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Population Pyramid Charts in Python

How to make Population Pyramid Charts in Python with Plotly.

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Basic Population Pyramid Chart

If you're starting with binned data, use a go.Bar trace.

In [1]:
import plotly.plotly as py
import plotly.graph_objs as go

import numpy as np

women_bins = np.array([-600, -623, -653, -650, -670, -578, -541, -411, -322, -230])
men_bins = np.array([600, 623, 653, 650, 670, 578, 541, 360, 312, 170])

y = list(range(0, 100, 10))

layout = go.Layout(yaxis=go.layout.YAxis(title='Age'),
                   xaxis=go.layout.XAxis(
                       range=[-1200, 1200],
                       tickvals=[-1000, -700, -300, 0, 300, 700, 1000],
                       ticktext=[1000, 700, 300, 0, 300, 700, 1000],
                       title='Number'),
                   barmode='overlay',
                   bargap=0.1)

data = [go.Bar(y=y,
               x=men_bins,
               orientation='h',
               name='Men',
               hoverinfo='x',
               marker=dict(color='powderblue')
               ),
        go.Bar(y=y,
               x=women_bins,
               orientation='h',
               name='Women',
               text=-1 * women_bins.astype('int'),
               hoverinfo='text',
               marker=dict(color='seagreen')
               )]

py.iplot(dict(data=data, layout=layout), filename='EXAMPLES/bar_pyramid') 
Out[1]:

Stacked Population Pyramid

In [2]:
import plotly.plotly as py
import plotly.graph_objs as go

import numpy as np

women_bins = np.array([-600, -623, -653, -650, -670, -578, -541, -411, -322, -230])
men_bins = np.array([600, 623, 653, 650, 670, 578, 541, 360, 312, 170])
women_with_dogs_bins = np.array([-0, -3, -308, -281, -245, -231, -212, -132, -74, -76])
men_with_dogs_bins = np.array([0, 1, 300, 273, 256, 211, 201, 170, 145, 43])

y = list(range(0, 100, 10))

layout = go.Layout(yaxis=go.layout.YAxis(title='Age'),
                   xaxis=go.layout.XAxis(
                       range=[-1200, 1200],
                       tickvals=[-1000, -700, -300, 0, 300, 700, 1000],
                       ticktext=[1000, 700, 300, 0, 300, 700, 1000],
                       title='Number'),
                   barmode='overlay',
                   bargap=0.1)

data = [go.Bar(y=y,
               x=men_bins,
               orientation='h',
               name='Men',
               hoverinfo='x',
               marker=dict(color='powderblue')
               ),
        go.Bar(y=y,
               x=women_bins,
               orientation='h',
               name='Women',
               text=-1 * women_bins.astype('int'),
               hoverinfo='text',
               marker=dict(color='seagreen')
               ),
        go.Bar(y=y,
               x=men_with_dogs_bins,
               orientation='h',
               hoverinfo='x',
               showlegend=False,
               opacity=0.5,
               marker=dict(color='teal')
               ),
        go.Bar(y=y,
               x=women_with_dogs_bins,
               orientation='h',
               text=-1 * women_bins.astype('int'),
               hoverinfo='text',
               showlegend=False,
               opacity=0.5,
               marker=dict(color='darkgreen')
               )]

py.iplot(dict(data=data, layout=layout), filename='EXAMPLES/stacked_bar_pyramid')
Out[2]:

Population Pyramid with Binning

If you want to quickly create a Population Pyramid from raw data, try go.Histogram.

In [3]:
import plotly.plotly as py
import plotly.graph_objs as go

import numpy as np

layout = go.Layout(barmode='overlay',
                   yaxis=go.layout.YAxis(range=[0, 90], title='Age'),
                   xaxis=go.layout.XAxis(
                       tickvals=[-150, -100, -50, 0, 50, 100, 150],
                       ticktext=[150, 100, 50, 0, 50, 100, 150],
                       title='Number'))

data = [go.Histogram(
    y=np.random.exponential(50, 1000),
    orientation='h',
    name='Men',
    marker=dict(color='plum'),
    hoverinfo='skip'
),
    go.Histogram(
        y=np.random.exponential(55, 1000),
        orientation='h',
        name='Women',
        marker=dict(color='purple'),
        hoverinfo='skip',
        x=-1 * np.ones(1000),
        histfunc="sum"
    )
]

py.iplot(dict(data=data, layout=layout), filename='EXAMPLES/histogram_pyramid')
Out[3]:

More Bar and Histogram Examples

See more examples of horizontal bar charts, bar charts and histograms.

Reference

See https://plot.ly/python/reference/#bar and https://plot.ly/python/reference/#histogram for more information and chart attribute options!