text_plain_output_2.png application_vnd.jupyter.stderr_output_1.png image_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sns

df_district = pd.read_csv('../input/learnplatform-covid19-impact-on-digital-learning/districts_info.csv')

df_district.isnull().sum()

df_district.columns

df_district.shape

df_district.dtypes

df_district = df_district.drop_duplicates()

plt.xticks(rotation=60)

fig, ax = plt.subplots(figsize=(12, 6))
fig.suptitle('Locale Distribution', size=20)
explode = (0.04, 0.04, 0.04, 0.04)
labels = list(df_district.locale.value_counts().index)
sizes = df_district.locale.value_counts().values
ax.pie(sizes, explode=explode, startangle=60, labels=labels, shadow=True)
ax.add_artist(plt.Circle((0, 0), 0.4, fc='white'))
plt.show()