Now let’s discuss using seaborn to plot categorical data! There are a few main plot type for this:

Let’s go through examples of each!

Matrixs plot allow you to plot data as color-encoded matrices and can also be used to indicate cluster within the data (later in the machine learning section we will learn how to formally cluster data).

SOME BASIC EXAMPLE
1. EXAMPLE:

# Seaborn for plotting and styling
import seaborn as sb
df = sb.load_dataset('tips')
print df.head()

   totalbill  tip   sexs    smoker day  time   size
0    16.99    1.01   Female  Yes    Sun  Dinner  2
1    10.34    1.66   Male    No    Sun  Dinner  3
2    21.01    3.50   Male    No    Sun  Dinner  3
3    23.68    3.31   Male    No    Sun  Dinner  2
4    24.59    3.61   Female  Yes   Sun  Dinner  4

2. EXAMPLE:

import seaborn as sb
print sb.get_dataset_names()

[u'anscombe', u'attention', u'brain_networks', u'car_crashes', u'dots', 
u'exercise', u'flights', u'fmri', u'gammas', u'iris', u'planets', u'tips', 
u'titanic']

OPEN DRIVE LINK FROM BELOW LINK:

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