text_plain_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

df = pd.read_csv('../input/covid19s-impact-on-airport-traffic/covid_impact_on_airport_traffic.csv')

df.isnull().sum()

df1 = df.groupby('Country')['PercentOfBaseline'].mean().sort_values(ascending=False).reset_index()
sns.set(font_scale=1.2)

df1 = df.groupby('City')['PercentOfBaseline'].mean().sort_values(ascending=False).reset_index()
sns.set(font_scale=1.2)

df1 = df.groupby('State')['PercentOfBaseline'].mean().sort_values(ascending=False).reset_index()
sns.set(font_scale=1.2)

df1 = df.groupby('AirportName')['PercentOfBaseline'].mean().sort_values(ascending=False).reset_index()
sns.set(font_scale=1.2)
plt.figure(figsize=[10, 10])
sns.barplot(data=df1, x='PercentOfBaseline', y='AirportName', palette='crest')
plt.xlabel('Percent of baseline')
plt.ylabel('Airport name')