text_plain_output_1.png image_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import seaborn as sns

corruption = pd.read_csv('../input/crime-in-india-2019/Corruption 2019.csv')

corruption.columns

corruption.drop(['Category', 'Unnamed: 11', 'Unnamed: 12', 'Unnamed: 13', 'Unnamed: 14'], axis=1, inplace=True)

totalcase = corruption.sort_values('Total cases', ascending=False)

plt.tick_params(axis='x', which='major', labelsize=15, rotation=90)
plt.tick_params(axis='y', which='major', labelsize=15)

chargesheet = corruption.sort_values('Cases Charge-sheeted', ascending=False)

plt.xticks(rotation=90)

pending = corruption.sort_values('Cases Pending Investigation at End of the Year', ascending=False)

plt.xticks(rotation=90)

previous = corruption.sort_values('Cases Pending Investigation from Previous Year', ascending=False)

plt.figure(figsize=(20, 12))
plt.xticks(rotation=90)
sns.pointplot(x='State/UT ', y='Cases Pending Investigation from Previous Year', data=previous, color='red')