import geopandas

world = geopandas.read_file(geopandas.datasets.get_path("naturalearth_lowres"))

world.head()

world = world[(world.pop_est > 0) & (world.continent != 'Antarctica')]

world['gdp_per_cap'] = world.gdp_md_est / world.pop_est

world.plot(column='gdp_per_cap')

<matplotlib.axes._subplots.AxesSubplot at 0x126780ac8>

world.continent.unique()

array(['Oceania', 'Africa', 'North America', 'Asia', 'South America',
       'Europe', 'Seven seas (open ocean)'], dtype=object)

# Show only Asia

asia = world[world.continent == 'Asia']

asia['gdp_per_cap'] = asia.gdp_md_est / asia.pop_est

/Users/rajacsp/anaconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  """Entry point for launching an IPython kernel.

asia.plot(column='gdp_per_cap')

<matplotlib.axes._subplots.AxesSubplot at 0x1268cf668>

# Show only Europe

eu = world[world.continent == 'Europe']
eu['gdp_per_cap'] = eu.gdp_md_est / eu.pop_est
eu.plot(column='gdp_per_cap')

/Users/rajacsp/anaconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy






<matplotlib.axes._subplots.AxesSubplot at 0x126a12ef0>

# South America

sa = world[world.continent == 'South America']
sa['gdp_per_cap'] = sa.gdp_md_est / sa.pop_est
sa.plot(column='gdp_per_cap')

/Users/rajacsp/anaconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  after removing the cwd from sys.path.





<matplotlib.axes._subplots.AxesSubplot at 0x126bc0470>

# With Legend

import matplotlib.pyplot as plt

fig, ax = plt.subplots(1, 1)

sa = world[world.continent == 'South America']
sa['gdp_per_cap'] = sa.gdp_md_est / sa.pop_est

sa.plot(column = 'pop_est', ax=ax, legend=True)

/Users/rajacsp/anaconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  after removing the cwd from sys.path.





<matplotlib.axes._subplots.AxesSubplot at 0x126b8c588>

fig, ax = plt.subplots(1, 1)

asia = world[world.continent == 'Asia']
asia['gdp_per_cap'] = asia.gdp_md_est / asia.pop_est

asia.plot(column = 'pop_est', ax=ax, legend=True)

/Users/rajacsp/anaconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  after removing the cwd from sys.path.





<matplotlib.axes._subplots.AxesSubplot at 0x127002ef0>

fig, ax = plt.subplots(1, 1)

asia = world[world['continent'] == 'Asia']
asia['gdp_per_cap'] = asia['gdp_md_est'] / asia['pop_est']

from mpl_toolkits.axes_grid1 import make_axes_locatable

divider = make_axes_locatable(ax)

cax = divider.append_axes("right", size="4%", pad=0.1)

asia.plot(column = 'pop_est', ax=ax, legend=True, cax=cax)

/Users/rajacsp/anaconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  after removing the cwd from sys.path.





<matplotlib.axes._subplots.AxesSubplot at 0x127e412e8>

fig, ax = plt.subplots(1, 1)

asia = world[world['continent'] == 'Asia']
asia['gdp_per_cap'] = asia['gdp_md_est'] / asia['pop_est']

from mpl_toolkits.axes_grid1 import make_axes_locatable

divider = make_axes_locatable(ax)

cax = divider.append_axes("right", size="4%", pad=0.1)

asia.plot(column = 'pop_est', ax=ax, legend=True, cax=cax, cmap='YlOrRd')

/Users/rajacsp/anaconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  after removing the cwd from sys.path.





<matplotlib.axes._subplots.AxesSubplot at 0x1282e8f98>

from geopy.geocoders import Nominatim
geoloc = Nominatim(user_agent="rajarcsp", format_string="%s, Toronto ON")

address, (lat, long) = geoloc.geocode("26, Spadina Road")

address

'Spadina Road, The Annex, University—Rosedale, Old Toronto, Toronto, Ontario, M5R 2X3, Canada'

from geopy.geocoders import Nominatim
geolocator = Nominatim(user_agent="rajarcsp")
from geopy import distance

l_spadina = geolocator.geocode("28 Spadina Road")

l_spadina_latlong = l_spadina.latitude, l_spadina.longitude

l_spadina_latlong

(43.6966329769175, -79.7940236288173)

l_north_york = geolocator.geocode("5000 Yonge Street")

l_north_york_latlong …

from geopy.geocoders import Nominatim
geolocator = Nominatim(user_agent="rajarcsp")
from geopy import distance

def get_distance(one, two):
    cone = geolocator.geocode(one)
    ctwo = geolocator.geocode(two)

    one_latlong = cone.latitude, ctwo.longitude
    two_latlong = ctwo.latitude, ctwo.longitude …

import pandas as pd
import geopandas
import matplotlib.pyplot as plt
from geopy.geocoders import Nominatim

geolocator = Nominatim(user_agent="rajarcsp")

def get_lat_lang(city):
    location = geolocator.geocode(city)
    return location.latitude, location.longitude

to_lat, to_long = get_lat_lang …

import pandas as pd
import geopandas
import matplotlib.pyplot as plt

df = pd.DataFrame(
    {'City': ['Buenos Aires', 'Brasilia', 'Santiago', 'Bogota', 'Caracas'],
     'Country': ['Argentina', 'Brazil', 'Chile', 'Colombia', 'Venezuela'],
     'Latitude': [-34.58, -15.78, -33.45, 4 …

from geopy.geocoders import Nominatim

geolocator = Nominatim(user_agent="rajarcsp")

location = geolocator.geocode("175 5th Avenue NYC")

location

Location(Flatiron Building, 175, 5th Avenue, Flatiron District, Manhattan, Manhattan Community Board 5, New York County, NYC, New York, 10010 …

import geopandas

world = geopandas.read_file(geopandas.datasets.get_path("naturalearth_lowres"))

world