This analysis focuses on Broadband (World). The data is [here][Pandas plotting]
Broadband (World) |
Data
The data used is [here]
Country,Average speed,Average peak,Above 4Mbps,Above 10Mbps,Above 15Mbps,GDP per capita Argentina,4.2,26.9,39.00,3.10,0.50,13589 Australia,7.8,41.9,72.00,18.00,7.40,50962 Austria,11.4,44,90.00,33.00,17.00,43724 Belgium,12.8,59.3,91.00,52.00,26.00,40107 Bolivia,1.8,13.9,2.80,0.20,0.10,2886 Brazil,3.6,29,32.00,2.20,0.60,8670 Canada,11.9,52.4,87.00,43.00,21.00,43332 Chile,5.7,42,62.00,7.10,1.60,13341 China,3.7,23.1,33.00,1.60,0.30,7990 Colombia,4.2,28.1,48.00,1.70,0.40,6084 Costa Rica,3.2,16.4,20.00,1.10,0.50,10936 Czech Republic,14.5,50.9,86.00,46.00,27.00,17257 Denmark,14,50.1,94.00,51.00,29.00,52114 Ecuador,4.1,25.5,36.00,2.50,0.60,6071 Finland,14.8,57.4,91.00,51.00,28.00,41974 France,8.2,38.9,74.00,21.00,8.70,37675 Germany,11.5,49.2,87.00,37.00,19.00,40997 Hong Kong,15.8,101.1,92.00,59.00,36.00,42390 Hungary,10.7,53.9,90.00,36.00,18.00,12240 India,2.5,18.7,14.00,2.30,0.80,1617 Indonesia,7.45,31,17.00,0.90,0.40,3362 Ireland,12.4,52,76.00,41.00,23.00,51351 Israel,11.2,70,94.00,36.00,14.00,35343 Italy,6.5,30.1,71.00,9.20,3.40,29867 Japan,15,78.4,90.00,54.00,32.00,32486 Malaysia,4.9,38.3,52.00,4.00,0.90,9557 Mexico,5.5,27.3,64.00,6.40,1.70,9009 Netherlands,15.6,63.5,95.00,60.00,34.00,43603 New Zealand,8.7,42,87.00,22.00,8.20,37045 Norway,16.4,55.9,88.00,54.00,37.00,74822 Panama,3.5,16.9,33.00,1.50,0.40,13013 Paraguay,1.5,13.4,2.10,0.10,0.10,4010 Peru,4.4,30.4,46.00,2.90,0.60,6021 Philippines,2.8,25.3,10.00,0.90,0.30,2858 Poland,10.6,45.6,88.00,34.00,17.00,12495 Portugal,10.6,47.9,85.00,37.00,19.00,19122 Romania,13.1,72.9,94.00,57.00,27.00,8906 Russia,10.2,57.9,87.00,38.00,15.00,9055 Singapore,12.5,135.4,87.00,51.00,27.00,52888 Slovakia,11.2,49,85.00,28.00,17.00,15992 South Africa,3.7,18.9,22.00,2.90,1.70,5695 South Korea,20.5,86.6,96.00,68.00,45.00,27195 Spain,10.4,53.5,85.00,34.00,17.00,25865 Sri Lanka,5.1,33.5,76.00,2.20,0.60,3889 Sweden,17.4,69,92.00,55.00,38.00,49866 Switzerland,16.2,62.6,93.00,61.00,36.00,80675 Taiwan,10.1,77.9,88.00,29.00,13.00,22288 Thailand,8.2,58.3,93.00,18.00,5.80,5742 Turkey,6.2,38.5,77.00,7.60,2.90,9437 United Arab Emirates,6.8,45.8,85.00,10.00,2.30,36060 United Kingdom,13,54.2,87.00,46.00,28.00,43771 United States,12.6,57.3,80.00,46.00,24.00,55805 Uruguay,5.9,60.2,68.00,7.70,1.60,15748 Vietnam,3.4,25.5,31.00,0.60,0.10,2088
Code
An outline of the code is:
import numpy as np import pandas as pd import sys import statsmodels.api as sm