Plotly - geographical plotting¶

In [1]:

import plotly.plotly as py
import plotly.graph_objs as go
import pandas as pd
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)

import plotly.plotly as py import plotly.graph_objs as go import pandas as pd from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot init_notebook_mode(connected=True)

Choropleth map of USA¶

Create some data for plotting. Plotly needs this notation

In [2]:

data = dict(type='choropleth', locations=['AZ','CA','NY'],
           locationmode='USA-states', colorscale='Greens',
           text=['text 1', 'text 2', 'text 3'],
           z=[1,2,3], colorbar={'title':'Color bar title here'})

layout = dict(geo={'scope':'usa'})

data = dict(type='choropleth', locations=['AZ','CA','NY'], locationmode='USA-states', colorscale='Greens', text=['text 1', 'text 2', 'text 3'], z=[1,2,3], colorbar={'title':'Color bar title here'}) layout = dict(geo={'scope':'usa'})

In [3]:

layout

layout

Out[3]:

{'geo': {'scope': 'usa'}}

In [4]:

choro_map = go.Figure(data=[data], layout=layout)
choro_map

choro_map = go.Figure(data=[data], layout=layout) choro_map

Out[4]:

{'data': [{'colorbar': {'title': 'Color bar title here'},
   'colorscale': 'Greens',
   'locationmode': 'USA-states',
   'locations': ['AZ', 'CA', 'NY'],
   'text': ['text 1', 'text 2', 'text 3'],
   'type': 'choropleth',
   'z': [1, 2, 3]}],
 'layout': {'geo': {'scope': 'usa'}}}

In [5]:

iplot(choro_map)

iplot(choro_map)

World choropleth maps¶

In [6]:

world_gdp_df = pd.read_csv('/Users/atma6951/Documents/code/pychakras/pychakras/udemy_ml_bootcamp/Python-for-Data-Visualization/Geographical Plotting/2014_World_GDP')
world_gdp_df.head()

world_gdp_df = pd.read_csv('/Users/atma6951/Documents/code/pychakras/pychakras/udemy_ml_bootcamp/Python-for-Data-Visualization/Geographical Plotting/2014_World_GDP') world_gdp_df.head()

Out[6]:

	COUNTRY	GDP (BILLIONS)	CODE
0	Afghanistan	21.71	AFG
1	Albania	13.40	ALB
2	Algeria	227.80	DZA
3	American Samoa	0.75	ASM
4	Andorra	4.80	AND

In [7]:

data = {'type':'choropleth', 'locations':world_gdp_df['CODE'],
       'z':world_gdp_df['GDP (BILLIONS)'], 'text':world_gdp_df['COUNTRY'],
       'colorbar':{'title':'GDP in Billions USD'}}

layout={'title':'2014 Global GDP',
       'geo':{'showframe':False, 'projection':{'type':'Mercator'}}}

choromap3 = go.Figure(data=[data], layout=layout)

data = {'type':'choropleth', 'locations':world_gdp_df['CODE'], 'z':world_gdp_df['GDP (BILLIONS)'], 'text':world_gdp_df['COUNTRY'], 'colorbar':{'title':'GDP in Billions USD'}} layout={'title':'2014 Global GDP', 'geo':{'showframe':False, 'projection':{'type':'Mercator'}}} choromap3 = go.Figure(data=[data], layout=layout)

In [8]:

iplot(choromap3)

iplot(choromap3)

In [ ]: