++++Data Science
May 2026×Notebook lesson
Notebook converted from Jupyter for blog publishing.
06-Matrix-Plots
Driptanil DattaSoftware Developer
Matrix Plots
NOTE: Make sure to watch the video lecture, not all datasets are well suited for a heatmap or clustermap.
Imports
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as snsThe Data
World Population Prospects publishes United Nations population estimates for all world countries and every year from 1950 to 2020, as well as projections for different scenarios (low, middle and high variants) from 2020 to 2100. The figures presented here correspond to middle variant projections for the given year.
Source : Estimates for the current year based on data from the World Population Prospects. United Nations.
# 2020 Projections
df = pd.read_csv('country_table.csv')dfHTML
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Countries
Birth rate
Mortality rate
Life expectancy
Infant mortality rateHeatmap
df = df.set_index('Countries')dfHTML
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Birth rate
Mortality rate
Life expectancy
Infant mortality rate
Growth rate# Clearly shows life expectancy in different units
sns.heatmap(df)RESULT
<AxesSubplot:ylabel='Countries'>PLOT
rates = df.drop('Life expectancy',axis=1)sns.heatmap(rates)RESULT
<AxesSubplot:ylabel='Countries'>PLOT
sns.heatmap(rates,linewidth=0.5)RESULT
<AxesSubplot:ylabel='Countries'>PLOT
sns.heatmap(rates,linewidth=0.5,annot=True)RESULT
<AxesSubplot:ylabel='Countries'>PLOT
# Note how its not palette here
sns.heatmap(rates,linewidth=0.5,annot=True,cmap='viridis')RESULT
<AxesSubplot:ylabel='Countries'>PLOT
# Set colorbar based on value from dataset
sns.heatmap(rates,linewidth=0.5,annot=True,cmap='viridis',center=40)RESULT
<AxesSubplot:ylabel='Countries'>PLOT
# Set colorbar based on value from dataset
sns.heatmap(rates,linewidth=0.5,annot=True,cmap='viridis',center=1)RESULT
<AxesSubplot:ylabel='Countries'>PLOT
Clustermap
Plot a matrix dataset as a hierarchically-clustered heatmap.
sns.clustermap(rates)RESULT
<seaborn.matrix.ClusterGrid at 0x158e27976c8>PLOT
sns.clustermap(rates,col_cluster=False)RESULT
<seaborn.matrix.ClusterGrid at 0x158e235c9c8>PLOT
sns.clustermap(rates,col_cluster=False,figsize=(12,8),cbar_pos=(-0.1, .2, .03, .4))RESULT
<seaborn.matrix.ClusterGrid at 0x158e2ffc848>PLOT
rates.index.set_names('',inplace=True)ratesHTML
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Birth rate
Mortality rate
Infant mortality rate
Growth rate
AFRICA# Recall you can always edit the DF before seaborn
sns.clustermap(rates,col_cluster=False,figsize=(12,8),cbar_pos=(-0.1, .2, .03, .4))RESULT
<seaborn.matrix.ClusterGrid at 0x158e354b508>PLOT
