Seaborn is python data visualization library built on the top of matplotlib.

1. Seaborn
Sourabh Sahu

2. Introduction
• Data Visualization
• Built on the top of matplotlib

3. Architecture

4. Installation
•For Installation
•Pip install seaborn
•!pip install seaborn --upgrade
For Testing
Import seaborn as sns
Sns.__version__

5. Demo
• To disable warning
• Import warnings
• Warnings.filterwarnings(‘Ignore’)

6. Imports
• import pandas as pd
• import seaborn as sns
• import numpy as np
• import matplotlib.pyplot as plt

7. Read Data
• data = pd.read_csv('data.csv', encoding='ISO-8859–
1')
• Data.head(100)

8. • data.columns
• Index(['stn_code', 'sampling_date', 'state', 'location',
'agency', 'type', 'so2', 'no2', 'rspm', 'spm',
'location_monitoring_station', 'pm2_5', 'date'],
dtype='object')

9. Data Cleaning
• data['no2']=data['no2'].fillna(0)

10. Distribution Plot
• dst=sns.distplot(data['no2'])
• dst.set_title('Pollution statistics of NO2')
• dst.set_xlabel('Air Quality Index of No2')
• dst.set_ylabel('Density of AQI')
• plt.show()

11. Display

12. Vertical Distribution
• dst=sns.distplot(data['no2'],color='green',vertical=True)
• dst.set_title('Pollution statistics of NO2')
• dst.set_xlabel('Air Quality Index of No2')
• dst.set_ylabel('Density of AQI')
• plt.show()

13. More Variant
• dst=sns.distplot(data['no2'],color='green',vertical=True,kde_kws={"color":"b",
• "lw":2,
• "label":"KDE"
• },hist_kws={
• "histtype":"step" ,
• "linewidth":2,
• "alpha":0.7,
• "color":"r",
• "label":"HIST"
• })
• dst.set_title('Pollution statistics of NO2')
• dst.set_xlabel('Air Quality Index of No2')
• dst.set_ylabel('Density of AQI')
• plt.show()

14. • dst=sns.distplot(data['no2'],color='green',kde=False,bins=500)
• dst.set_title('Pollution statistics of NO2')
• dst.set_xlabel('Air Quality Index of No2')
• dst.set_ylabel('Frequency')
• plt.show()

15. Sub Plots & heatmap
• plt.subplots(figsize=(30,10))
• cordata=data.corr()
• sns.heatmap(cordata,vmax=0.8,square=T
rue,annot=True,fmt=".2f",cmap="YlGnBu
")

16. PairPlot
• sns.pairplot(data)
• plt.show()

17. • Sns.set() //sets default theme
• Style=‘darkgrid’ palette=‘deep’ font=‘sans=serif’

18. • Sns.displine() //removes lines