{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"data = pd.read_csv('data/gapminder_gdp_europe.csv',index_col='country')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true,
"jupyter": {
"outputs_hidden": true
}
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" \n",
" gdpPercap_1952 \n",
" gdpPercap_1957 \n",
" gdpPercap_1962 \n",
" gdpPercap_1967 \n",
" gdpPercap_1972 \n",
" gdpPercap_1977 \n",
" gdpPercap_1982 \n",
" gdpPercap_1987 \n",
" gdpPercap_1992 \n",
" gdpPercap_1997 \n",
" gdpPercap_2002 \n",
" gdpPercap_2007 \n",
" \n",
" \n",
" country \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Albania \n",
" 1601.056136 \n",
" 1942.284244 \n",
" 2312.888958 \n",
" 2760.196931 \n",
" 3313.422188 \n",
" 3533.003910 \n",
" 3630.880722 \n",
" 3738.932735 \n",
" 2497.437901 \n",
" 3193.054604 \n",
" 4604.211737 \n",
" 5937.029526 \n",
" \n",
" \n",
" Austria \n",
" 6137.076492 \n",
" 8842.598030 \n",
" 10750.721110 \n",
" 12834.602400 \n",
" 16661.625600 \n",
" 19749.422300 \n",
" 21597.083620 \n",
" 23687.826070 \n",
" 27042.018680 \n",
" 29095.920660 \n",
" 32417.607690 \n",
" 36126.492700 \n",
" \n",
" \n",
" Belgium \n",
" 8343.105127 \n",
" 9714.960623 \n",
" 10991.206760 \n",
" 13149.041190 \n",
" 16672.143560 \n",
" 19117.974480 \n",
" 20979.845890 \n",
" 22525.563080 \n",
" 25575.570690 \n",
" 27561.196630 \n",
" 30485.883750 \n",
" 33692.605080 \n",
" \n",
" \n",
" Bosnia and Herzegovina \n",
" 973.533195 \n",
" 1353.989176 \n",
" 1709.683679 \n",
" 2172.352423 \n",
" 2860.169750 \n",
" 3528.481305 \n",
" 4126.613157 \n",
" 4314.114757 \n",
" 2546.781445 \n",
" 4766.355904 \n",
" 6018.975239 \n",
" 7446.298803 \n",
" \n",
" \n",
" Bulgaria \n",
" 2444.286648 \n",
" 3008.670727 \n",
" 4254.337839 \n",
" 5577.002800 \n",
" 6597.494398 \n",
" 7612.240438 \n",
" 8224.191647 \n",
" 8239.854824 \n",
" 6302.623438 \n",
" 5970.388760 \n",
" 7696.777725 \n",
" 10680.792820 \n",
" \n",
" \n",
" Croatia \n",
" 3119.236520 \n",
" 4338.231617 \n",
" 5477.890018 \n",
" 6960.297861 \n",
" 9164.090127 \n",
" 11305.385170 \n",
" 13221.821840 \n",
" 13822.583940 \n",
" 8447.794873 \n",
" 9875.604515 \n",
" 11628.388950 \n",
" 14619.222720 \n",
" \n",
" \n",
" Czech Republic \n",
" 6876.140250 \n",
" 8256.343918 \n",
" 10136.867130 \n",
" 11399.444890 \n",
" 13108.453600 \n",
" 14800.160620 \n",
" 15377.228550 \n",
" 16310.443400 \n",
" 14297.021220 \n",
" 16048.514240 \n",
" 17596.210220 \n",
" 22833.308510 \n",
" \n",
" \n",
" Denmark \n",
" 9692.385245 \n",
" 11099.659350 \n",
" 13583.313510 \n",
" 15937.211230 \n",
" 18866.207210 \n",
" 20422.901500 \n",
" 21688.040480 \n",
" 25116.175810 \n",
" 26406.739850 \n",
" 29804.345670 \n",
" 32166.500060 \n",
" 35278.418740 \n",
" \n",
" \n",
" Finland \n",
" 6424.519071 \n",
" 7545.415386 \n",
" 9371.842561 \n",
" 10921.636260 \n",
" 14358.875900 \n",
" 15605.422830 \n",
" 18533.157610 \n",
" 21141.012230 \n",
" 20647.164990 \n",
" 23723.950200 \n",
" 28204.590570 \n",
" 33207.084400 \n",
" \n",
" \n",
" France \n",
" 7029.809327 \n",
" 8662.834898 \n",
" 10560.485530 \n",
" 12999.917660 \n",
" 16107.191710 \n",
" 18292.635140 \n",
" 20293.897460 \n",
" 22066.442140 \n",
" 24703.796150 \n",
" 25889.784870 \n",
" 28926.032340 \n",
" 30470.016700 \n",
" \n",
" \n",
" Germany \n",
" 7144.114393 \n",
" 10187.826650 \n",
" 12902.462910 \n",
" 14745.625610 \n",
" 18016.180270 \n",
" 20512.921230 \n",
" 22031.532740 \n",
" 24639.185660 \n",
" 26505.303170 \n",
" 27788.884160 \n",
" 30035.801980 \n",
" 32170.374420 \n",
" \n",
" \n",
" Greece \n",
" 3530.690067 \n",
" 4916.299889 \n",
" 6017.190733 \n",
" 8513.097016 \n",
" 12724.829570 \n",
" 14195.524280 \n",
" 15268.420890 \n",
" 16120.528390 \n",
" 17541.496340 \n",
" 18747.698140 \n",
" 22514.254800 \n",
" 27538.411880 \n",
" \n",
" \n",
" Hungary \n",
" 5263.673816 \n",
" 6040.180011 \n",
" 7550.359877 \n",
" 9326.644670 \n",
" 10168.656110 \n",
" 11674.837370 \n",
" 12545.990660 \n",
" 12986.479980 \n",
" 10535.628550 \n",
" 11712.776800 \n",
" 14843.935560 \n",
" 18008.944440 \n",
" \n",
" \n",
" Iceland \n",
" 7267.688428 \n",
" 9244.001412 \n",
" 10350.159060 \n",
" 13319.895680 \n",
" 15798.063620 \n",
" 19654.962470 \n",
" 23269.607500 \n",
" 26923.206280 \n",
" 25144.392010 \n",
" 28061.099660 \n",
" 31163.201960 \n",
" 36180.789190 \n",
" \n",
" \n",
" Ireland \n",
" 5210.280328 \n",
" 5599.077872 \n",
" 6631.597314 \n",
" 7655.568963 \n",
" 9530.772896 \n",
" 11150.981130 \n",
" 12618.321410 \n",
" 13872.866520 \n",
" 17558.815550 \n",
" 24521.947130 \n",
" 34077.049390 \n",
" 40675.996350 \n",
" \n",
" \n",
" Italy \n",
" 4931.404155 \n",
" 6248.656232 \n",
" 8243.582340 \n",
" 10022.401310 \n",
" 12269.273780 \n",
" 14255.984750 \n",
" 16537.483500 \n",
" 19207.234820 \n",
" 22013.644860 \n",
" 24675.024460 \n",
" 27968.098170 \n",
" 28569.719700 \n",
" \n",
" \n",
" Montenegro \n",
" 2647.585601 \n",
" 3682.259903 \n",
" 4649.593785 \n",
" 5907.850937 \n",
" 7778.414017 \n",
" 9595.929905 \n",
" 11222.587620 \n",
" 11732.510170 \n",
" 7003.339037 \n",
" 6465.613349 \n",
" 6557.194282 \n",
" 9253.896111 \n",
" \n",
" \n",
" Netherlands \n",
" 8941.571858 \n",
" 11276.193440 \n",
" 12790.849560 \n",
" 15363.251360 \n",
" 18794.745670 \n",
" 21209.059200 \n",
" 21399.460460 \n",
" 23651.323610 \n",
" 26790.949610 \n",
" 30246.130630 \n",
" 33724.757780 \n",
" 36797.933320 \n",
" \n",
" \n",
" Norway \n",
" 10095.421720 \n",
" 11653.973040 \n",
" 13450.401510 \n",
" 16361.876470 \n",
" 18965.055510 \n",
" 23311.349390 \n",
" 26298.635310 \n",
" 31540.974800 \n",
" 33965.661150 \n",
" 41283.164330 \n",
" 44683.975250 \n",
" 49357.190170 \n",
" \n",
" \n",
" Poland \n",
" 4029.329699 \n",
" 4734.253019 \n",
" 5338.752143 \n",
" 6557.152776 \n",
" 8006.506993 \n",
" 9508.141454 \n",
" 8451.531004 \n",
" 9082.351172 \n",
" 7738.881247 \n",
" 10159.583680 \n",
" 12002.239080 \n",
" 15389.924680 \n",
" \n",
" \n",
" Portugal \n",
" 3068.319867 \n",
" 3774.571743 \n",
" 4727.954889 \n",
" 6361.517993 \n",
" 9022.247417 \n",
" 10172.485720 \n",
" 11753.842910 \n",
" 13039.308760 \n",
" 16207.266630 \n",
" 17641.031560 \n",
" 19970.907870 \n",
" 20509.647770 \n",
" \n",
" \n",
" Romania \n",
" 3144.613186 \n",
" 3943.370225 \n",
" 4734.997586 \n",
" 6470.866545 \n",
" 8011.414402 \n",
" 9356.397240 \n",
" 9605.314053 \n",
" 9696.273295 \n",
" 6598.409903 \n",
" 7346.547557 \n",
" 7885.360081 \n",
" 10808.475610 \n",
" \n",
" \n",
" Serbia \n",
" 3581.459448 \n",
" 4981.090891 \n",
" 6289.629157 \n",
" 7991.707066 \n",
" 10522.067490 \n",
" 12980.669560 \n",
" 15181.092700 \n",
" 15870.878510 \n",
" 9325.068238 \n",
" 7914.320304 \n",
" 7236.075251 \n",
" 9786.534714 \n",
" \n",
" \n",
" Slovak Republic \n",
" 5074.659104 \n",
" 6093.262980 \n",
" 7481.107598 \n",
" 8412.902397 \n",
" 9674.167626 \n",
" 10922.664040 \n",
" 11348.545850 \n",
" 12037.267580 \n",
" 9498.467723 \n",
" 12126.230650 \n",
" 13638.778370 \n",
" 18678.314350 \n",
" \n",
" \n",
" Slovenia \n",
" 4215.041741 \n",
" 5862.276629 \n",
" 7402.303395 \n",
" 9405.489397 \n",
" 12383.486200 \n",
" 15277.030170 \n",
" 17866.721750 \n",
" 18678.534920 \n",
" 14214.716810 \n",
" 17161.107350 \n",
" 20660.019360 \n",
" 25768.257590 \n",
" \n",
" \n",
" Spain \n",
" 3834.034742 \n",
" 4564.802410 \n",
" 5693.843879 \n",
" 7993.512294 \n",
" 10638.751310 \n",
" 13236.921170 \n",
" 13926.169970 \n",
" 15764.983130 \n",
" 18603.064520 \n",
" 20445.298960 \n",
" 24835.471660 \n",
" 28821.063700 \n",
" \n",
" \n",
" Sweden \n",
" 8527.844662 \n",
" 9911.878226 \n",
" 12329.441920 \n",
" 15258.296970 \n",
" 17832.024640 \n",
" 18855.725210 \n",
" 20667.381250 \n",
" 23586.929270 \n",
" 23880.016830 \n",
" 25266.594990 \n",
" 29341.630930 \n",
" 33859.748350 \n",
" \n",
" \n",
" Switzerland \n",
" 14734.232750 \n",
" 17909.489730 \n",
" 20431.092700 \n",
" 22966.144320 \n",
" 27195.113040 \n",
" 26982.290520 \n",
" 28397.715120 \n",
" 30281.704590 \n",
" 31871.530300 \n",
" 32135.323010 \n",
" 34480.957710 \n",
" 37506.419070 \n",
" \n",
" \n",
" Turkey \n",
" 1969.100980 \n",
" 2218.754257 \n",
" 2322.869908 \n",
" 2826.356387 \n",
" 3450.696380 \n",
" 4269.122326 \n",
" 4241.356344 \n",
" 5089.043686 \n",
" 5678.348271 \n",
" 6601.429915 \n",
" 6508.085718 \n",
" 8458.276384 \n",
" \n",
" \n",
" United Kingdom \n",
" 9979.508487 \n",
" 11283.177950 \n",
" 12477.177070 \n",
" 14142.850890 \n",
" 15895.116410 \n",
" 17428.748460 \n",
" 18232.424520 \n",
" 21664.787670 \n",
" 22705.092540 \n",
" 26074.531360 \n",
" 29478.999190 \n",
" 33203.261280 \n",
" \n",
" \n",
"
\n",
"
"
],
"text/plain": [
" gdpPercap_1952 gdpPercap_1957 gdpPercap_1962 \\\n",
"country \n",
"Albania 1601.056136 1942.284244 2312.888958 \n",
"Austria 6137.076492 8842.598030 10750.721110 \n",
"Belgium 8343.105127 9714.960623 10991.206760 \n",
"Bosnia and Herzegovina 973.533195 1353.989176 1709.683679 \n",
"Bulgaria 2444.286648 3008.670727 4254.337839 \n",
"Croatia 3119.236520 4338.231617 5477.890018 \n",
"Czech Republic 6876.140250 8256.343918 10136.867130 \n",
"Denmark 9692.385245 11099.659350 13583.313510 \n",
"Finland 6424.519071 7545.415386 9371.842561 \n",
"France 7029.809327 8662.834898 10560.485530 \n",
"Germany 7144.114393 10187.826650 12902.462910 \n",
"Greece 3530.690067 4916.299889 6017.190733 \n",
"Hungary 5263.673816 6040.180011 7550.359877 \n",
"Iceland 7267.688428 9244.001412 10350.159060 \n",
"Ireland 5210.280328 5599.077872 6631.597314 \n",
"Italy 4931.404155 6248.656232 8243.582340 \n",
"Montenegro 2647.585601 3682.259903 4649.593785 \n",
"Netherlands 8941.571858 11276.193440 12790.849560 \n",
"Norway 10095.421720 11653.973040 13450.401510 \n",
"Poland 4029.329699 4734.253019 5338.752143 \n",
"Portugal 3068.319867 3774.571743 4727.954889 \n",
"Romania 3144.613186 3943.370225 4734.997586 \n",
"Serbia 3581.459448 4981.090891 6289.629157 \n",
"Slovak Republic 5074.659104 6093.262980 7481.107598 \n",
"Slovenia 4215.041741 5862.276629 7402.303395 \n",
"Spain 3834.034742 4564.802410 5693.843879 \n",
"Sweden 8527.844662 9911.878226 12329.441920 \n",
"Switzerland 14734.232750 17909.489730 20431.092700 \n",
"Turkey 1969.100980 2218.754257 2322.869908 \n",
"United Kingdom 9979.508487 11283.177950 12477.177070 \n",
"\n",
" gdpPercap_1967 gdpPercap_1972 gdpPercap_1977 \\\n",
"country \n",
"Albania 2760.196931 3313.422188 3533.003910 \n",
"Austria 12834.602400 16661.625600 19749.422300 \n",
"Belgium 13149.041190 16672.143560 19117.974480 \n",
"Bosnia and Herzegovina 2172.352423 2860.169750 3528.481305 \n",
"Bulgaria 5577.002800 6597.494398 7612.240438 \n",
"Croatia 6960.297861 9164.090127 11305.385170 \n",
"Czech Republic 11399.444890 13108.453600 14800.160620 \n",
"Denmark 15937.211230 18866.207210 20422.901500 \n",
"Finland 10921.636260 14358.875900 15605.422830 \n",
"France 12999.917660 16107.191710 18292.635140 \n",
"Germany 14745.625610 18016.180270 20512.921230 \n",
"Greece 8513.097016 12724.829570 14195.524280 \n",
"Hungary 9326.644670 10168.656110 11674.837370 \n",
"Iceland 13319.895680 15798.063620 19654.962470 \n",
"Ireland 7655.568963 9530.772896 11150.981130 \n",
"Italy 10022.401310 12269.273780 14255.984750 \n",
"Montenegro 5907.850937 7778.414017 9595.929905 \n",
"Netherlands 15363.251360 18794.745670 21209.059200 \n",
"Norway 16361.876470 18965.055510 23311.349390 \n",
"Poland 6557.152776 8006.506993 9508.141454 \n",
"Portugal 6361.517993 9022.247417 10172.485720 \n",
"Romania 6470.866545 8011.414402 9356.397240 \n",
"Serbia 7991.707066 10522.067490 12980.669560 \n",
"Slovak Republic 8412.902397 9674.167626 10922.664040 \n",
"Slovenia 9405.489397 12383.486200 15277.030170 \n",
"Spain 7993.512294 10638.751310 13236.921170 \n",
"Sweden 15258.296970 17832.024640 18855.725210 \n",
"Switzerland 22966.144320 27195.113040 26982.290520 \n",
"Turkey 2826.356387 3450.696380 4269.122326 \n",
"United Kingdom 14142.850890 15895.116410 17428.748460 \n",
"\n",
" gdpPercap_1982 gdpPercap_1987 gdpPercap_1992 \\\n",
"country \n",
"Albania 3630.880722 3738.932735 2497.437901 \n",
"Austria 21597.083620 23687.826070 27042.018680 \n",
"Belgium 20979.845890 22525.563080 25575.570690 \n",
"Bosnia and Herzegovina 4126.613157 4314.114757 2546.781445 \n",
"Bulgaria 8224.191647 8239.854824 6302.623438 \n",
"Croatia 13221.821840 13822.583940 8447.794873 \n",
"Czech Republic 15377.228550 16310.443400 14297.021220 \n",
"Denmark 21688.040480 25116.175810 26406.739850 \n",
"Finland 18533.157610 21141.012230 20647.164990 \n",
"France 20293.897460 22066.442140 24703.796150 \n",
"Germany 22031.532740 24639.185660 26505.303170 \n",
"Greece 15268.420890 16120.528390 17541.496340 \n",
"Hungary 12545.990660 12986.479980 10535.628550 \n",
"Iceland 23269.607500 26923.206280 25144.392010 \n",
"Ireland 12618.321410 13872.866520 17558.815550 \n",
"Italy 16537.483500 19207.234820 22013.644860 \n",
"Montenegro 11222.587620 11732.510170 7003.339037 \n",
"Netherlands 21399.460460 23651.323610 26790.949610 \n",
"Norway 26298.635310 31540.974800 33965.661150 \n",
"Poland 8451.531004 9082.351172 7738.881247 \n",
"Portugal 11753.842910 13039.308760 16207.266630 \n",
"Romania 9605.314053 9696.273295 6598.409903 \n",
"Serbia 15181.092700 15870.878510 9325.068238 \n",
"Slovak Republic 11348.545850 12037.267580 9498.467723 \n",
"Slovenia 17866.721750 18678.534920 14214.716810 \n",
"Spain 13926.169970 15764.983130 18603.064520 \n",
"Sweden 20667.381250 23586.929270 23880.016830 \n",
"Switzerland 28397.715120 30281.704590 31871.530300 \n",
"Turkey 4241.356344 5089.043686 5678.348271 \n",
"United Kingdom 18232.424520 21664.787670 22705.092540 \n",
"\n",
" gdpPercap_1997 gdpPercap_2002 gdpPercap_2007 \n",
"country \n",
"Albania 3193.054604 4604.211737 5937.029526 \n",
"Austria 29095.920660 32417.607690 36126.492700 \n",
"Belgium 27561.196630 30485.883750 33692.605080 \n",
"Bosnia and Herzegovina 4766.355904 6018.975239 7446.298803 \n",
"Bulgaria 5970.388760 7696.777725 10680.792820 \n",
"Croatia 9875.604515 11628.388950 14619.222720 \n",
"Czech Republic 16048.514240 17596.210220 22833.308510 \n",
"Denmark 29804.345670 32166.500060 35278.418740 \n",
"Finland 23723.950200 28204.590570 33207.084400 \n",
"France 25889.784870 28926.032340 30470.016700 \n",
"Germany 27788.884160 30035.801980 32170.374420 \n",
"Greece 18747.698140 22514.254800 27538.411880 \n",
"Hungary 11712.776800 14843.935560 18008.944440 \n",
"Iceland 28061.099660 31163.201960 36180.789190 \n",
"Ireland 24521.947130 34077.049390 40675.996350 \n",
"Italy 24675.024460 27968.098170 28569.719700 \n",
"Montenegro 6465.613349 6557.194282 9253.896111 \n",
"Netherlands 30246.130630 33724.757780 36797.933320 \n",
"Norway 41283.164330 44683.975250 49357.190170 \n",
"Poland 10159.583680 12002.239080 15389.924680 \n",
"Portugal 17641.031560 19970.907870 20509.647770 \n",
"Romania 7346.547557 7885.360081 10808.475610 \n",
"Serbia 7914.320304 7236.075251 9786.534714 \n",
"Slovak Republic 12126.230650 13638.778370 18678.314350 \n",
"Slovenia 17161.107350 20660.019360 25768.257590 \n",
"Spain 20445.298960 24835.471660 28821.063700 \n",
"Sweden 25266.594990 29341.630930 33859.748350 \n",
"Switzerland 32135.323010 34480.957710 37506.419070 \n",
"Turkey 6601.429915 6508.085718 8458.276384 \n",
"United Kingdom 26074.531360 29478.999190 33203.261280 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" \n",
" gdpPercap_1952 \n",
" gdpPercap_1957 \n",
" gdpPercap_1962 \n",
" gdpPercap_1967 \n",
" gdpPercap_1972 \n",
" gdpPercap_1977 \n",
" gdpPercap_1982 \n",
" gdpPercap_1987 \n",
" gdpPercap_1992 \n",
" gdpPercap_1997 \n",
" gdpPercap_2002 \n",
" gdpPercap_2007 \n",
" \n",
" \n",
" country \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Albania \n",
" 1601.056136 \n",
" 1942.284244 \n",
" 2312.888958 \n",
" 2760.196931 \n",
" 3313.422188 \n",
" 3533.00391 \n",
" 3630.880722 \n",
" 3738.932735 \n",
" 2497.437901 \n",
" 3193.054604 \n",
" 4604.211737 \n",
" 5937.029526 \n",
" \n",
" \n",
" Austria \n",
" 6137.076492 \n",
" 8842.598030 \n",
" 10750.721110 \n",
" 12834.602400 \n",
" 16661.625600 \n",
" 19749.42230 \n",
" 21597.083620 \n",
" 23687.826070 \n",
" 27042.018680 \n",
" 29095.920660 \n",
" 32417.607690 \n",
" 36126.492700 \n",
" \n",
" \n",
" Belgium \n",
" 8343.105127 \n",
" 9714.960623 \n",
" 10991.206760 \n",
" 13149.041190 \n",
" 16672.143560 \n",
" 19117.97448 \n",
" 20979.845890 \n",
" 22525.563080 \n",
" 25575.570690 \n",
" 27561.196630 \n",
" 30485.883750 \n",
" 33692.605080 \n",
" \n",
" \n",
"
\n",
"
"
],
"text/plain": [
" gdpPercap_1952 gdpPercap_1957 gdpPercap_1962 gdpPercap_1967 \\\n",
"country \n",
"Albania 1601.056136 1942.284244 2312.888958 2760.196931 \n",
"Austria 6137.076492 8842.598030 10750.721110 12834.602400 \n",
"Belgium 8343.105127 9714.960623 10991.206760 13149.041190 \n",
"\n",
" gdpPercap_1972 gdpPercap_1977 gdpPercap_1982 gdpPercap_1987 \\\n",
"country \n",
"Albania 3313.422188 3533.00391 3630.880722 3738.932735 \n",
"Austria 16661.625600 19749.42230 21597.083620 23687.826070 \n",
"Belgium 16672.143560 19117.97448 20979.845890 22525.563080 \n",
"\n",
" gdpPercap_1992 gdpPercap_1997 gdpPercap_2002 gdpPercap_2007 \n",
"country \n",
"Albania 2497.437901 3193.054604 4604.211737 5937.029526 \n",
"Austria 27042.018680 29095.920660 32417.607690 36126.492700 \n",
"Belgium 25575.570690 27561.196630 30485.883750 33692.605080 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.loc['Albania':'Belgium',:]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": true,
"jupyter": {
"outputs_hidden": true
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: matplotlib in ./Code/anaconda3/lib/python3.7/site-packages (3.1.3)\n",
"Requirement already satisfied: kiwisolver>=1.0.1 in ./Code/anaconda3/lib/python3.7/site-packages (from matplotlib) (1.1.0)\n",
"Requirement already satisfied: cycler>=0.10 in ./Code/anaconda3/lib/python3.7/site-packages (from matplotlib) (0.10.0)\n",
"Requirement already satisfied: python-dateutil>=2.1 in ./Code/anaconda3/lib/python3.7/site-packages (from matplotlib) (2.8.1)\n",
"Requirement already satisfied: numpy>=1.11 in ./Code/anaconda3/lib/python3.7/site-packages (from matplotlib) (1.18.1)\n",
"Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in ./Code/anaconda3/lib/python3.7/site-packages (from matplotlib) (2.4.6)\n",
"Requirement already satisfied: setuptools in ./Code/anaconda3/lib/python3.7/site-packages (from kiwisolver>=1.0.1->matplotlib) (45.2.0.post20200210)\n",
"Requirement already satisfied: six in ./Code/anaconda3/lib/python3.7/site-packages (from cycler>=0.10->matplotlib) (1.14.0)\n"
]
}
],
"source": [
"# to install the package on macOS\n",
"!pip install matplotlib"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"time = [0,1,2,3]\n",
"position = [0,100,150,225]\n",
"\n",
"plt.plot(time,position)\n",
"plt.xlabel('Time (hr)')\n",
"plt.ylabel('Position (m)')"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"time = [0,1,2,3]\n",
"position = [0,100,150,225]\n",
"\n",
"plt.plot(time,position,label='Data #1')\n",
"plt.xlabel('Time (hr)')\n",
"plt.ylabel('Position (m)')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(time,position,'.')"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(time,position,'g-')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": true,
"jupyter": {
"outputs_hidden": true
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on function plot in module matplotlib.pyplot:\n",
"\n",
"plot(*args, scalex=True, scaley=True, data=None, **kwargs)\n",
" Plot y versus x as lines and/or markers.\n",
" \n",
" Call signatures::\n",
" \n",
" plot([x], y, [fmt], *, data=None, **kwargs)\n",
" plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)\n",
" \n",
" The coordinates of the points or line nodes are given by *x*, *y*.\n",
" \n",
" The optional parameter *fmt* is a convenient way for defining basic\n",
" formatting like color, marker and linestyle. It's a shortcut string\n",
" notation described in the *Notes* section below.\n",
" \n",
" >>> plot(x, y) # plot x and y using default line style and color\n",
" >>> plot(x, y, 'bo') # plot x and y using blue circle markers\n",
" >>> plot(y) # plot y using x as index array 0..N-1\n",
" >>> plot(y, 'r+') # ditto, but with red plusses\n",
" \n",
" You can use `.Line2D` properties as keyword arguments for more\n",
" control on the appearance. Line properties and *fmt* can be mixed.\n",
" The following two calls yield identical results:\n",
" \n",
" >>> plot(x, y, 'go--', linewidth=2, markersize=12)\n",
" >>> plot(x, y, color='green', marker='o', linestyle='dashed',\n",
" ... linewidth=2, markersize=12)\n",
" \n",
" When conflicting with *fmt*, keyword arguments take precedence.\n",
" \n",
" \n",
" **Plotting labelled data**\n",
" \n",
" There's a convenient way for plotting objects with labelled data (i.e.\n",
" data that can be accessed by index ``obj['y']``). Instead of giving\n",
" the data in *x* and *y*, you can provide the object in the *data*\n",
" parameter and just give the labels for *x* and *y*::\n",
" \n",
" >>> plot('xlabel', 'ylabel', data=obj)\n",
" \n",
" All indexable objects are supported. This could e.g. be a `dict`, a\n",
" `pandas.DataFame` or a structured numpy array.\n",
" \n",
" \n",
" **Plotting multiple sets of data**\n",
" \n",
" There are various ways to plot multiple sets of data.\n",
" \n",
" - The most straight forward way is just to call `plot` multiple times.\n",
" Example:\n",
" \n",
" >>> plot(x1, y1, 'bo')\n",
" >>> plot(x2, y2, 'go')\n",
" \n",
" - Alternatively, if your data is already a 2d array, you can pass it\n",
" directly to *x*, *y*. A separate data set will be drawn for every\n",
" column.\n",
" \n",
" Example: an array ``a`` where the first column represents the *x*\n",
" values and the other columns are the *y* columns::\n",
" \n",
" >>> plot(a[0], a[1:])\n",
" \n",
" - The third way is to specify multiple sets of *[x]*, *y*, *[fmt]*\n",
" groups::\n",
" \n",
" >>> plot(x1, y1, 'g^', x2, y2, 'g-')\n",
" \n",
" In this case, any additional keyword argument applies to all\n",
" datasets. Also this syntax cannot be combined with the *data*\n",
" parameter.\n",
" \n",
" By default, each line is assigned a different style specified by a\n",
" 'style cycle'. The *fmt* and line property parameters are only\n",
" necessary if you want explicit deviations from these defaults.\n",
" Alternatively, you can also change the style cycle using the\n",
" 'axes.prop_cycle' rcParam.\n",
" \n",
" \n",
" Parameters\n",
" ----------\n",
" x, y : array-like or scalar\n",
" The horizontal / vertical coordinates of the data points.\n",
" *x* values are optional and default to `range(len(y))`.\n",
" \n",
" Commonly, these parameters are 1D arrays.\n",
" \n",
" They can also be scalars, or two-dimensional (in that case, the\n",
" columns represent separate data sets).\n",
" \n",
" These arguments cannot be passed as keywords.\n",
" \n",
" fmt : str, optional\n",
" A format string, e.g. 'ro' for red circles. See the *Notes*\n",
" section for a full description of the format strings.\n",
" \n",
" Format strings are just an abbreviation for quickly setting\n",
" basic line properties. All of these and more can also be\n",
" controlled by keyword arguments.\n",
" \n",
" This argument cannot be passed as keyword.\n",
" \n",
" data : indexable object, optional\n",
" An object with labelled data. If given, provide the label names to\n",
" plot in *x* and *y*.\n",
" \n",
" .. note::\n",
" Technically there's a slight ambiguity in calls where the\n",
" second label is a valid *fmt*. `plot('n', 'o', data=obj)`\n",
" could be `plt(x, y)` or `plt(y, fmt)`. In such cases,\n",
" the former interpretation is chosen, but a warning is issued.\n",
" You may suppress the warning by adding an empty format string\n",
" `plot('n', 'o', '', data=obj)`.\n",
" \n",
" Other Parameters\n",
" ----------------\n",
" scalex, scaley : bool, optional, default: True\n",
" These parameters determined if the view limits are adapted to\n",
" the data limits. The values are passed on to `autoscale_view`.\n",
" \n",
" **kwargs : `.Line2D` properties, optional\n",
" *kwargs* are used to specify properties like a line label (for\n",
" auto legends), linewidth, antialiasing, marker face color.\n",
" Example::\n",
" \n",
" >>> plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)\n",
" >>> plot([1,2,3], [1,4,9], 'rs', label='line 2')\n",
" \n",
" If you make multiple lines with one plot command, the kwargs\n",
" apply to all those lines.\n",
" \n",
" Here is a list of available `.Line2D` properties:\n",
" \n",
" agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array\n",
" alpha: float\n",
" animated: bool\n",
" antialiased or aa: bool\n",
" clip_box: `.Bbox`\n",
" clip_on: bool\n",
" clip_path: [(`~matplotlib.path.Path`, `.Transform`) | `.Patch` | None]\n",
" color or c: color\n",
" contains: callable\n",
" dash_capstyle: {'butt', 'round', 'projecting'}\n",
" dash_joinstyle: {'miter', 'round', 'bevel'}\n",
" dashes: sequence of floats (on/off ink in points) or (None, None)\n",
" drawstyle or ds: {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default'\n",
" figure: `.Figure`\n",
" fillstyle: {'full', 'left', 'right', 'bottom', 'top', 'none'}\n",
" gid: str\n",
" in_layout: bool\n",
" label: object\n",
" linestyle or ls: {'-', '--', '-.', ':', '', (offset, on-off-seq), ...}\n",
" linewidth or lw: float\n",
" marker: marker style\n",
" markeredgecolor or mec: color\n",
" markeredgewidth or mew: float\n",
" markerfacecolor or mfc: color\n",
" markerfacecoloralt or mfcalt: color\n",
" markersize or ms: float\n",
" markevery: None or int or (int, int) or slice or List[int] or float or (float, float)\n",
" path_effects: `.AbstractPathEffect`\n",
" picker: float or callable[[Artist, Event], Tuple[bool, dict]]\n",
" pickradius: float\n",
" rasterized: bool or None\n",
" sketch_params: (scale: float, length: float, randomness: float)\n",
" snap: bool or None\n",
" solid_capstyle: {'butt', 'round', 'projecting'}\n",
" solid_joinstyle: {'miter', 'round', 'bevel'}\n",
" transform: `matplotlib.transforms.Transform`\n",
" url: str\n",
" visible: bool\n",
" xdata: 1D array\n",
" ydata: 1D array\n",
" zorder: float\n",
" \n",
" Returns\n",
" -------\n",
" lines\n",
" A list of `.Line2D` objects representing the plotted data.\n",
" \n",
" See Also\n",
" --------\n",
" scatter : XY scatter plot with markers of varying size and/or color (\n",
" sometimes also called bubble chart).\n",
" \n",
" Notes\n",
" -----\n",
" **Format Strings**\n",
" \n",
" A format string consists of a part for color, marker and line::\n",
" \n",
" fmt = '[marker][line][color]'\n",
" \n",
" Each of them is optional. If not provided, the value from the style\n",
" cycle is used. Exception: If ``line`` is given, but no ``marker``,\n",
" the data will be a line without markers.\n",
" \n",
" Other combinations such as ``[color][marker][line]`` are also\n",
" supported, but note that their parsing may be ambiguous.\n",
" \n",
" **Markers**\n",
" \n",
" ============= ===============================\n",
" character description\n",
" ============= ===============================\n",
" ``'.'`` point marker\n",
" ``','`` pixel marker\n",
" ``'o'`` circle marker\n",
" ``'v'`` triangle_down marker\n",
" ``'^'`` triangle_up marker\n",
" ``'<'`` triangle_left marker\n",
" ``'>'`` triangle_right marker\n",
" ``'1'`` tri_down marker\n",
" ``'2'`` tri_up marker\n",
" ``'3'`` tri_left marker\n",
" ``'4'`` tri_right marker\n",
" ``'s'`` square marker\n",
" ``'p'`` pentagon marker\n",
" ``'*'`` star marker\n",
" ``'h'`` hexagon1 marker\n",
" ``'H'`` hexagon2 marker\n",
" ``'+'`` plus marker\n",
" ``'x'`` x marker\n",
" ``'D'`` diamond marker\n",
" ``'d'`` thin_diamond marker\n",
" ``'|'`` vline marker\n",
" ``'_'`` hline marker\n",
" ============= ===============================\n",
" \n",
" **Line Styles**\n",
" \n",
" ============= ===============================\n",
" character description\n",
" ============= ===============================\n",
" ``'-'`` solid line style\n",
" ``'--'`` dashed line style\n",
" ``'-.'`` dash-dot line style\n",
" ``':'`` dotted line style\n",
" ============= ===============================\n",
" \n",
" Example format strings::\n",
" \n",
" 'b' # blue markers with default shape\n",
" 'or' # red circles\n",
" '-g' # green solid line\n",
" '--' # dashed line with default color\n",
" '^k:' # black triangle_up markers connected by a dotted line\n",
" \n",
" **Colors**\n",
" \n",
" The supported color abbreviations are the single letter codes\n",
" \n",
" ============= ===============================\n",
" character color\n",
" ============= ===============================\n",
" ``'b'`` blue\n",
" ``'g'`` green\n",
" ``'r'`` red\n",
" ``'c'`` cyan\n",
" ``'m'`` magenta\n",
" ``'y'`` yellow\n",
" ``'k'`` black\n",
" ``'w'`` white\n",
" ============= ===============================\n",
" \n",
" and the ``'CN'`` colors that index into the default property cycle.\n",
" \n",
" If the color is the only part of the format string, you can\n",
" additionally use any `matplotlib.colors` spec, e.g. full names\n",
" (``'green'``) or hex strings (``'#008000'``).\n",
"\n"
]
}
],
"source": [
"help(plt.plot)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"data = pd.read_csv('data/gapminder_gdp_oceania.csv',index_col='country')"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['gdpPercap_1952', 'gdpPercap_1957', 'gdpPercap_1962', 'gdpPercap_1967',\n",
" 'gdpPercap_1972', 'gdpPercap_1977', 'gdpPercap_1982', 'gdpPercap_1987',\n",
" 'gdpPercap_1992', 'gdpPercap_1997', 'gdpPercap_2002', 'gdpPercap_2007'],\n",
" dtype='object')"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.columns"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAD5CAYAAADFqlkBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nO3deXxU5dn/8c9F2Pd9DRCQIPsaAipUXAG1onXDKotisVZbbV2q7fOrVevT2kWrtVpREFQsItiKiFKqoKJCCPsukbAEwhLCEpaELPfvj3PjM8YoISSZmeT7fr3mlZN77nPmumbOzDXnPmfOMeccIiJSuVUJdwAiIhJ+KgYiIqJiICIiKgYiIoKKgYiIAFXDHUBJNW3a1MXFxYU7DBGRqLJs2bIM51yzwu1RWwzi4uJITk4OdxgiIlHFzLYV1a5hIhEROXUxMLOaZpZkZqvMbJ2ZPeLbp5hZqpmt9Lc+vt3M7BkzSzGz1WbWL2RZY81ss7+NDWnvb2Zr/DzPmJmVRbIiIlK04gwT5QAXOueOmFk1YJGZvefvu985N7NQ/xFAvL8NBJ4HBppZY+BhIAFwwDIzm+2cO+D7TAAWA3OB4cB7iIhIuTjlloELHPH/VvO37zqHxUjgFT/fYqChmbUChgHznXOZvgDMB4b7++o75z53wbkxXgGuOoOcRETkNBVrn4GZxZjZSmAvwQf6En/X434o6Ckzq+Hb2gA7QmZP823f1Z5WRHtRcUwws2QzS963b19xQhcRkWIoVjFwzuU75/oAsUCimfUAHgK6AAOAxsAvffeixvtdCdqLimOicy7BOZfQrNk3jowSEZESOq2jiZxzB4GFwHDnXLofCsoBXgYSfbc0oG3IbLHArlO0xxbRLiIi5aQ4RxM1M7OGfroWcDGw0Y/144/8uQpY62eZDYzxRxUNAg4559KBecClZtbIzBoBlwLz/H1ZZjbIL2sM8HbppikiEv32HM5myqeplMWlB4pzNFErYKqZxRAUjxnOuTlm9qGZNSMY5lkJ/Nj3nwtcBqQAx4BbAJxzmWb2GLDU93vUOZfpp+8ApgC1CI4i0pFEIiIhDh3PZezkJHZkHuOS7i1p07BWqS7fovXiNgkJCU6/QBaRyiA7N5/Rk5awaschXr5lAOd1alriZZnZMudcQuH2qD0dhYhIZZCXX8Bdry8nedsBnr2x3xkVgu+i01GIiEQo5xy/+tca/rthL49e2Z3Le7Uqs8dSMRARiVB/nLeJGclp/OyieEafE1emj6ViICISgV76ZAvPL/ySmwa24+cXx5f546kYiIhEmH+tSON3727gsp4teXRkD8rj3J0qBiIiEWTBpr3c/+ZqzunYhKdu6ENMlfI5ibOKgYhIhFi+/QA/eW05Z7esx8Qx/alRNabcHlvFQEQkAqTszeLWKUtpXr8GU25JpF7NauX6+CoGIiJhtuvgcUZPSqJaTBVevXUgzerVOPVMpUzFQEQkjA4cPcGYyUkcyc5j6i2JtGtSOyxx6BfIIiJhcuxEHrdMWcr2zGO8cmsi3VrXD1ss2jIQEQmD3PwCfjJtOavTDvK3G/syqGOTsMajLQMRkXJWUOB4YOZqFm7axx9+0JNh3VuGOyRtGYiIlCfnHI/P3cC/Vuzkvks7MyqxXbhDAlQMRETK1T8+2sKkRamMOzeOOy/oFO5wvqJiICJSTmYk7+CJ9zdyZe/W/OaKbuVymoniUjEQESkH89fv4aG31jAkvil/vq43VcrpNBPFpWIgIlLGklIzuev15fRoXZ9/3Nyf6lUj76M38iISEalANu4+zPipS2nTqBaTxw2gTo3IPIhTxUBEpIzsyDzGmElJ1KlelVduTaRJ3fI/zURxqRiIiJSBjCM5jJmcRHZuPlNvTSS2UXhOM1Fckbm9IiISxY7k5HHLy0vZdfA4024byNkt64U7pFNSMRARKUU5efn8+NVlrE8/zMTR/UmIaxzukIpFw0QiIqUkv8Bx74xVLErJ4IlrenFR1xbhDqnYVAxEREqBc45H3lnHnNXpPDSiC9f2jw13SKdFxUBEpBT87cMUXvl8Gz8a0oHbzz8r3OGcNhUDEZEzNG3JNp6c/wU/6NeGh0Z0DXc4JaJiICJyBt5bk87//HstF3ZpzhPX9Iq400wUl4qBiEgJfZaSwd3TV9K3bUP+/sN+VIuJ3o/U6I1cRCSMVu04yI9eSSauaW0mjxtAreox4Q7pjKgYiIicppS9WYx7OYlGdarz6viBNKxdPdwhnbFTFgMzq2lmSWa2yszWmdkjvr2DmS0xs81m9oaZVfftNfz/Kf7+uJBlPeTbN5nZsJD24b4txcweLP00RURKx86Dxxk9KYmYKlV4bfxAWtSvGe6QSkVxtgxygAudc72BPsBwMxsEPAE85ZyLBw4A433/8cAB51wn4CnfDzPrBowCugPDgefMLMbMYoC/AyOAbsCNvq+ISETJOJLD6JeWcCQnj1duTSSuaZ1wh1RqTlkMXOCI/7eavzngQmCmb58KXOWnR/r/8fdfZMHlfEYC051zOc65VCAFSPS3FOfcFufcCWC67ysiEjGysnMZ93ISuw4dZ/K4AXRrXT/cIZWqYu0z8N/gVwJ7gfnAl8BB51ye75IGtPHTbYAdAP7+Q0CT0PZC83xbe1FxTDCzZDNL3rdvX3FCFxE5Y9m5+dw2NZmN6Vk8f1N/BkTJ+YZOR7GKgXMu3znXB4gl+CZf1K8qnP9b1EG2rgTtRcUx0TmX4JxLaNas2akDFxE5Q3n5Bdz1+gqStmbyl+t7c0GX5uEOqUyc1tFEzrmDwEJgENDQzE6e9TQW2OWn04C2AP7+BkBmaHuheb6tXUQkrAoKHL+ctYb/btjDI1d2Z2SfIgctKoTiHE3UzMwa+ulawMXABmABcK3vNhZ420/P9v/j7//QOed8+yh/tFEHIB5IApYC8f7opOoEO5lnl0ZyIiIl5Zzj8bkbmLU8jZ9f3Jkx58SFO6QyVZzrGbQCpvqjfqoAM5xzc8xsPTDdzH4HrAAm+f6TgFfNLIVgi2AUgHNunZnNANYDecCdzrl8ADO7C5gHxACTnXPrSi1DEZES+PuCFCYtSmXcuXH87KJO4Q6nzFnwpT36JCQkuOTk5HCHISIV0KuLt/H//r2Wq/u24S/X9Y7a8w0VxcyWOecSCrfrF8giIiFmr9rFb95ey8Vdm/PHa6P3xHOnS8VARMRbuGkvv3hjJQPiGvNslJ947nRVnkxFRL7Dsm2Z/Pi1ZZzdsh4vjU2gZrXoPvHc6VIxEJFKb0P6YW55eSmtGtRi6q2J1K9ZLdwhlTsVAxGp1LbvP8aYyUnUrl6VV8cn0rRujXCHFBYqBiJSae09nM3Nk5aQm1/Aq+MTiW1UO9whhY2KgYhUSoeO5TJmchIZR3KYcksi8S3qhTuksFIxEJFK59iJPG6dupQt+44ycXQCfdo2DHdIYadiICKVyom8Au54bTkrth/g6VF9GBzfNNwhRYTinI5CRKRCyC9w3PvmKj76Yh9/+EFPRvRsFe6QIoa2DESkUnDO8fDstbyzahcPjujCqMR24Q4poqgYiEil8OT8L3ht8XZuP78jPz7/rHCHE3FUDESkwpu0KJW/fZjCqAFteXB4l3CHE5FUDESkQpu1LI3H5qxnRI+WPH51T4JLskthKgYiUmHNX7+HB2atZnCnpvx1VB9iKskZSEtCxUBEKqTFW/Zz5+vL6dGmAS+M7k+NqpXrxHOnS8VARCqctTsPcdvUZNo3rs2UcQOoU0NH0Z+KioGIVChb9h1h7OQkGtSqxqvjB9KoTvVwhxQVVAxEpMJIO3CMm19aghm8dttAWjaoGe6QooaKgYhUCHsOZ3PTS0s4kpPH1FsT6dC0TrhDiioqBiIS9fYfyeHml5aQkZXD1FsT6d66QbhDijraqyIiUe3Q8eBU1DsOHGPKLYn0bdco3CFFJW0ZiEjUOpKTx7iXk/hiTxYvjE5gUMcm4Q4pamnLQESiUnZuPrdNXcrqtEM8d1M/zu/cLNwhRTVtGYhI1MnJy+fHry1jSWomT17fm2HdW4Y7pKinYiAiUSUvv4C7/7mShZuCaxKM7NMm3CFVCCoGIhI1Cgoc9725ivfX7ebh73fjhgG6JkFpUTEQkajgnOPX/17Lv1fu4v5hZ3PLeR3CHVKFomIgIhHPOcdjczbwz6Tt3HVBJ+68oFO4Q6pwVAxEJOI9Of8LJn+ayi3nxXHvpZ3DHU6FpGIgIhHtuYUpX12l7DdXdNPFacqIioGIRKyXP03lj+9vYmSf1rpKWRk7ZTEws7ZmtsDMNpjZOjO727f/1sx2mtlKf7ssZJ6HzCzFzDaZ2bCQ9uG+LcXMHgxp72BmS8xss5m9YWY656xIJffG0u088s56hnVvwV+u662rlJWx4mwZ5AH3Oue6AoOAO82sm7/vKedcH3+bC+DvGwV0B4YDz5lZjJnFAH8HRgDdgBtDlvOEX1Y8cAAYX0r5iUgUenvlTh58aw3nd27GMzf2pWqMBjHK2imfYedcunNuuZ/OAjYA3/Urj5HAdOdcjnMuFUgBEv0txTm3xTl3ApgOjLRgu+9CYKaffypwVUkTEpHoNm/dbn4xYxWJcY35x826XGV5Oa1ya2ZxQF9giW+6y8xWm9lkMzt5qsA2wI6Q2dJ827e1NwEOOufyCrUX9fgTzCzZzJL37dt3OqGLSBT46It9/PT1FfSKbcCkcQOoVV2FoLwUuxiYWV1gFnCPc+4w8DxwFtAHSAf+crJrEbO7ErR/s9G5ic65BOdcQrNmOimVSEWyZMt+bn81mU7N6zJlXCJ1dd3iclWsZ9vMqhEUgmnOubcAnHN7Qu5/EZjj/00D2obMHgvs8tNFtWcADc2sqt86CO0vIpXAiu0HuHXKUmIb1ebV8Yk0qF0t3CFVOsU5msiAScAG59yTIe2tQrpdDaz107OBUWZWw8w6APFAErAUiPdHDlUn2Mk82znngAXAtX7+scDbZ5aWiESL9bsOM3ZyEk3r1WDabQNpUrdGuEOqlIqzZXAeMBpYY2YrfduvCI4G6kMwpLMVuB3AObfOzGYA6wmORLrTOZcPYGZ3AfOAGGCyc26dX94vgelm9jtgBUHxEZEKLmVvFqMnLaFujapMu20gLerrAvbhYsEX8+iTkJDgkpOTwx2GiJTQtv1Huf6Fz8kvgBm3D6Jjs7rhDqlSMLNlzrmEwu06eFdEyt2ug8f54YtLyMkrYNptA1UIIoCKgYiUq31ZOdz80hIOH8/l1VsHcnbLeuEOSdA1kEWkHB04eoKbX1pC+qFsXh2fSM/YBuEOSTwVAxEpF4ezcxkzOYnU/Ud5edwAEuIahzskCaFhIhEpc8dO5HHry0vZkH6Yf9zcj/M6NQ13SFKIioGIlKns3HwmvLKM5dsP8PSovlzYpUW4Q5IiaJhIRMrEwWMnmLZkO1M+28q+rBz+cl1vLu/V6tQzSlioGIhIqdq2/yiTFqXyZnIax3PzGRLflKdH9eHcszQ0FMlUDESkVCzblsmLH6cyb/1uqlYxruzdhtuGdKBrq/rhDk2KQcVAREosv8Axb91uXvxkCyu2H6RBrWrccf5ZjD03TqeWiDIqBiJy2o7m5DEjeQeTP01lR+Zx2jWuzSNXdue6hFhqV9fHSjTSqyYixbbncDZTPtvKtMXbOJydR//2jfj1ZV25pFtLXaM4yqkYiMgpbUg/zIufbOGdVbvIL3AM696S24Z0pH/7RqeeWaKCioGIFMk5x0df7OOlT1JZlJJB7eox3DSwPbee14F2TWqHOzwpZSoGIvI1OXn5vL1iFy8t2sIXe47QvF4NHhh+NjclttcVyCowFQMRAYKTyE1bso2pn29jX1YOXVrW4y/X9eb7vVtTvapOVlDRqRiIVHJbM/yPxJbtIDu3gO91bsaT13dgcKemBFe9lcpAxUCkEnLOkbztAC9+vIX5G/ZQrUoVRvZpzW1DOur6ApWUioFIJbNx92F+9dYalm8/SMPa1bhzaCfGnNue5vX0I7HKTMVApJIoKHC8/NlWnnh/I/VrVuPRkd25tr9+JCYBrQUilcCew9nc9+YqPtmcwcVdW/DENT1pUrdGuMOSCKJiIFLBvb82nQffWkN2bj6PX92DHya2045h+QYVA5EK6mhOHo+8s44ZyWn0im3AUzf04axmdcMdlkQoFQORCmjF9gPc88ZKtmce484LzuKeiztTLUa/FZBvp2IgUoHk5Rfw9wVf8syHm2lZvyZvTDiHxA668LycmoqBSAWxff8x7nljBcu3H+Tqvm14ZGR36tfU6SOkeFQMRKKcc46Zy9L47ex1VKliPHNjX67s3TrcYUmUUTEQiWIHj53gV/9aw9w1uxnYoTFP3tCHNg1rhTssiUIqBiJRatHmDO59cyWZR0/w4Igu/GhIR11gRkpMxUAkyuTk5fOn9zfx0qJUzmpWh0ljB9CjTYNwhyVRTsVAJIps2p3F3dNXsHF3FqMHtedXl3WlVvWYcIclFcApDzw2s7ZmtsDMNpjZOjO727c3NrP5ZrbZ/23k283MnjGzFDNbbWb9QpY11vffbGZjQ9r7m9kaP88zpp9HinxNQYFj8qJUvv/sIjKO5DB5XAKPXdVDhUBKTXF+hZIH3Ouc6woMAu40s27Ag8AHzrl44AP/P8AIIN7fJgDPQ1A8gIeBgUAi8PDJAuL7TAiZb/iZpyZSMew9nM24KUt5dM56hnRqyvv3fI8Lu7QId1hSwZxymMg5lw6k++ksM9sAtAFGAkN9t6nAQuCXvv0V55wDFptZQzNr5fvOd85lApjZfGC4mS0E6jvnPvftrwBXAe+VTooi0Wveut08OGs1x3Pz+d1VPbhpoM4rJGXjtPYZmFkc0BdYArTwhQLnXLqZNffd2gA7QmZL823f1Z5WRHtRjz+BYAuCdu3anU7oIlHlaE4ej81Zz/SlO+jRpj5/vaEvnZrrvEJSdopdDMysLjALuMc5d/g7vp0UdYcrQfs3G52bCEwESEhIKLKPSLRbueMg90xfwbbMY/xkaHBeIV2DWMpasYqBmVUjKATTnHNv+eY9ZtbKbxW0Avb69jSgbcjsscAu3z60UPtC3x5bRH+RSiUvv4DnFn7J0x8E5xWa/qNBDOzYJNxhSSVRnKOJDJgEbHDOPRly12zg5BFBY4G3Q9rH+KOKBgGH/HDSPOBSM2vkdxxfCszz92WZ2SD/WGNCliVSKaRmHOWGiYt5cv4XXNGrFXPvHqJCIOWqOFsG5wGjgTVmttK3/Qr4AzDDzMYD24Hr/H1zgcuAFOAYcAuAcy7TzB4Dlvp+j57cmQzcAUwBahHsONbOY6nw0g8dZ+6a3by7ehfLtx+kXo2qPD2qDyP7FLnLTKRMWXDQT/RJSEhwycnJ4Q5D5LTsPpTN3DXpvLsmnWXbDgDQtVV9rujVimv6xdKygS5KL2XLzJY55xIKt+sXyCJlbPehbN5bm867q9NJ9gWgS8t63HdpZy7r2YqOuvqYRAAVA5EysOdwNu/5LYClW/+vANx7SWcu69VKl5+UiKNiIFJK9h7O5r21u3l3dTpLt2XiHJzdoh6/uCTYAtDvBCSSqRiInIG9Wdm8v3Y3c1ans3Tr/xWAey7qzOW9WtKpeb1whyhSLCoGIqdpb1Y283wBSPIFoHOLutx9UTyX92xFfAsVAIk+KgYixbAvK4f31wWHgSalZlLgoFPzuvzswngu79WKzioAEuVUDES+RcaRHN73+wCWpO6nwMFZzepw14XxXKECIBWMioFIIcu2ZTLx4y3MX7+HAgcdm9Xhrgs6cXmv1nRuUVdnDZUKScVABMgvcMxfv5uJH29h+faDNKhVjQnfO4ur+rbm7Bb1VACkwlMxkErt2Ik8Zi5LY9KiVLbtP0a7xrV55MruXJcQS+3qentI5aG1XSqlfVk5vPL5Vl5dvI2Dx3Lp07YhDw7vwqXdWxJTRVsBUvmoGEilkrI3i5c+SeWtFTvJzS/gkq4tmPC9jvRv30hDQVKpqRhIheecY0lqJi9+vIUPNu6lRtUqXNc/lvGDO+i8QCKeioFUWHn5Bcxdu5sXP97Cmp2HaFKnOvdcHM/oQe1pUrdGuMMTiSgqBlLhHMnJ442lO5i8KJWdB4/TsWkd/vfqnvygXxtqVosJd3giEUnFQCqM3YeymfLZVqYt2UZWdh6JcY357ZXduahLc6pop7DId1IxkKi3If0wL36yhXdW7SK/wDGiRytuG9KBvu0ahTs0kaihYiBRyTnHopQMJn68hU82Z1CrWgw3DWzPred1oF2T2uEOTyTqqBhIVDmRV8Cc1buY+PEWNu7Oolm9Gtw/7GxuGtiOhrWrhzs8kailYiBRIScvn6mfbWXyoq3sPpxNfPO6/PHaXozs05oaVbVTWORMqRhIxFu14yD3z1zFF3uOcO5ZTfj9NT0Z2rmZfiQmUopUDCRiZefm8/QHm3nhoy9pXq8mL48bwAVdmoc7LJEKScVAItLy7Qd4YOZqUvYe4fqEWH59eTca1KoW7rBEKiwVA4ko2bn5PDn/C176ZAst6tdkyi0DGHq2tgZEypqKgUSMZdsyuf/N1WzJOMqNie341WVdqFdTWwMi5UHFQMLu+Il8/vyfTUz+NJXWDWrx6vhEhsQ3C3dYIpWKioGEVVJqJg/MXMXW/ce4eVA7HhzRlbo1tFqKlDe96yQsjp3I44/vb2Lq51tp07AWr982kHM7NQ13WCKVloqBlLvFW/bzwMzVbM88xthz2vPA8C7U0daASFjpHSjl5mhOHk+8v5FXPt9Gu8a1mT5hEIM6Ngl3WCKCioGUk89SMnhg1mp2HjzOLefFcf+ws3XBeZEIonejlKkjOXn8fu4Gpi3ZToemdZhx+zkMiGsc7rBEpJAqp+pgZpPNbK+ZrQ1p+62Z7TSzlf52Wch9D5lZipltMrNhIe3DfVuKmT0Y0t7BzJaY2WYze8PMdOrJCmLR5gyGPfUxrydt57bBHZj7syEqBCIR6pTFAJgCDC+i/SnnXB9/mwtgZt2AUUB3P89zZhZjZjHA34ERQDfgRt8X4Am/rHjgADD+TBKS8DucnctDb63m5klLqFGtCjN/fA7/c0U3alXX2UVFItUph4mccx+bWVwxlzcSmO6cywFSzSwFSPT3pTjntgCY2XRgpJltAC4Efuj7TAV+Czxf3AQksizctJeH3lrDnsPZ3P69jvz8ks667rBIFDiTfQZ3mdkYIBm41zl3AGgDLA7pk+bbAHYUah8INAEOOufyiuj/DWY2AZgA0K5duzMIXUrboeO5PP7uemYkp9GpeV1m3XGuLjspEkWKM0xUlOeBs4A+QDrwF99e1AnmXQnai+Scm+icS3DOJTRrptMVRIoPN+5h2FMfM3NZGj8ZehZzfjpYhUAkypRoy8A5t+fktJm9CMzx/6YBbUO6xgK7/HRR7RlAQzOr6rcOQvtLhDt0LJdH56xn1vI0Oreoywujz6N324bhDktESqBExcDMWjnn0v2/VwMnjzSaDbxuZk8CrYF4IIlgCyDezDoAOwl2Mv/QOefMbAFwLTAdGAu8XdJkpPws2LiXX85azf6jJ/jphZ2468JOuvykSBQ7ZTEws38CQ4GmZpYGPAwMNbM+BEM6W4HbAZxz68xsBrAeyAPudM7l++XcBcwDYoDJzrl1/iF+CUw3s98BK4BJpZadlLqs7FwemxPsGzi7RT0mjR1Az9gG4Q5LRM6QOfetQ/QRLSEhwSUnJ4c7jErl05QMHpi5mvRDx7n9/LO45+J4bQ2IRBkzW+acSyjcrl8gyykdzcnj9+9t4LXF2+nYrA4z7ziXftpBLFKhqBjId0pKzeS+N1ex48Axxg/uwP3DztbvBkQqIBUDKVJ2bj5/mhdcfaxto9q8MeEcEjvoVBIiFZWKgXzDiu0HuPfNVWzZd5TRg9rz4Ahdb0CkotM7XL6Sk5fPX/+7mRc++pKW9Wvy2viBDI7X1cdEKgMVAwFg7c5D3DtjFZv2ZHF9Qiz/c0U36tesFu6wRKScqBhUcrn5Bfx9QQrPfphC4zrVmTwugQu7tAh3WCJSzlQMKrFNu7O4982VrN15mKv6tOa3V3anYW1dTkKkMlIxqITy8gt44eMtPP3fzdSrWZV/3Nyf4T1ahjssEQkjFYNK5st9R7h3xipW7jjIZT1b8tjIHjSpWyPcYYlImKkYVBIFBY7Jn6byp3mbqFU9hmdu7Mv3e7XCrKiziItIZaNiUAls23+U+99cTdLWTC7u2pz/vbonzevXDHdYIhJBVAwqsIICx7Ql2/j9exuJMePP1/Xmmn5ttDUgIt+gYlBB7Tx4nAdmruLTlP0MiW/KE9f0onXDWuEOS0QilIpBBeOc483kNB6ds54C53j86h78MLGdtgZE5DupGFQgKXuP8Pi761mwaR8DOzTmz9f1pm3j2uEOS0SigIpBlDt47ATvrNrFzOU7WbXjIDWrVeHh73dj7DlxVKmirQERKR4VgyiUm1/AR5v2MWt5Gh9s2MuJ/AK6tKzHry/rysi+rWleT0cKicjpUTGIIut2HWLWsp3MXrWTjCMnaFKnOjcNasc1/WLp3rq+9guISImpGES4fVk5vL1yJzOXpbFxdxbVYoyLurTgmv6xDD27GdViqoQ7RBGpAFQMIlB2bj4fbNjLrOVpfPTFPvILHL1jG/DoyO58v1drGtXRyeREpHSpGEQI5xwrdhxk1rI03lm1i8PZebSoX4MfDenItf3b0Kl5vXCHKCIVmIpBmO06eJx/rdjJrOVpbNl3lJrVqjCse0uu6RfLeZ2aEqMjgkSkHKgYhMGxE3m8v3Y3s5an8dmX+3EOEuMac/v3OnJZz1bU0xXGRKScqRiUk4ICx5LUTGYtT+O9NekcPZFP28a1+NmF8VzTL5Z2TfTjMBEJHxWDMrY14yhvrdjJW8vTSDtwnLo1qnJ5r1Zc0y+WAXGN9cMwEYkIKgal7NCxXD7fksGilAw+TdlPasZRzGBwp6bcd+nZDOveklrVY8IdpojI16gYnKGcvHyWbTvApykZLErZz5q0gxQ4qFM9hkEdmzB6UHtG9GxJqwY6Y6iIRC4Vg9NUUODYsPvwVx/+San7yc4tIKaK0bdtQ356YTxD4pvSu21D/SBMROPRhksAAArWSURBVKKGikExpB049tWH/2cpGew/egKA+OZ1GTWgHUPim5LYobGOAhKRqKViUITQcf9FmzPYuv8YAM3r1eD8zs04r1NTBsc3pYUuHSkiFcQpi4GZTQauAPY653r4tsbAG0AcsBW43jl3wIIzpT0NXAYcA8Y555b7ecYC/+MX+zvn3FTf3h+YAtQC5gJ3O+dcKeVXLCfH/RdtzuDTlAzW7Dz0tXH/MefEMSS+KZ2a19XJ4ESkQirOlsEU4FnglZC2B4EPnHN/MLMH/f+/BEYA8f42EHgeGOiLx8NAAuCAZWY22zl3wPeZACwmKAbDgffOPLVvd3Lcf9Hm4Nv/0q2ZXxv3/9lF8QzupHF/Eak8TlkMnHMfm1lcoeaRwFA/PRVYSFAMRgKv+G/2i82soZm18n3nO+cyAcxsPjDczBYC9Z1zn/v2V4CrKMNicN+bq/hw414yQ8b9b0xsx+BOGvcXkcqrpPsMWjjn0gGcc+lm1ty3twF2hPRL823f1Z5WRHuRzGwCwVYE7dq1K1Hg+QWOoZ2bMTi+Ked10ri/iAiU/g7kogbUXQnai+ScmwhMBEhISCjRfoWnbuhTktlERCq0kg6I7/HDP/i/e317GtA2pF8ssOsU7bFFtIuISDkqaTGYDYz102OBt0Pax1hgEHDIDyfNAy41s0Zm1gi4FJjn78sys0H+SKQxIcsSEZFyUpxDS/9JsAO4qZmlERwV9AdghpmNB7YD1/nucwkOK00hOLT0FgDnXKaZPQYs9f0ePbkzGbiD/zu09D3K+EgiERH5JivnQ/pLTUJCgktOTg53GCIiUcXMljnnEgq36yB6ERFRMRARERUDERFBxUBERIjiHchmtg/YVsLZmwIZpRhOJKnIuUHFzk+5Ra9oyq+9c65Z4caoLQZnwsySi9qbXhFU5NygYuen3KJXRchPw0QiIqJiICIilbcYTAx3AGWoIucGFTs/5Ra9oj6/SrnPQEREvq6ybhmIiEgIFQMREVExEBGRMBUDM4szs7XF6JdvZivNbK2ZvWlmtcsjvuIws8fNbIeZHSnUfp6ZHTGz1Wa20MxiQ+47mc9KM3MhuW0zsy/89GQzC+uFmEuYWzsz+4+ZbfC5rY+y3Nqb2admlh2am5ldEPKarfT3n3wdD5pZlpmti4TcfLwlee3+6HPYYGYFPrd1ZpZuZpv89B/KP5uvK2FuT/h1b21IbhG1XppZbTN718w2Fn6uzayGmb1hZilmtsRCrkdvZg/59k1mNsy3tTWzBf61XGdmdxc7EOdcud+AOGBtMfodCZmeBvziNB4jpoxzGAS0Co3Rt78LpPnpC4FXvyWf0OkFwC8ILgP6T+COKMxtIXDJydyA2lGW25vAvcDawrmF9GkMZJ6cl+DaHdN8fqfMLRJfO+Bc4FMgxt/yCa5fUhv4r8+tOvAJMCLKcrscmE9w3ZY6Prf6kbZe+uf6Aj/9teca+AnwDz89CnjDT3cDVgE1gA7Al/71awX0833qAV8A3YoVRxkl9/+Ajf6F+CdwH9DfB/858Cd8MQDGEVzd7H1gE/BwyHJCPzB/DDznp28GkoCVwAsnXyiCD6FHgSXAYGAA8Jl/3CT/5MT5J3u5v53r5x0KfAz8C1gP/AOoUozccgrllgFsDMktNyS3nGLk9hrBpT+jKbdUYFsk51ZEfrl8fb08BjxPUAwMOE6h9RKYQPDh/438gJ/7/tG2Xm7zr0ktgg+lfKBrEa/dydc5mnLbC3wQspxc4PpIWy+LyPdp4Ed+eh5wjp+u6nM14CHgoZB5vupXaFlv47+klXsxABL8k1rLP1mbCd50q4HzfZ/CxSAdaOLnWQskhH6o+CfhbYKronUF3gGq+fueA8b4aRfyYlcHtgAD/P/1/XJqAzV9WzyQHPLiZQMdCSrsfODaYuSWUyi39UC6n/6bj6mTn8f5+xcDx4vIrSdwEBgaZbldDxwGPgRWACf840REbt+SXwEh6yXwOvABwfr3Ax/Tbr6+Xi4FruCb6+Wd/rn5lOhcLzOALOAQcKKI9TIROAp0jrLcrvBxn0dw7qACgq2/iFkvi1hPG/rH6ej/XwvEhtz/pc/lWeDmkPZJRTx3cQRXoqxfnM/uU172sgQGA287544DmNk7BJtoDZ1zH/k+rwIjQuaZ75zb7/u/5ZeRDNQys5W+zyc+4QkE3wqWmhkEK8le3ycfmOWnzyZYQZYCOOcO++XXAZ41sz6+f+eQOJKcc1t8v3/6OGaeIrc7C+X2U+AtM1sB7CP4xrnPOXfczJ4ieHFmA1+a2XqCD86TuS0gWMH+Gk25EbzJqhN8GD5C8A0slWBIJRJyKyq/PELWSzPbDLwCnEVQHA4AC0LWy/8QrHvz+OZ62Q/Y42OPqvUSaONzfZHggzDLPxdHfW5TCN6LeQSXuo2a3JxzKWa2BJhBUDAg2IIbTeSsl18xs6oEWz7PnJyPYCugMPcd7SeXVdfHfs/JWE+lLIpBUUEeJSTQIhS+7+T/x51zfb628OAVm+qce6iI5WQ75/JD4ijqMX9O8MbtTbADPbsYcXz18EWH/7V++4Adzrm+ZnY7cJ5z7pC/7wjgnHNb/IfRb5xzM31eDxN88/lbtOVmwbWxdwMZzrk8M8sB3nHO3RkhuX1bfl+tl865XWb2C4IthF8TfGCcCOnbDVjtnMs1s6/WS59bX4LhgFZR+NpNANIIhjCPmNkJ4EXn3B99fpP9vLOjLTd/3yKCYvK0meUCE5xzc31ukbBehpoIbHbO/TWkLQ1oC6T5YtGA4EvWyfaTYgmGuvA7w2cB05xzb53iMb9SFkcTLQK+b2Y1fXW63LcfMrPBfvqmQvNcYmaNzawWcBXBN8xv8wFwrZk1B/DztS+i30agtZkN8P3qhTyZ6c65AoI3fEzIPIlm1sHMqgA3+FxON7fbQvpfART4GFsBVwOfmllT/7jrfWy3AcOAsdGYG7AGaAGs8/dFWm5F5Xfyi9AhMxvsX5OT6+VDBN8cQ9fLIcDU0AWG5HYjwc7WaHzt0gmGYhb7D5EYYIOP7Xc+rjujMTf/rf0agvdcL4LPu//42CJlvcQv7+RzfU+hu2b7GAGuBT50wRjQbGCUBUcbdSAYokryX5YnARucc09+2+MVGYMfWypVZvZbgjfINoKqvZBg58pkgk24eQTjWz3MbBzBURl1CMb5XnfOPeKXc8Q5V7eI5d9A8IatQjAkcadzbnHh/v6F+xvBpt9x4GKCve2zfBwLgJ865+qa2VDgNz7engQ7f37iX+SicqtO8AFY08/jCIZGdgAjfe7p/r5aQA/fd7ePO945V9MvM8/3zyIYM6zh54uW3DoR7AfpS/ANqgtQxzl3IlJyC8nvZwTjvDUIxopnEBylUpNgLLYuwTDmYuBSgvWyC9CMYGii4GS8hXKD4MiNzkTXetnJx1/H9+3knKtuweGZOwg+BHP8a1fFP2fRklu8jzuDYJ9WL+dcbb/MSFovCz/XAM86514ys5oE62Nfgi2CUSFDT78GbiUYwrvHOfeeL5CfEHxBO/lYvzq5NfSdirNj4XRvQF3/tzbBeGO/7+g7zideJrGcRsxDgTnKrWLmVtHzU27RmVsk3cpinwHARDPrRlDBpzrnlpfR44SDcoteFTk/5SZnRGctPQULjkaoUah5tHNuTTjiKU3KLXpV5PyUW3ioGIiIiE5UJyIiKgYiIoKKgYiIoGIgIiLA/wf8fa4XoGNq+gAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data.loc['Australia'].plot()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"' hello! '"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"' hello! '"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'hello'"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"' hello! '.strip().strip('!')"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"years = data.columns.str.strip('gdpPercap_')"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['1952', '1957', '1962', '1967', '1972', '1977', '1982', '1987', '1992',\n",
" '1997', '2002', '2007'],\n",
" dtype='object')"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"years"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"data.columns = years"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['1952', '1957', '1962', '1967', '1972', '1977', '1982', '1987', '1992',\n",
" '1997', '2002', '2007'],\n",
" dtype='object')"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.columns"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": true,
"jupyter": {
"outputs_hidden": true
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" \n",
" 1952 \n",
" 1957 \n",
" 1962 \n",
" 1967 \n",
" 1972 \n",
" 1977 \n",
" 1982 \n",
" 1987 \n",
" 1992 \n",
" 1997 \n",
" 2002 \n",
" 2007 \n",
" \n",
" \n",
" country \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Australia \n",
" 10039.59564 \n",
" 10949.64959 \n",
" 12217.22686 \n",
" 14526.12465 \n",
" 16788.62948 \n",
" 18334.19751 \n",
" 19477.00928 \n",
" 21888.88903 \n",
" 23424.76683 \n",
" 26997.93657 \n",
" 30687.75473 \n",
" 34435.36744 \n",
" \n",
" \n",
" New Zealand \n",
" 10556.57566 \n",
" 12247.39532 \n",
" 13175.67800 \n",
" 14463.91893 \n",
" 16046.03728 \n",
" 16233.71770 \n",
" 17632.41040 \n",
" 19007.19129 \n",
" 18363.32494 \n",
" 21050.41377 \n",
" 23189.80135 \n",
" 25185.00911 \n",
" \n",
" \n",
"
\n",
"
"
],
"text/plain": [
" 1952 1957 1962 1967 1972 \\\n",
"country \n",
"Australia 10039.59564 10949.64959 12217.22686 14526.12465 16788.62948 \n",
"New Zealand 10556.57566 12247.39532 13175.67800 14463.91893 16046.03728 \n",
"\n",
" 1977 1982 1987 1992 1997 \\\n",
"country \n",
"Australia 18334.19751 19477.00928 21888.88903 23424.76683 26997.93657 \n",
"New Zealand 16233.71770 17632.41040 19007.19129 18363.32494 21050.41377 \n",
"\n",
" 2002 2007 \n",
"country \n",
"Australia 30687.75473 34435.36744 \n",
"New Zealand 23189.80135 25185.00911 "
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data.loc['Australia'].plot()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": true,
"jupyter": {
"outputs_hidden": true
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" country \n",
" Australia \n",
" New Zealand \n",
" \n",
" \n",
" \n",
" \n",
" 1952 \n",
" 10039.59564 \n",
" 10556.57566 \n",
" \n",
" \n",
" 1957 \n",
" 10949.64959 \n",
" 12247.39532 \n",
" \n",
" \n",
" 1962 \n",
" 12217.22686 \n",
" 13175.67800 \n",
" \n",
" \n",
" 1967 \n",
" 14526.12465 \n",
" 14463.91893 \n",
" \n",
" \n",
" 1972 \n",
" 16788.62948 \n",
" 16046.03728 \n",
" \n",
" \n",
" 1977 \n",
" 18334.19751 \n",
" 16233.71770 \n",
" \n",
" \n",
" 1982 \n",
" 19477.00928 \n",
" 17632.41040 \n",
" \n",
" \n",
" 1987 \n",
" 21888.88903 \n",
" 19007.19129 \n",
" \n",
" \n",
" 1992 \n",
" 23424.76683 \n",
" 18363.32494 \n",
" \n",
" \n",
" 1997 \n",
" 26997.93657 \n",
" 21050.41377 \n",
" \n",
" \n",
" 2002 \n",
" 30687.75473 \n",
" 23189.80135 \n",
" \n",
" \n",
" 2007 \n",
" 34435.36744 \n",
" 25185.00911 \n",
" \n",
" \n",
"
\n",
"
"
],
"text/plain": [
"country Australia New Zealand\n",
"1952 10039.59564 10556.57566\n",
"1957 10949.64959 12247.39532\n",
"1962 12217.22686 13175.67800\n",
"1967 14526.12465 14463.91893\n",
"1972 16788.62948 16046.03728\n",
"1977 18334.19751 16233.71770\n",
"1982 19477.00928 17632.41040\n",
"1987 21888.88903 19007.19129\n",
"1992 23424.76683 18363.32494\n",
"1997 26997.93657 21050.41377\n",
"2002 30687.75473 23189.80135\n",
"2007 34435.36744 25185.00911"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.T"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'GDP per capita')"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data.T.plot()\n",
"plt.ylabel('GDP per capita')"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'GDP per capita')"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data.plot()\n",
"plt.ylabel('GDP per capita')"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'GDP per capita')"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.style.use('ggplot')\n",
"data.T.plot(kind='bar')\n",
"plt.ylabel('GDP per capita')"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(data.loc['Australia'],data.loc['New Zealand'])"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data.T.plot.scatter(x='Australia',y='New Zealand')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Fill in the blanks below to plot the minimum GDP per capita over time for all the countries in Europe. Modify it again to plot the maximum GDP per capita over time for Europe.\n",
"\n",
"```\n",
"data_europe = pd.read_csv('data/gapminder_gdp_europe.csv',index_col='country')\n",
"data_europe.____.plot(label='min')\n",
"data_europe.____\n",
"plt.legend(loc='best')\n",
"plt.xticks(rotation=90)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_europe = pd.read_csv('data/gapminder_gdp_europe.csv',index_col='country')\n",
"data_europe.columns = data_europe.columns.str.strip('gdpPercap_')\n",
"data_europe.max().plot(label='max')\n",
"data_europe.mean().plot(label='mean')\n",
"data_europe.min().plot(label='min')\n",
"plt.legend(loc='best')\n",
"#plt.xticks(rotation=90)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"data_europe = pd.read_csv('data/gapminder_gdp_europe.csv',index_col='country')\n"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"gdpPercap_1952 973.533195\n",
"gdpPercap_1957 1353.989176\n",
"gdpPercap_1962 1709.683679\n",
"gdpPercap_1967 2172.352423\n",
"gdpPercap_1972 2860.169750\n",
"gdpPercap_1977 3528.481305\n",
"gdpPercap_1982 3630.880722\n",
"gdpPercap_1987 3738.932735\n",
"gdpPercap_1992 2497.437901\n",
"gdpPercap_1997 3193.054604\n",
"gdpPercap_2002 4604.211737\n",
"gdpPercap_2007 5937.029526\n",
"dtype: float64"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_europe.min()"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"data_all = pd.read_csv('data/gapminder_all.csv',index_col='country')"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_all.plot(kind='scatter',x='gdpPercap_2007',y='lifeExp_2007')"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_all.plot(kind='scatter',\n",
" x='gdpPercap_2007',\n",
" y='lifeExp_2007',\n",
" s=data_all['pop_2007']/1e6)"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_all.plot(kind='scatter',\n",
" x='gdpPercap_2007',\n",
" y='lifeExp_2007',\n",
" s=data_all['pop_2007']/1e6)\n",
"plt.xlabel('Per-capita GDP')\n",
"plt.ylabel('Life expectancy')\n",
"plt.title('2007 Data')\n",
"plt.savefig('pop-corr.pdf',dpi=600)"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on function savefig in module matplotlib.pyplot:\n",
"\n",
"savefig(*args, **kwargs)\n",
" Save the current figure.\n",
" \n",
" Call signature::\n",
" \n",
" savefig(fname, dpi=None, facecolor='w', edgecolor='w',\n",
" orientation='portrait', papertype=None, format=None,\n",
" transparent=False, bbox_inches=None, pad_inches=0.1,\n",
" frameon=None, metadata=None)\n",
" \n",
" The output formats available depend on the backend being used.\n",
" \n",
" Parameters\n",
" ----------\n",
" \n",
" fname : str or PathLike or file-like object\n",
" A path, or a Python file-like object, or\n",
" possibly some backend-dependent object such as\n",
" `matplotlib.backends.backend_pdf.PdfPages`.\n",
" \n",
" If *format* is not set, then the output format is inferred from\n",
" the extension of *fname*, if any, and from :rc:`savefig.format`\n",
" otherwise. If *format* is set, it determines the output format.\n",
" \n",
" Hence, if *fname* is not a path or has no extension, remember to\n",
" specify *format* to ensure that the correct backend is used.\n",
" \n",
" Other Parameters\n",
" ----------------\n",
" \n",
" dpi : [ *None* | scalar > 0 | 'figure' ]\n",
" The resolution in dots per inch. If *None*, defaults to\n",
" :rc:`savefig.dpi`. If 'figure', uses the figure's dpi value.\n",
" \n",
" quality : [ *None* | 1 <= scalar <= 100 ]\n",
" The image quality, on a scale from 1 (worst) to 95 (best).\n",
" Applicable only if *format* is jpg or jpeg, ignored otherwise.\n",
" If *None*, defaults to :rc:`savefig.jpeg_quality` (95 by default).\n",
" Values above 95 should be avoided; 100 completely disables the\n",
" JPEG quantization stage.\n",
" \n",
" optimize : bool\n",
" If *True*, indicates that the JPEG encoder should make an extra\n",
" pass over the image in order to select optimal encoder settings.\n",
" Applicable only if *format* is jpg or jpeg, ignored otherwise.\n",
" Is *False* by default.\n",
" \n",
" progressive : bool\n",
" If *True*, indicates that this image should be stored as a\n",
" progressive JPEG file. Applicable only if *format* is jpg or\n",
" jpeg, ignored otherwise. Is *False* by default.\n",
" \n",
" facecolor : color spec or None, optional\n",
" The facecolor of the figure; if *None*, defaults to\n",
" :rc:`savefig.facecolor`.\n",
" \n",
" edgecolor : color spec or None, optional\n",
" The edgecolor of the figure; if *None*, defaults to\n",
" :rc:`savefig.edgecolor`\n",
" \n",
" orientation : {'landscape', 'portrait'}\n",
" Currently only supported by the postscript backend.\n",
" \n",
" papertype : str\n",
" One of 'letter', 'legal', 'executive', 'ledger', 'a0' through\n",
" 'a10', 'b0' through 'b10'. Only supported for postscript\n",
" output.\n",
" \n",
" format : str\n",
" The file format, e.g. 'png', 'pdf', 'svg', ... The behavior when\n",
" this is unset is documented under *fname*.\n",
" \n",
" transparent : bool\n",
" If *True*, the axes patches will all be transparent; the\n",
" figure patch will also be transparent unless facecolor\n",
" and/or edgecolor are specified via kwargs.\n",
" This is useful, for example, for displaying\n",
" a plot on top of a colored background on a web page. The\n",
" transparency of these patches will be restored to their\n",
" original values upon exit of this function.\n",
" \n",
" bbox_inches : str or `~matplotlib.transforms.Bbox`, optional\n",
" Bbox in inches. Only the given portion of the figure is\n",
" saved. If 'tight', try to figure out the tight bbox of\n",
" the figure. If None, use savefig.bbox\n",
" \n",
" pad_inches : scalar, optional\n",
" Amount of padding around the figure when bbox_inches is\n",
" 'tight'. If None, use savefig.pad_inches\n",
" \n",
" bbox_extra_artists : list of `~matplotlib.artist.Artist`, optional\n",
" A list of extra artists that will be considered when the\n",
" tight bbox is calculated.\n",
" \n",
" metadata : dict, optional\n",
" Key/value pairs to store in the image metadata. The supported keys\n",
" and defaults depend on the image format and backend:\n",
" \n",
" - 'png' with Agg backend: See the parameter ``metadata`` of\n",
" `~.FigureCanvasAgg.print_png`.\n",
" - 'pdf' with pdf backend: See the parameter ``metadata`` of\n",
" `~.backend_pdf.PdfPages`.\n",
" - 'eps' and 'ps' with PS backend: Only 'Creator' is supported.\n",
" \n",
" pil_kwargs : dict, optional\n",
" Additional keyword arguments that are passed to `PIL.Image.save`\n",
" when saving the figure. Only applicable for formats that are saved\n",
" using Pillow, i.e. JPEG, TIFF, and (if the keyword is set to a\n",
" non-None value) PNG.\n",
"\n"
]
}
],
"source": [
"help(plt.savefig)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 4
}