE 310 | 309,"GMB","Wolof",,FALSE 311 | 310,"GMB","Fula",,FALSE 312 | 311,"GMB","Other",,FALSE 313 | 312,"GEO","Georgian",87.6,TRUE 314 | 313,"GEO","Azeri",6.2,FALSE 315 | 314,"GEO","Armenian",3.9,FALSE 316 | 315,"GEO","Russian",1.2,FALSE 317 | 316,"GEO","Other",1,FALSE 318 | 317,"DEU","German",,TRUE 319 | 318,"GHA","Asante",16,FALSE 320 | 319,"GHA","Ewe",14,FALSE 321 | 320,"GHA","Fante",11.6,FALSE 322 | 321,"GHA","Boron",4.9,FALSE 323 | 322,"GHA","Dagomba",4.4,FALSE 324 | 323,"GHA","Dangme",4.2,FALSE 325 | 324,"GHA","Dagarte",3.9,FALSE 326 | 325,"GHA","Kokomba",3.5,FALSE 327 | 326,"GHA","Akyem",3.2,FALSE 328 | 327,"GHA","Ga",3.1,FALSE 329 | 328,"GHA","Other",31.2,FALSE 330 | 329,"GIB","English",,TRUE 331 | 330,"GIB","Spanish",,FALSE 332 | 331,"GIB","Italian",,FALSE 333 | 332,"GIB","Portuguese",,FALSE 334 | 333,"GRC","Greek",99,TRUE 335 | 334,"GRC","Other",1,FALSE 336 | 335,"GRL","Greenlandic",,TRUE 337 | 336,"GRL","Danish",,TRUE 338 | 337,"GRL","English",,FALSE 339 | 338,"GRD","English",,TRUE 340 | 339,"GRD","French patois",,FALSE 341 | 340,"GUM","English",43.6,FALSE 342 | 341,"GUM","Filipino",21.2,FALSE 343 | 342,"GUM","Chamorro",17.8,FALSE 344 | 343,"GUM","Other Pacific Islander",10,FALSE 345 | 344,"GUM","Asian",6.3,FALSE 346 | 345,"GUM","Other",1.1,FALSE 347 | 346,"GTM","Spanish",60,TRUE 348 | 347,"GTM","Amerindian",40,FALSE 349 | 348,"GIN","French",,TRUE 350 | 349,"GNB","Crioulo",,FALSE 351 | 350,"GNB","Portuguese",,TRUE 352 | 351,"GNB","Pular",,FALSE 353 | 352,"GNB","Mandingo",,FALSE 354 | 353,"GUY","English",,TRUE 355 | 354,"GUY","Guyanese Creole",,FALSE 356 | 355,"GUY","Amerindian",,FALSE 357 | 356,"GUY","Indian",,FALSE 358 | 357,"GUY","Chinese",,FALSE 359 | 358,"HTI","French",,TRUE 360 | 359,"HTI","Creole",,TRUE 361 | 360,"HND","Spanish",,TRUE 362 | 361,"HND","Amerindian",,FALSE 363 | 362,"HKG","Cantonese",89.5,TRUE 364 | 363,"HKG","English",3.5,TRUE 365 | 364,"HKG","Mandarin",1.4,TRUE 366 | 365,"HKG","Other Chinese",4,FALSE 367 | 366,"HKG","Other",1.6,FALSE 368 | 367,"HUN","Hungarian",99.6,TRUE 369 | 368,"HUN","English",16,FALSE 370 | 369,"HUN","German",11.2,FALSE 371 | 370,"HUN","Russian",1.6,FALSE 372 | 371,"HUN","Romanian",1.3,FALSE 373 | 372,"HUN","French",1.2,FALSE 374 | 373,"HUN","Other",4.2,FALSE 375 | 374,"ISL","Icelandic",,FALSE 376 | 375,"ISL","English",,FALSE 377 | 376,"ISL","Nordic",,FALSE 378 | 377,"ISL","German",,FALSE 379 | 378,"IND","Hindi",41,FALSE 380 | 379,"IND","Bengali",8.1,FALSE 381 | 380,"IND","Telugu",7.2,FALSE 382 | 381,"IND","Marathi",7,FALSE 383 | 382,"IND","Tamil",5.9,FALSE 384 | 383,"IND","Urdu",5,FALSE 385 | 384,"IND","Gujarati",4.5,FALSE 386 | 385,"IND","Kannada",3.7,FALSE 387 | 386,"IND","Malayalam",3.2,FALSE 388 | 387,"IND","Oriya",3.2,FALSE 389 | 388,"IND","Punjabi",2.8,FALSE 390 | 389,"IND","Assamese",1.3,FALSE 391 | 390,"IND","Maithili",1.2,FALSE 392 | 391,"IND","Other",5.9,FALSE 393 | 392,"IDN","Bahasa",,TRUE 394 | 393,"IDN","English",,FALSE 395 | 394,"IDN","Dutch",,FALSE 396 | 395,"IDN","Other",,FALSE 397 | 396,"IRN","Persian",,TRUE 398 | 397,"IRN","Turkic",,FALSE 399 | 398,"IRN","Kurdish",,FALSE 400 | 399,"IRN","Gilaki and Mazandarani",,FALSE 401 | 400,"IRN","Luri",,FALSE 402 | 401,"IRN","Balochi",,FALSE 403 | 402,"IRN","Arabic",,FALSE 404 | 403,"IRN","Other",,FALSE 405 | 404,"IRQ","Arabic",,TRUE 406 | 405,"IRQ","Kurdish",,TRUE 407 | 406,"IRQ","Turkmen",,FALSE 408 | 407,"IRQ","Syriac",,TRUE 409 | 408,"IRQ","Armenian",,TRUE 410 | 409,"IRL","English",61.3,TRUE 411 | 410,"IRL","Irish",38.7,TRUE 412 | 411,"ISR","Hebrew",,TRUE 413 | 412,"ISR","Arabic",,TRUE 414 | 413,"ISR","English",,FALSE 415 | 414,"ITA","Italian",,TRUE 416 | 415,"ITA","German",,FALSE 417 | 416,"ITA","French",,FALSE 418 | 417,"ITA","Slovene",,FALSE 419 | 418,"JAM","English",,FALSE 420 | 419,"JAM","English patois",,FALSE 421 | 420,"JPN","Japanese",,FALSE 422 | 421,"JOR","Arabic",,TRUE 423 | 422,"JOR","English",,FALSE 424 | 423,"KAZ","Kazakh",74,TRUE 425 | 424,"KAZ","Russian",94.4,TRUE 426 | 425,"KEN","English",,TRUE 427 | 426,"KEN","Kiswahili",,TRUE 428 | 427,"KEN","Other",,FALSE 429 | 428,"KIR","Kiribati",,FALSE 430 | 429,"KIR","English",,TRUE 431 | 430,"PRK","Korean",,FALSE 432 | 431,"KOR","Korean",,FALSE 433 | 432,"KOR","English",,FALSE 434 | 433,"KWT","Arabic",,TRUE 435 | 434,"KWT","English",,FALSE 436 | 435,"KGZ","Kyrgyz",71.4,TRUE 437 | 436,"KGZ","Uzbek",14.4,FALSE 438 | 437,"KGZ","Russian",9,TRUE 439 | 438,"KGZ","Other",5.2,FALSE 440 | 439,"LAO","Lao",,TRUE 441 | 440,"LAO","French",,FALSE 442 | 441,"LAO","English",,FALSE 443 | 442,"LAO","Other",,FALSE 444 | 443,"LVA","Latvian",56.3,TRUE 445 | 444,"LVA","Russian",33.8,FALSE 446 | 445,"LVA","Other",0.6,FALSE 447 | 446,"LVA","unspecified",9.4,FALSE 448 | 447,"LBN","Arabic",,TRUE 449 | 448,"LBN","French",,FALSE 450 | 449,"LBN","English",,FALSE 451 | 450,"LBN","Armenian",,FALSE 452 | 451,"LSO","Sesotho",,TRUE 453 | 452,"LSO","English",,TRUE 454 | 453,"LSO","Zulu",,FALSE 455 | 454,"LSO","Xhosa",,FALSE 456 | 455,"LBR","English",20,TRUE 457 | 456,"LBR","Other",,FALSE 458 | 457,"LBY","Arabic",,TRUE 459 | 458,"LBY","Italian",,FALSE 460 | 459,"LBY","English",,FALSE 461 | 460,"LBY","Berber",,FALSE 462 | 461,"LIE","German",94.5,TRUE 463 | 462,"LIE","Italian",1.1,FALSE 464 | 463,"LIE","Other",4.3,FALSE 465 | 464,"LTU","Lithuanian",82,TRUE 466 | 465,"LTU","Russian",8,FALSE 467 | 466,"LTU","Polish",5.6,FALSE 468 | 467,"LTU","Other",0.9,FALSE 469 | 468,"LTU","unspecified",3.5,FALSE 470 | 469,"LUX","Luxembourgish",88.8,TRUE 471 | 470,"LUX","French",4.2,TRUE 472 | 471,"LUX","Portuguese",2.3,FALSE 473 | 472,"LUX","German",1.1,TRUE 474 | 473,"LUX","Other",3.5,FALSE 475 | 474,"MKD","Macedonian",66.5,TRUE 476 | 475,"MKD","Albanian",25.1,FALSE 477 | 476,"MKD","Turkish",3.5,FALSE 478 | 477,"MKD","Romani",1.9,FALSE 479 | 478,"MKD","Serbian",1.2,FALSE 480 | 479,"MKD","Other",1.8,FALSE 481 | 480,"MDG","French",,TRUE 482 | 481,"MDG","Malagasy",,TRUE 483 | 482,"MDG","English",,FALSE 484 | 483,"MWI","English",,TRUE 485 | 484,"MWI","Chichewa",,FALSE 486 | 485,"MWI","Chinyanja",,FALSE 487 | 486,"MWI","Chiyao",,FALSE 488 | 487,"MWI","Chitumbuka",,FALSE 489 | 488,"MWI","Chilomwe",,FALSE 490 | 489,"MWI","Chinkhonde",,FALSE 491 | 490,"MWI","Chingoni",,FALSE 492 | 491,"MWI","Chisena",,FALSE 493 | 492,"MWI","Chitonga",,FALSE 494 | 493,"MWI","Chinyakyusa",,FALSE 495 | 494,"MWI","Chilambya",,FALSE 496 | 495,"MYS","Bahasa Malaysia",,TRUE 497 | 496,"MYS","English",,FALSE 498 | 497,"MYS","Chinese",,FALSE 499 | 498,"MYS","Tamil",,FALSE 500 | 499,"MYS","Telugu",,FALSE 501 | 500,"MYS","Malayalam",,FALSE 502 | 501,"MYS","Panjabi",,FALSE 503 | 502,"MYS","Thai",,FALSE 504 | 503,"MDV","Dhivehi",,TRUE 505 | 504,"MDV","English",,TRUE 506 | 505,"MLI","French",,TRUE 507 | 506,"MLI","Bambara",46.3,FALSE 508 | 507,"MLI","Peul/Foulfoulbe",9.4,FALSE 509 | 508,"MLI","Dogon",7.2,FALSE 510 | 509,"MLI","Maraka/Soninke",6.4,FALSE 511 | 510,"MLI","Malinke",5.6,FALSE 512 | 511,"MLI","Sonrhai/Djerma",5.6,FALSE 513 | 512,"MLI","Minianka",4.3,FALSE 514 | 513,"MLI","Tamacheq",3.5,FALSE 515 | 514,"MLI","Senoufo",2.6,FALSE 516 | 515,"MLI","Bobo",2.1,FALSE 517 | 516,"MLI","unspecified",0.7,FALSE 518 | 517,"MLI","Other",6.3,FALSE 519 | 518,"MLT","Maltese",90.1,TRUE 520 | 519,"MLT","English",6,TRUE 521 | 520,"MLT","multilingual",3,FALSE 522 | 521,"MLT","Other",0.9,FALSE 523 | 522,"MHL","Marshallese",98.2,TRUE 524 | 523,"MHL","Other",1.8,FALSE 525 | 524,"MRT","Arabic",,TRUE 526 | 525,"MRT","Pular",,FALSE 527 | 526,"MRT","Soninke",,FALSE 528 | 527,"MRT","Wolof",,FALSE 529 | 528,"MRT","French",,FALSE 530 | 529,"MUS","Creole",86.5,FALSE 531 | 530,"MUS","Bhojpuri",5.3,FALSE 532 | 531,"MUS","French",4.1,FALSE 533 | 532,"MUS","Other",2.6,FALSE 534 | 533,"MUS","unspecified",0.1,FALSE 535 | 534,"MEX","Spanish",92.7,FALSE 536 | 535,"MEX","indigenous",0.8,FALSE 537 | 536,"MEX","unspecified",0.8,FALSE 538 | 537,"FSM","English",,TRUE 539 | 538,"FSM","Chuukese",,FALSE 540 | 539,"FSM","Kosrean",,FALSE 541 | 540,"FSM","Pohnpeian",,FALSE 542 | 541,"FSM","Yapese",,FALSE 543 | 542,"FSM","Ulithian",,FALSE 544 | 543,"FSM","Woleaian",,FALSE 545 | 544,"FSM","Nukuoro",,FALSE 546 | 545,"FSM","Kapingamarangi",,FALSE 547 | 546,"MDA","Romanian",80.2,TRUE 548 | 547,"MDA","Russian",9.7,FALSE 549 | 548,"MDA","Gagauz",4.2,FALSE 550 | 549,"MDA","Ukrainian",3.9,FALSE 551 | 550,"MDA","Bulgarian",1.5,FALSE 552 | 551,"MDA","Romani",0.3,FALSE 553 | 552,"MDA","Other",0.2,FALSE 554 | 553,"MCO","French",,TRUE 555 | 554,"MCO","English",,FALSE 556 | 555,"MCO","Italian",,FALSE 557 | 556,"MCO","Monegasque",,FALSE 558 | 557,"MNG","Mongolian",90,TRUE 559 | 558,"MNG","Turkic",,FALSE 560 | 559,"MNG","Russian",,FALSE 561 | 560,"MSR","English",,FALSE 562 | 561,"MAR","Arabic",,TRUE 563 | 562,"MAR","Berber",,TRUE 564 | 563,"MAR","Tachelhit",,FALSE 565 | 564,"MAR","Tarifit",,FALSE 566 | 565,"MAR","French",,FALSE 567 | 566,"MAR","government",,FALSE 568 | 567,"MAR","and",,FALSE 569 | 568,"MOZ","Emakhuwa",25.3,FALSE 570 | 569,"MOZ","Portuguese",10.7,TRUE 571 | 570,"MOZ","Xichangana",10.3,FALSE 572 | 571,"MOZ","Cisena",7.5,FALSE 573 | 572,"MOZ","Elomwe",7,FALSE 574 | 573,"MOZ","Echuwabo",5.1,FALSE 575 | 574,"MOZ","Other",30.4,FALSE 576 | 575,"MOZ","unspecified",3.7,FALSE 577 | 576,"NAM","Oshivambo",48.9,FALSE 578 | 577,"NAM","Nama",11.3,FALSE 579 | 578,"NAM","Afrikaans",10.4,FALSE 580 | 579,"NAM","Otjiherero",8.6,FALSE 581 | 580,"NAM","Kavango",8.5,FALSE 582 | 581,"NAM","Caprivi",4.8,FALSE 583 | 582,"NAM","English",3.4,TRUE 584 | 583,"NAM","Other",2.3,FALSE 585 | 584,"NAM","Other",1.7,FALSE 586 | 585,"NRU","Nauruan",93,TRUE 587 | 586,"NRU","English",2,FALSE 588 | 587,"NRU","Other",5,FALSE 589 | 588,"NPL","Nepali",44.6,TRUE 590 | 589,"NPL","Maithali",11.7,FALSE 591 | 590,"NPL","Bhojpuri",6,FALSE 592 | 591,"NPL","Tharu",5.8,FALSE 593 | 592,"NPL","Tamang",5.1,FALSE 594 | 593,"NPL","Newar",3.2,FALSE 595 | 594,"NPL","Magar",3,FALSE 596 | 595,"NPL","Bajjika",3,FALSE 597 | 596,"NPL","Urdu",2.6,FALSE 598 | 597,"NPL","Avadhi",1.9,FALSE 599 | 598,"NPL","Limbu",1.3,FALSE 600 | 599,"NPL","Gurung",1.2,FALSE 601 | 600,"NPL","Other",10.4,FALSE 602 | 601,"NPL","unspecified",0.2,FALSE 603 | 602,"NLD","Dutch",,TRUE 604 | 603,"NCL","French",,TRUE 605 | 604,"NCL","Other",,FALSE 606 | 605,"NZL","English",89.8,TRUE 607 | 606,"NZL","Maori",3.5,TRUE 608 | 607,"NZL","Samoan",2,FALSE 609 | 608,"NZL","Hindi",1.6,FALSE 610 | 609,"NZL","French",1.2,FALSE 611 | 610,"NZL","Northern Chinese",1.2,FALSE 612 | 611,"NZL","Yue",1,FALSE 613 | 612,"NZL","Other",20.5,FALSE 614 | 613,"NZL","New Zealand Sign",,TRUE 615 | 614,"NIC","Spanish",95.3,TRUE 616 | 615,"NIC","Miskito",2.2,FALSE 617 | 616,"NIC","Mestizo",2,FALSE 618 | 617,"NIC","Other",0.5,FALSE 619 | 618,"NER","French",,TRUE 620 | 619,"NER","Hausa",,FALSE 621 | 620,"NER","Djerma",,FALSE 622 | 621,"NGA","English",,TRUE 623 | 622,"NGA","Hausa",,FALSE 624 | 623,"NGA","Yoruba",,FALSE 625 | 624,"NGA","Igbo",,FALSE 626 | 625,"NGA","Fulani",,FALSE 627 | 626,"NGA","Other",,FALSE 628 | 627,"NIU","Niuean",46,TRUE 629 | 628,"NIU","Niuean",32,FALSE 630 | 629,"NIU","English",11,TRUE 631 | 630,"NIU","Niuean",5,FALSE 632 | 631,"NIU","Other",6,FALSE 633 | 632,"NFK","English",67.6,TRUE 634 | 633,"NFK","Other",32.4,FALSE 635 | 634,"MNP","Philippine",32.8,FALSE 636 | 635,"MNP","Chamorro",24.1,TRUE 637 | 636,"MNP","English",17,TRUE 638 | 637,"MNP","Other Pacific Island",10.1,FALSE 639 | 638,"MNP","Chinese",6.8,FALSE 640 | 639,"MNP","Other Asian",7.3,FALSE 641 | 640,"MNP","Other",1.9,FALSE 642 | 641,"NOR","Bokmal",,TRUE 643 | 642,"NOR","Nynorsk",,TRUE 644 | 643,"NOR","Other",,FALSE 645 | 644,"OMN","Arabic",,TRUE 646 | 645,"OMN","English",,FALSE 647 | 646,"OMN","Baluchi",,FALSE 648 | 647,"OMN","Urdu",,FALSE 649 | 648,"OMN","Indian",,FALSE 650 | 649,"PAK","Punjabi",48,FALSE 651 | 650,"PAK","Sindhi",12,FALSE 652 | 651,"PAK","Saraiki",10,FALSE 653 | 652,"PAK","Pashto",8,FALSE 654 | 653,"PAK","Urdu",8,TRUE 655 | 654,"PAK","Balochi",3,FALSE 656 | 655,"PAK","Hindko",2,FALSE 657 | 656,"PAK","Brahui",1,FALSE 658 | 657,"PAK","English",,TRUE 659 | 658,"PAK","Burushaski",,FALSE 660 | 659,"PAK","Other",,FALSE 661 | 660,"PLW","Palauan",65.2,TRUE 662 | 661,"PLW","Other",1.9,FALSE 663 | 662,"PLW","English",19.1,TRUE 664 | 663,"PLW","Filipino",9.9,FALSE 665 | 664,"PLW","Chinese",1.2,FALSE 666 | 665,"PLW","Other",2.8,FALSE 667 | 666,"PAN","Spanish",,TRUE 668 | 667,"PAN","indigenous",,FALSE 669 | 668,"PAN","Panamanian English Creole",,FALSE 670 | 669,"PAN","English",,FALSE 671 | 670,"PAN","Chinese",,FALSE 672 | 671,"PAN","Arabic",,FALSE 673 | 672,"PAN","French",,FALSE 674 | 673,"PAN","Other",,FALSE 675 | 674,"PAN","Hebrew",,FALSE 676 | 675,"PAN","Korean",,FALSE 677 | 676,"PAN","Japanese",,FALSE 678 | 677,"PNG","Tok Pisin",,TRUE 679 | 678,"PNG","English",,TRUE 680 | 679,"PNG","Hiri",,TRUE 681 | 680,"PNG","Other",,FALSE 682 | 681,"PRY","Spanish",,TRUE 683 | 682,"PRY","Guarani",,TRUE 684 | 683,"PER","Spanish",84.1,TRUE 685 | 684,"PER","Quechua",13,TRUE 686 | 685,"PER","Aymara",1.7,TRUE 687 | 686,"PER","Ashaninka",0.3,FALSE 688 | 687,"PER","Other Native",0.7,FALSE 689 | 688,"PER","Other",0.2,FALSE 690 | 689,"PHL","Filipino",,TRUE 691 | 690,"PHL","English",,TRUE 692 | 691,"PHL","Other",,FALSE 693 | 692,"POL","Polish",98.2,TRUE 694 | 693,"POL","Silesian",1.4,FALSE 695 | 694,"POL","Other",1.1,FALSE 696 | 695,"POL","unspecified",1.3,FALSE 697 | 696,"PRT","Portuguese",,TRUE 698 | 697,"PRT","Mirandese",,TRUE 699 | 698,"PRI","Spanish",,FALSE 700 | 699,"PRI","English",,FALSE 701 | 700,"QAT","Arabic",,TRUE 702 | 701,"QAT","English",,FALSE 703 | 702,"ROM","Romanian",85.4,TRUE 704 | 703,"ROM","Hungarian",6.3,FALSE 705 | 704,"ROM","Romani",1.2,FALSE 706 | 705,"ROM","Other",1,FALSE 707 | 706,"ROM","unspecified",6.1,FALSE 708 | 707,"RUS","Russian",85.7,TRUE 709 | 708,"RUS","Tatar",3.2,FALSE 710 | 709,"RUS","Chechen",1,FALSE 711 | 710,"RUS","Other",10.1,FALSE 712 | 711,"RWA","Kinyarwanda",99.4,TRUE 713 | 712,"RWA","French",0.1,TRUE 714 | 713,"RWA","English",0.1,TRUE 715 | 714,"RWA","Swahili",0.02,FALSE 716 | 715,"RWA","Other",0.03,FALSE 717 | 716,"RWA","unspecified",0.3,FALSE 718 | 717,"KNA","English",,TRUE 719 | 718,"LCA","English",,TRUE 720 | 719,"LCA","French patois",,FALSE 721 | 720,"SPM","French",,TRUE 722 | 721,"VCT","English",,FALSE 723 | 722,"VCT","French patois",,FALSE 724 | 723,"WSM","Samoan",,TRUE 725 | 724,"WSM","English",,FALSE 726 | 725,"SMR","Italian",,FALSE 727 | 726,"STP","Portuguese",98.4,TRUE 728 | 727,"STP","Forro",36.2,FALSE 729 | 728,"STP","Cabo",8.5,FALSE 730 | 729,"STP","French",6.8,FALSE 731 | 730,"STP","Angolar",6.6,FALSE 732 | 731,"STP","English",4.9,FALSE 733 | 732,"STP","Lunguie",1,FALSE 734 | 733,"STP","Other",2.4,FALSE 735 | 734,"SAU","Arabic",,TRUE 736 | 735,"SEN","French",,TRUE 737 | 736,"SEN","Wolof",,FALSE 738 | 737,"SEN","Pular",,FALSE 739 | 738,"SEN","Jola",,FALSE 740 | 739,"SEN","Mandinka",,FALSE 741 | 740,"SEN","Serer",,FALSE 742 | 741,"SEN","Soninke",,FALSE 743 | 742,"SYC","Seychellois",89.1,TRUE 744 | 743,"SYC","English",5.1,TRUE 745 | 744,"SYC","French",0.7,TRUE 746 | 745,"SYC","Other",3.8,FALSE 747 | 746,"SYC","unspecified",1.4,FALSE 748 | 747,"SLE","English",,TRUE 749 | 748,"SLE","Mende",,FALSE 750 | 749,"SLE","Temne",,FALSE 751 | 750,"SLE","Krio",10,FALSE 752 | 751,"SGP","Mandarin",36.3,TRUE 753 | 752,"SGP","English",29.8,TRUE 754 | 753,"SGP","Malay",11.9,TRUE 755 | 754,"SGP","Hokkien",8.1,FALSE 756 | 755,"SGP","Cantonese",4.1,FALSE 757 | 756,"SGP","Tamil",3.2,TRUE 758 | 757,"SGP","Teochew",3.2,FALSE 759 | 758,"SGP","Other Indian",1.2,FALSE 760 | 759,"SGP","Other Chinese",1.1,FALSE 761 | 760,"SGP","Other",1.1,FALSE 762 | 761,"SVK","Slovak",78.6,TRUE 763 | 762,"SVK","Hungarian",9.4,FALSE 764 | 763,"SVK","Roma",2.3,FALSE 765 | 764,"SVK","Ruthenian",1,FALSE 766 | 765,"SVK","Other",8.8,FALSE 767 | 766,"SVN","Slovenian",91.1,TRUE 768 | 767,"SVN","Serbo",4.5,FALSE 769 | 768,"SVN","Other",4.4,FALSE 770 | 769,"SVN","Italian",,TRUE 771 | 770,"SVN","Hungarian",,TRUE 772 | 771,"SLB","Melanesian pidgin",,FALSE 773 | 772,"SLB","English",1,TRUE 774 | 773,"SLB","indigenous",,FALSE 775 | 774,"SOM","Somali",,TRUE 776 | 775,"SOM","Arabic",,TRUE 777 | 776,"SOM","Italian",,FALSE 778 | 777,"SOM","English",,FALSE 779 | 778,"ZAF","IsiZulu",22.7,TRUE 780 | 779,"ZAF","IsiXhosa",16,TRUE 781 | 780,"ZAF","Afrikaans",13.5,TRUE 782 | 781,"ZAF","English",9.6,TRUE 783 | 782,"ZAF","Sepedi",9.1,TRUE 784 | 783,"ZAF","Setswana",8,TRUE 785 | 784,"ZAF","Sesotho",7.6,TRUE 786 | 785,"ZAF","Xitsonga",4.5,TRUE 787 | 786,"ZAF","siSwati",2.5,TRUE 788 | 787,"ZAF","Tshivenda",2.4,TRUE 789 | 788,"ZAF","isiNdebele",2.1,TRUE 790 | 789,"ZAF","sign",0.5,FALSE 791 | 790,"ZAF","Other",1.6,FALSE 792 | 791,"ESP","Castilian Spanish",74,TRUE 793 | 792,"ESP","Catalan",17,TRUE 794 | 793,"ESP","Galician",7,TRUE 795 | 794,"ESP","Basque",2,TRUE 796 | 795,"ESP","Aranese",,TRUE 797 | 796,"LKA","Sinhala",74,TRUE 798 | 797,"LKA","Tamil",18,TRUE 799 | 798,"LKA","Other",8,FALSE 800 | 799,"SDN","Arabic",,TRUE 801 | 800,"SDN","English",,TRUE 802 | 801,"SDN","Nubian",,FALSE 803 | 802,"SDN","Ta Bedawie",,FALSE 804 | 803,"SDN","Fur",,FALSE 805 | 804,"SUR","Dutch",,TRUE 806 | 805,"SUR","English",,FALSE 807 | 806,"SUR","Sranang Tongo",,FALSE 808 | 807,"SUR","Caribbean Hindustani",,FALSE 809 | 808,"SUR","Javanese",,FALSE 810 | 809,"SWZ","English",,TRUE 811 | 810,"SWZ","siSwati",,TRUE 812 | 811,"SWE","Swedish",,TRUE 813 | 812,"CHE","German",63,TRUE 814 | 813,"CHE","French",22.7,TRUE 815 | 814,"CHE","Italian",8.1,TRUE 816 | 815,"CHE","English",4.9,FALSE 817 | 816,"CHE","Portuguese",3.7,FALSE 818 | 817,"CHE","Albanian",3,FALSE 819 | 818,"CHE","Serbo-Croatian",2.4,FALSE 820 | 819,"CHE","Spanish",2.2,FALSE 821 | 820,"CHE","Romansch",0.5,TRUE 822 | 821,"CHE","Other",7.1,FALSE 823 | 822,"SYR","Arabic",,TRUE 824 | 823,"SYR","Kurdish",,FALSE 825 | 824,"SYR","Armenian",,FALSE 826 | 825,"SYR","Aramaic",,FALSE 827 | 826,"SYR","Circassian",,FALSE 828 | 827,"SYR","French",,FALSE 829 | 828,"SYR","English",,FALSE 830 | 829,"TWN","Mandarin",,TRUE 831 | 830,"TWN","Taiwanese",,FALSE 832 | 831,"TWN","Hakka",,FALSE 833 | 832,"TJK","Tajik",,TRUE 834 | 833,"TJK","Russian",,FALSE 835 | 834,"TZA","Kiswahili",,TRUE 836 | 835,"TZA","English",,TRUE 837 | 836,"TZA","Arabic",,FALSE 838 | 837,"TZA","many",,FALSE 839 | 838,"THA","Thai",90.7,TRUE 840 | 839,"THA","Burmese",1.3,FALSE 841 | 840,"THA","Other",8,FALSE 842 | 841,"TGO","French",,TRUE 843 | 842,"TGO","Ewe",,FALSE 844 | 843,"TGO","Kabye",,FALSE 845 | 844,"TGO","Mina",,FALSE 846 | 845,"TGO","Dagomba",,FALSE 847 | 846,"TKL","Tokelauan",88.1,FALSE 848 | 847,"TKL","English",48.6,FALSE 849 | 848,"TKL","Samoan",26.7,FALSE 850 | 849,"TKL","Tuvaluan",11.2,FALSE 851 | 850,"TKL","Kiribati",1.5,FALSE 852 | 851,"TKL","Other",2.8,FALSE 853 | 852,"TKL","none",2.8,FALSE 854 | 853,"TKL","unspecified",0.8,FALSE 855 | 854,"TON","Tongan",,TRUE 856 | 855,"TON","English",,TRUE 857 | 856,"TON","Other",1.1,FALSE 858 | 857,"TON","unspecified",0.03,FALSE 859 | 858,"TTO","English",,TRUE 860 | 859,"TTO","Caribbean Hindustani",,FALSE 861 | 860,"TTO","French",,FALSE 862 | 861,"TTO","Spanish",,FALSE 863 | 862,"TTO","Chinese",,FALSE 864 | 863,"TUN","Arabic",,TRUE 865 | 864,"TUN","French",,FALSE 866 | 865,"TUN","Berber",,FALSE 867 | 866,"TUR","Turkish",,TRUE 868 | 867,"TUR","Kurdish",,FALSE 869 | 868,"TUR","Other",,FALSE 870 | 869,"TKM","Turkmen",72,TRUE 871 | 870,"TKM","Russian",12,FALSE 872 | 871,"TKM","Uzbek",9,FALSE 873 | 872,"TKM","Other",7,FALSE 874 | 873,"TCA","English",,TRUE 875 | 874,"TUV","Tuvaluan",,TRUE 876 | 875,"TUV","English",,TRUE 877 | 876,"TUV","Samoan",,FALSE 878 | 877,"TUV","Kiribati",,FALSE 879 | 878,"UGA","English",,TRUE 880 | 879,"UGA","Ganda",,FALSE 881 | 880,"UGA","Other",,FALSE 882 | 881,"UGA","Nilo",,FALSE 883 | 882,"UGA","Swahili",,FALSE 884 | 883,"UGA","Arabic",,FALSE 885 | 884,"UKR","Ukrainian",67.5,TRUE 886 | 885,"UKR","Russian",29.6,FALSE 887 | 886,"UKR","Other",2.9,FALSE 888 | 887,"ARE","Arabic",,TRUE 889 | 888,"ARE","Persian",,FALSE 890 | 889,"ARE","English",,FALSE 891 | 890,"ARE","Hindi",,FALSE 892 | 891,"ARE","Urdu",,FALSE 893 | 892,"GBR","English",,FALSE 894 | 893,"USA","English",79.2,FALSE 895 | 894,"USA","Spanish",12.9,FALSE 896 | 895,"USA","Other",8,FALSE 897 | 896,"URY","Spanish",,TRUE 898 | 897,"URY","Portunol",,FALSE 899 | 898,"URY","Brazilero",,FALSE 900 | 899,"UZB","Uzbek",74.3,TRUE 901 | 900,"UZB","Russian",14.2,FALSE 902 | 901,"UZB","Tajik",4.4,FALSE 903 | 902,"UZB","Other",7.1,FALSE 904 | 903,"VUT","Tribal Languages",63.2,FALSE 905 | 904,"VUT","Bislama",33.7,TRUE 906 | 905,"VUT","English",2,TRUE 907 | 906,"VUT","French",0.6,TRUE 908 | 907,"VUT","Other",0.5,FALSE 909 | 908,"VEN","Spanish",,TRUE 910 | 909,"VEN","indigenous",,FALSE 911 | 910,"VNM","Vietnamese",,TRUE 912 | 911,"VNM","English",,FALSE 913 | 912,"VNM","Other",,FALSE 914 | 913,"WLF","Wallisian",58.9,FALSE 915 | 914,"WLF","Futunian",30.1,FALSE 916 | 915,"WLF","French",10.8,TRUE 917 | 916,"WLF","Other",0.2,FALSE 918 | 917,"ESH","Standard",,FALSE 919 | 918,"ESH","Hassaniya",,FALSE 920 | 919,"ESH","Moroccan",,FALSE 921 | 920,"YEM","Arabic",,TRUE 922 | 921,"ZMB","Bembe",33.4,FALSE 923 | 922,"ZMB","Nyanja",14.7,FALSE 924 | 923,"ZMB","Tonga",11.4,FALSE 925 | 924,"ZMB","Lozi",5.5,FALSE 926 | 925,"ZMB","Chewa",4.5,FALSE 927 | 926,"ZMB","Nsenga",2.9,FALSE 928 | 927,"ZMB","Tumbuka",2.5,FALSE 929 | 928,"ZMB","Lunda",1.9,FALSE 930 | 929,"ZMB","Kaonde",1.8,FALSE 931 | 930,"ZMB","Lala",1.8,FALSE 932 | 931,"ZMB","Lamba",1.8,FALSE 933 | 932,"ZMB","English",1.7,TRUE 934 | 933,"ZMB","Luvale",1.5,FALSE 935 | 934,"ZMB","Mambwe",1.3,FALSE 936 | 935,"ZMB","Namwanga",1.2,FALSE 937 | 936,"ZMB","Lenje",1.1,FALSE 938 | 937,"ZMB","Bisa",1,FALSE 939 | 938,"ZMB","Other",9.7,FALSE 940 | 939,"ZMB","unspecified",0.2,FALSE 941 | 940,"ZWE","Shona",,TRUE 942 | 941,"ZWE","Ndebele",,TRUE 943 | 942,"ZWE","English",,TRUE 944 | 943,"ZWE","Chewa",,TRUE 945 | 944,"ZWE","Chibarwe",,TRUE 946 | 945,"ZWE","Kalanga",,TRUE 947 | 946,"ZWE","Koisan",,TRUE 948 | 947,"ZWE","Nambya",,TRUE 949 | 948,"ZWE","Ndau",,TRUE 950 | 949,"ZWE","Shangani",,TRUE 951 | 950,"ZWE","sign",,TRUE 952 | 951,"ZWE","Sotho",,TRUE 953 | 952,"ZWE","Tonga",,TRUE 954 | 953,"ZWE","Tswana",,TRUE 955 | 954,"ZWE","Venda",,TRUE 956 | 955,"ZWE","Xhosa",,TRUE 957 | --------------------------------------------------------------------------------