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Wednesday, 17 April 2019

Data Visualization using Heatmap (Seaborn Library)

Lets visualize our data with Heatmap which is present in Seaborn library. Heatmap is full of colors. Darker the color, higher is the value and vice versa. Values closer to 1 represent higher values and values closer to 0 represent lower values. We will use Flights dataset and analyze it through heatmap. We can pass various parameters to heatmap like annot, fmt, vmin, vmax, cbar, cmap, linewidths, center etc. Lets explore heatmap in detail: 

Step 1: Import required libraries

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
#matplotlib inline

Step 2: Load Flights datasets

flights = sns.load_dataset('flights')

Step 3: Explore data using Heat Map

Please note that I am not displaying the resulting maps in this post. Please explore it yourself in your Jupyter notebook.

Before exploring Flights dataset with Heatmap, lets first analyze some random numbers using Heatmap:

numbers = np.random.randn(12, 15)


sns.heatmap(numbers, annot=True)  #to show actual values in the heatmap

sns.heatmap(numbers, annot=True, vmin=0, vmax=2)  #to change the key value of heatmap, by default key varies from 0 and 1.

sns.heatmap(flights, cbar=False)  #to hide the color bar

Now, lets jump to our Flights dataset. Lets pivot this dataset so that we have "year" on x-axis and "month" on y-axis.

flights = flights.pivot('month', 'year', 'passengers')


sns.heatmap(flights, annot=True)

sns.heatmap(flights, annot=True, fmt='d')  #format the annotation to contain only digits

sns.heatmap(flights, annot=True, fmt='d', linewidths=0.9)  #add linewidth to heatmap

sns.heatmap(flights, annot=True, fmt='d', linewidths=0.9, cmap='RdBu')  #add color map to heatmap to change the color

sns.heatmap(flights, annot=True, fmt='d', linewidths=0.9, cmap='summer')

sns.heatmap(flights, annot=True, fmt='d', linewidths=0.9, cmap='winter_r')

sns.heatmap(flights, annot=True, fmt='d', linewidths=0.9, cmap='coolwarm')

sns.heatmap(flights, annot=True, fmt='d', center=flights.loc['June', 1954])  #center color theme to a particular cell

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