├── trajectory_plot.py ├── estimate_velocity.py ├── README.md ├── dataset_api.csv └── dataset.csv /trajectory_plot.py: -------------------------------------------------------------------------------- 1 | # This code is explained in the readme.md of this repo- 2 | 3 | import pandas as pd 4 | import plotly.express as px 5 | import time 6 | 7 | latitudes = [] 8 | longitudes = [] 9 | N = 60 # Sixty for one hour trajectory 10 | 11 | 12 | # Getting points 13 | 14 | for i in range(N): 15 | url = "http://api.open-notify.org/iss-now.json" # API URL 16 | 17 | df = pd.read_json(url) # Pandas read JSON data from API 18 | 19 | latitudes.append(df["iss_position"]["latitude"]) # We append latitude ISS position to latitudes list 20 | longitudes.append(df["iss_position"]["longitude"]) # We append longitude ISS position to longitudes list 21 | 22 | time.sleep(60) # This is used to separate de point records with one minute 23 | 24 | 25 | # Plotting 26 | fig = px.line_geo(lat=latitudes, lon=longitudes) # Passing our latitudes and longitudes list as parameter 27 | fig.show() 28 | 29 | # Update to orthographic plot 30 | 31 | fig.update_geos(projection_type="orthographic") 32 | fig.update_layout(height=300, margin={"r":0,"t":0,"l":0,"b":0}) 33 | fig.show() -------------------------------------------------------------------------------- /estimate_velocity.py: -------------------------------------------------------------------------------- 1 | 2 | # This code is explained in the readme.md of this repo- 3 | 4 | import pandas as pd # Pandas to read API data 5 | import time # Time for time.sleep 6 | import geopy.distance # Geopy to get distance between two lat-lon points 7 | import requests # Get another API data 8 | import json # Read that data 9 | 10 | 11 | # We need to initialize two empty list to save latitudes and longitudes 12 | 13 | lat = [] 14 | long = [] 15 | 16 | 17 | for i in range(2): # for in range(2) because we want two lat-lon points 18 | 19 | url = "http://api.open-notify.org/iss-now.json" # API url 20 | 21 | df = pd.read_json(url) # Read API Json data with Pandas 22 | 23 | lat.append(df["iss_position"]["latitude"]) # Append latitude to lat list 24 | long.append(df["iss_position"]["longitude"]) # Append longitude to long list 25 | 26 | time.sleep(60) # Wait 60 seconds to record the second lat-lon point 27 | 28 | coords_1 = (lat[0], long[0]) 29 | coords_2 = (lat[1], long[1]) 30 | 31 | distance = ( 32 | geopy.distance.distance(coords_1, coords_2).m 33 | ) # Distance between the points in meters 34 | 35 | 36 | iss_alt_url = "https://api.wheretheiss.at/v1/satellites/25544" 37 | r = requests.get(iss_alt_url) 38 | r = r.text 39 | r = json.loads(r) 40 | 41 | iss_alt = int(r["altitude"]) # IN KM 42 | 43 | earth_radius = 6371 # in KM 44 | distance_corrected = (distance * (earth_radius+iss_alt)/earth_radius) 45 | 46 | 47 | speed = distance_corrected/60 48 | 49 | 50 | print(round(speed*3.6, 3), "KM/H") # Multiplied by 3.6 to convert from m/s to km/h. Rounded by 3. 51 | 52 | 53 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ![espaciador](https://i.imgur.com/ugx3vyl.jpg) 2 | 3 | # International Space Station data with Python research:earth_americas: 4 | 5 | ### _Plotting ISS trajectory, calculating the velocity over the earth and more._ 6 | 7 | --- 8 | 9 | ### **Plotting trajectory:** 10 | ##### _We are going to make a graph of the trajectory of the ISS that is N minutes long. The N will be chosen by the user according to their preferences. This means that the program will run and keep points in a list for N minutes._ 11 | 12 | ##### We will use an API to retrieve ISS current position in latitude and longitude: 13 | http://open-notify.org/Open-Notify-API/ISS-Location-Now/ 14 | 15 | 16 | 17 | #### First we need to import the following python modules: 18 | ###### _Pandas to read json data from ISS API, plotly to make the plot of the trajectory and time to time.sleep function_ 19 | ```py 20 | import pandas as pd 21 | import plotly.express as px 22 | import time 23 | ``` 24 | 25 | #### Second we must initialize the list that will preserve the latitude and longitude points (every sixty seconds). You also have to initialize the N variable with time in minutes 26 | 27 | 28 | ```py 29 | latitudes = [] 30 | longitudes = [] 31 | N = 60 # Sixty for one hour trajectory 32 | ``` 33 | 34 | #### Then we will create the following for loop to keep recording latitude-longitude points separated by one minute 35 | ##### _We use for i in range(N), which is the time that the script will keep running (in hours) because we have a time.sleep(60) at the end_ 36 | 37 | 38 | ```py 39 | for i in range(N): 40 | url = "http://api.open-notify.org/iss-now.json" # API URL 41 | 42 | df = pd.read_json(url) # Pandas read JSON data from API 43 | 44 | latitudes.append(df["iss_position"]["latitude"]) # We append latitude ISS position to latitudes list 45 | longitudes.append(df["iss_position"]["longitude"]) # We append longitude ISS position to longitudes list 46 | 47 | time.sleep(60) # This is used to separate de point records with one minute 48 | ``` 49 | 50 | #### When the for loop finish the iterating we will have a record of N minutes ISS trajectory. Now we can plot this with Plotly (px.line_geo): 51 | ##### _px.line_geo will create a plot with earth map_ 52 | ```py 53 | fig = px.line_geo(lat=latitudes, lon=longitudes) # Passing our latitudes and longitudes list as parameter 54 | fig.show() 55 | ``` 56 | ![image](https://user-images.githubusercontent.com/80207106/137491882-9f2c82f2-f68c-4d84-833e-49baa44bdbc1.png) 57 | ###### _This is a two hours trajectory plot_ 58 | 59 | #### We can update our plot to orthographic projection with this code: 60 | ```py 61 | fig.update_geos(projection_type="orthographic") 62 | fig.update_layout(height=300, margin={"r":0,"t":0,"l":0,"b":0}) 63 | fig.show() 64 | ``` 65 | ![image](https://user-images.githubusercontent.com/80207106/137492413-bb3b060d-f560-4956-a321-66e56e4d7a6b.png) 66 | ###### _30 minutes trajectory plot_ 67 | 68 | ![image](https://i.imgur.com/BtMkiG6.gif) 69 | 70 | ###### _2 Hours trajectory plot GIF_ 71 | --- 72 | ### **Estimating ISS velocity:** 73 | 74 | ##### _We will estimate the ISS velocity using two diferent latitude-longitude points separated by one minute (sixty seconds). We can get the distance between that two points and then use phisics formula velocity(m/s) = distance(in meters)/time(in seconds)_ 75 | 76 | 77 | #### First import the following python modules 78 | 79 | ```py 80 | import pandas as pd # Pandas to read API data 81 | import time # Time for time.sleep 82 | import geopy.distance # Geopy to get distance between two lat-lon points 83 | import requests # Get another API data 84 | import json # Read that data 85 | ``` 86 | 87 | ##### _We need to initialize two empty list to save latitudes and longitudes_ 88 | 89 | 90 | ```py 91 | lat = [] 92 | long = [] 93 | ``` 94 | 95 | ##### _Next we will use a for loop to get the two latitude-longitude points separated by 60 seconds (time.sleep(60))_ 96 | 97 | 98 | ```py 99 | for i in range(2): # for in range(2) because we want two lat-lon points 100 | 101 | url = "http://api.open-notify.org/iss-now.json" # API url 102 | 103 | df = pd.read_json(url) # Read API Json data with Pandas 104 | 105 | lat.append(df["iss_position"]["latitude"]) # Append latitude to lat list 106 | long.append(df["iss_position"]["longitude"]) # Append longitude to long list 107 | 108 | time.sleep(60) # Wait 60 seconds to record the second lat-lon point 109 | ``` 110 | 111 | ##### _When this for loop finish we will have a lat list with two latitude positions and one long list with two longitude positions. In conjuntion of this 4 numbers we have two lat-lon points in different time moments (separated by one minute)_ 112 | 113 | #### Then we must get the distance between this points: 114 | 115 | ##### _We create the two different points. The first one with lat[0] index and long[0]. The second one with lat[1] and long[0]_ 116 | 117 | ```py 118 | coords_1 = (lat[0], long[0]) 119 | coords_2 = (lat[1], long[1]) 120 | ``` 121 | 122 | ##### _Then calculate distance with geopy library:_ 123 | 124 | ```py 125 | distance = ( 126 | geopy.distance.distance(coords_1, coords_2).m 127 | ) # Distance between the points in meters 128 | ``` 129 | 130 | ##### _But we must make a litle correction. Because ISS isn't moving in earth surface. It's orbiting aproximately 400Km above earth surface. So the radius is greater. The distance traveled is a litle bit more. To do this, we need to get ISS current altitud. Use the following code:_ 131 | 132 | 133 | ![image](https://i.imgur.com/jDZATbD.png) 134 | 135 | ```py 136 | iss_alt_url = "https://api.wheretheiss.at/v1/satellites/25544" 137 | r = requests.get(iss_alt_url) 138 | r = r.text 139 | r = json.loads(r) 140 | 141 | iss_alt = int(r["altitude"]) # IN KM 142 | ``` 143 | 144 | ##### _Now apply phisics formula to make the correction_ 145 | 146 | 147 | ```py 148 | earth_radius = 6371 # in KM 149 | distance_corrected = (distance * (earth_radius+iss_alt)/earth_radius) 150 | ``` 151 | 152 | ##### Now finish the calculation with speed formula already explained: 153 | 154 | ```py 155 | speed = distancia_corrected/60 156 | 157 | 158 | print(round(speed*3.6, 3), "KM/H") # Multiplied by 3.6 to convert from m/s to km/h. Rounded by 3. 159 | ``` 160 | #### Output: 161 | ``` 162 | 26367.118 KM/h 163 | ``` 164 | 165 | --- 166 | ### **Proving physical postulate that follows from kepler's second law with the ISS:** 167 | 168 | ##### _A body in elliptical orbit around another of greater mass moves at minimum orbital speed when it is in its apoaster (apogee for a body in orbit around the Earth) and at maximum orbital speed when it is in its periaster 1 ( perigee for a body in orbit around the Earth) because, according to Kepler's second law, in its travel through the ellipse the body sweeps equal areas in equal times._ 169 | 170 | #### We will use the database_api that i included in this repository. It include 300 minutes os ISS Data. 171 | ```py 172 | import pandas 173 | matrixpandas = pandas.read_csv("dataset_api.csv") 174 | ``` 175 | 176 | #### And then: 177 | ```py 178 | import plotly.express as px 179 | 180 | print("Un cuerpo en órbita elíptica alrededor de otro de mayor masa se mueve a la mínima velocidad orbital cuando se encuentra en su apoastro (apogeo para un cuerpo en órbita alrededor de la Tierra) y a la máxima velocidad orbital cuando se encuentra en su periastro 1​ (perigeo para un cuerpo en órbita alrededor de la Tierra) debido a que, según la segunda ley de Kepler, en su recorrido por la elipse el cuerpo barre áreas iguales en tiempos iguales.") 181 | fig = px.line(matrixpandas, x="time_utc", y="velocity_api", title='ISS Velocity cycle') 182 | fig.show() 183 | fig = px.line(matrixpandas, x="time_utc", y="altitude", title='ISS Altitude cycle') 184 | fig.show() 185 | ``` 186 | #### Output: 187 | ![image](https://i.imgur.com/SNlCwej.png) ![image](https://i.imgur.com/rvvlRKK.png) 188 | 189 | #### _It is demonstrated that the body that orbits elliptically (ISS) to another body of greater mass (Earth) reaches its minimum orbital speed at its apoaster. And its higher orbital speed in its periaster._ 190 | 191 |
192 | 193 | > ISS data - 2021 - Made by Facundo Pedaccio 194 | 195 | -------------------------------------------------------------------------------- /dataset_api.csv: -------------------------------------------------------------------------------- 1 | velocitys,velocity_api,altitude,latitude,longitude,time_utc 2 | 26790.68345697291,27524,440,-51.4772,35.123,17/10/2021 20:42:16 3 | 26560.82532771252,27524,440,-50.2049,46.8213,17/10/2021 20:44:18 4 | 26773.332781084355,27526,439,-47.7253,57.6479,17/10/2021 20:46:19 5 | 26754.333164764193,27529,437,-44.2416,67.2527,17/10/2021 20:48:21 6 | 26516.446109466164,27533,435,-39.9893,75.579,17/10/2021 20:50:22 7 | 26717.004398603643,27538,433,-35.1255,82.8328,17/10/2021 20:52:24 8 | 26474.463019428524,27543,431,-29.8455,89.1503,17/10/2021 20:54:25 9 | 26678.649422949726,27549,429,-24.2248,94.7853,17/10/2021 20:56:27 10 | 26440.976769316763,27554,427,-18.4014,99.8707,17/10/2021 20:58:28 11 | 26649.618038422006,27560,425,-12.3981,104.605,17/10/2021 21:00:30 12 | 26423.51810241795,27565,423,-6.3211,109.0845,17/10/2021 21:02:31 13 | 26863.731073240193,27569,422,-0.1456,113.4843,17/10/2021 21:04:33 14 | 26431.23640833049,27574,421,5.9829,117.847,17/10/2021 21:06:35 15 | 26665.683997173608,27577,421,12.0943,122.3406,17/10/2021 21:08:36 16 | 27126.511214011443,27581,421,18.1628,127.1093,17/10/2021 21:10:39 17 | 27371.371166670564,27583,421,24.1022,132.2785,17/10/2021 21:12:42 18 | 26733.60201667544,27585,421,29.7442,137.9188,17/10/2021 21:14:44 19 | 26542.32536141245,27587,422,35.0485,144.2461,17/10/2021 21:16:45 20 | 26571.88396930054,27589,423,39.9373,151.5159,17/10/2021 21:18:47 21 | 26813.548470987553,27590,423,44.2299,159.9055,17/10/2021 21:20:48 22 | 27721.092787915437,27591,423,47.78,169.7258,17/10/2021 21:22:52 23 | 26626.9542585931,27592,423,50.2561,-179.3237,17/10/2021 21:24:55 24 | 26857.18349092158,27593,423,51.499,-167.4962,17/10/2021 21:26:56 25 | 26862.654271890147,27594,423,51.3996,-155.3558,17/10/2021 21:28:58 26 | 26628.794591978945,27595,422,49.9763,-143.6758,17/10/2021 21:30:59 27 | 26838.867933500922,27596,421,47.3536,-132.9277,17/10/2021 21:33:01 28 | 26602.311212491422,27597,421,43.7608,-123.468,17/10/2021 21:35:02 29 | 26802.96234548969,27597,420,39.3863,-115.2161,17/10/2021 21:37:04 30 | 26556.702872648726,27597,419,34.4565,-108.0893,17/10/2021 21:39:05 31 | 26750.150539757058,27596,418,29.0842,-101.8255,17/10/2021 21:41:07 32 | 26723.108384436022,27594,417,23.4065,-96.2534,17/10/2021 21:43:08 33 | 26479.18373111103,27592,417,17.5394,-91.2137,17/10/2021 21:45:10 34 | 26684.495358356064,27588,418,11.5035,-86.5093,17/10/2021 21:47:11 35 | 26447.101261952113,27584,418,5.4062,-82.0459,17/10/2021 21:49:13 36 | 26663.92503415598,27579,420,-0.7546,-77.6658,17/10/2021 21:51:14 37 | 26441.045713935368,27574,421,-6.8827,-73.2915,17/10/2021 21:53:16 38 | 26665.412992115387,27568,423,-12.9822,-68.7727,17/10/2021 21:55:17 39 | 26459.77228181567,27562,426,-18.9541,-64.0241,17/10/2021 21:57:19 40 | 26690.549319778263,27555,428,-24.7879,-58.8694,17/10/2021 21:59:21 41 | 26719.78171235881,27548,431,-30.4089,-53.1426,17/10/2021 22:01:23 42 | 26506.25541445518,27542,433,-35.6743,-46.7075,17/10/2021 22:03:24 43 | 26966.70650326622,27537,435,-40.5028,-39.3065,17/10/2021 22:05:26 44 | 26540.99137536085,27532,437,-44.6785,-30.8413,17/10/2021 22:07:27 45 | 27220.120691416098,27528,439,-48.0846,-21.0042,17/10/2021 22:09:30 46 | 26570.994896447595,27525,440,-50.4209,-10.0866,17/10/2021 22:11:31 47 | 26791.34784101797,27524,440,-51.5476,1.8378,17/10/2021 22:13:34 48 | 26566.299357728836,27524,440,-51.3288,13.8588,17/10/2021 22:15:35 49 | 26781.649444729148,27525,440,-49.7996,25.4623,17/10/2021 22:17:41 50 | 26545.7217290809,27527,438,-46.9955,36.3865,17/10/2021 22:19:43 51 | 26758.39959356809,27530,437,-43.3089,45.6965,17/10/2021 22:21:44 52 | 26513.078718090765,27534,435,-38.9026,53.7496,17/10/2021 22:23:46 53 | 26713.215758841234,27539,433,-33.9243,60.7721,17/10/2021 22:25:47 54 | 26687.010087454164,27544,430,-28.5379,66.9312,17/10/2021 22:27:49 55 | 26452.307516091125,27550,428,-22.8796,72.4038,17/10/2021 22:29:50 56 | 26665.35584093546,27555,426,-16.9883,77.4105,17/10/2021 22:31:53 57 | 26645.213202084193,27561,424,-10.8818,82.1329,17/10/2021 22:33:56 58 | 26423.300842942903,27566,423,-4.7384,86.6083,17/10/2021 22:36:00 59 | 26645.86176056122,27571,422,1.5437,91.0688,17/10/2021 22:38:02 60 | 26432.89848027286,27575,421,7.665,95.4508,17/10/2021 22:40:04 61 | 26678.669847414745,27578,421,13.8073,100.0354,17/10/2021 22:42:06 62 | 26469.54754169013,27581,421,19.7904,104.8538,17/10/2021 22:44:08 63 | 26717.28126745775,27584,421,25.6289,110.1082,17/10/2021 22:46:10 64 | 26743.46729534723,27586,422,31.2188,115.9449,17/10/2021 22:48:12 65 | 26767.14153743159,27588,422,36.4801,122.5853,17/10/2021 22:50:15 66 | 26802.37928854859,27589,423,41.2368,130.1862,17/10/2021 22:52:17 67 | 26817.90032832166,27590,423,45.3387,138.9656,17/10/2021 22:54:19 68 | 26838.30124812287,27591,423,48.5672,148.9873,17/10/2021 22:56:21 69 | 26628.339758847218,27593,423,50.7191,160.1876,17/10/2021 22:58:23 70 | 26857.682628386483,27594,423,51.6075,172.2188,17/10/2021 23:00:25 71 | 26861.37684781529,27595,423,51.1358,-175.6832,17/10/2021 23:02:27 72 | 26628.995496235555,27596,422,49.3289,-164.0454,17/10/2021 23:04:30 73 | 27057.839059615264,27596,421,46.3399,-153.4871,17/10/2021 23:06:34 74 | 26815.001107407857,27597,420,42.4371,-144.314,17/10/2021 23:08:36 75 | 26792.76728934831,27597,419,37.8395,-136.4033,17/10/2021 23:10:39 76 | 26766.531078870586,27596,418,32.7144,-129.5343,17/10/2021 23:12:41 77 | 26742.044409993767,27595,418,27.183,-123.4752,17/10/2021 23:14:46 78 | 26714.36635418387,27593,417,21.3029,-117.991,17/10/2021 23:16:48 79 | 26471.351928709762,27591,417,15.3516,-113.0764,17/10/2021 23:18:50 80 | 26457.629719004297,27587,418,9.2529,-108.4495,17/10/2021 23:20:52 81 | 26665.741304952397,27583,419,3.085,-104.0007,17/10/2021 23:22:56 82 | 26660.113238545073,27577,420,-3.2046,-99.5394,17/10/2021 23:24:58 83 | 26663.94426605987,27572,422,-9.3672,-95.0919,17/10/2021 23:27:00 84 | 26669.684067719558,27565,424,-15.4313,-90.487,17/10/2021 23:29:02 85 | 26469.453259181297,27559,427,-21.3939,-85.5569,17/10/2021 23:31:04 86 | 26699.992305468695,27552,429,-27.1407,-80.1958,17/10/2021 23:33:05 87 | 26496.819637074987,27546,432,-32.5923,-74.2422,17/10/2021 23:35:07 88 | 26734.429575607137,27540,434,-37.6896,-67.4533,17/10/2021 23:37:09 89 | 26755.46853871204,27535,436,-42.2714,-59.6475,17/10/2021 23:39:10 90 | 26549.203892429752,27530,438,-46.1474,-50.6878,17/10/2021 23:41:12 91 | 26780.51532383119,27527,439,-49.1422,-40.4318,17/10/2021 23:43:13 92 | 26565.74129935147,27525,440,-51.0176,-29.1198,17/10/2021 23:45:16 93 | 26567.487831926213,27524,440,-51.6212,-17.0144,17/10/2021 23:47:17 94 | 26786.028436575947,27524,440,-50.8723,-5.0492,17/10/2021 23:49:20 95 | 26777.950858199565,27526,439,-48.8456,6.2471,17/10/2021 23:51:21 96 | 26541.22543637747,27528,438,-45.7501,16.3165,17/10/2021 23:53:22 97 | 26744.89287000904,27532,436,-41.7706,25.1664,17/10/2021 23:55:24 98 | 26723.517466996615,27536,434,-37.1235,32.8396,17/10/2021 23:57:25 99 | 27586.465462659,27541,432,-31.8916,39.6225,17/10/2021 23:59:29 100 | 26396.455547196558,27546,430,-26.4078,45.4707,18/10/2021 00:01:31 101 | 26665.901509630792,27552,427,-20.637,50.7597,18/10/2021 00:03:32 102 | 26651.50144935006,27557,425,-14.6851,55.6187,18/10/2021 00:05:34 103 | 26867.516339703503,27563,424,-8.5385,60.2464,18/10/2021 00:07:37 104 | 26644.13166635151,27568,422,-2.4002,64.6573,18/10/2021 00:09:39 105 | 26656.10349531225,27572,422,3.7582,69.0259,18/10/2021 00:11:40 106 | 26883.485414451854,27576,421,9.9159,73.484,18/10/2021 00:13:43 107 | 26680.17625821136,27579,421,15.9748,78.1141,18/10/2021 00:15:44 108 | 26479.996681404,27582,421,21.8815,83.043,18/10/2021 00:17:46 109 | 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