text_html_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sns

train_set = pd.read_csv('/kaggle/input/aviakompaniya/train_dataset.csv')
test_set = pd.read_csv('/kaggle/input/aviakompaniya/test_dataset.csv')
sample = pd.read_csv('/kaggle/input/aviakompaniya/sample_submission.csv')

df = train_set.dropna()

df_100 = df[df['Flight Distance'] > 100]

df_100.select_dtypes('object').columns

Gender = list(df_100.Gender) + list(df_100.Gender)
Customer_Type = list(df_100['Customer Type']) + list(df_100['Customer Type'])
Type_of_Travel = list(df_100['Type of Travel']) + list(df_100['Type of Travel'])
Classes = list(df_100['Class']) + list(df_100['Class'])

satisfaction_rate = df_100['satisfaction'].value_counts() / len(df_100) * 100

fig, axes = plt.subplots(1, 3, figsize=(15, 5))
sns.countplot(x='Gender', hue='satisfaction', palette='viridis', data=df_100, ax=axes[0])
axes[0].set_title('Qolgan va qaytgan mijozrlarning jinsi')
sns.countplot(x='Class', hue='satisfaction', palette='viridis', data=df_100, ax=axes[1])
axes[1].set_title('Qolgan va qaytgan mijozrlarning qaysi classda uchganligi')
sns.countplot(x='Type of Travel', hue='satisfaction', palette='viridis', data=df_100, ax=axes[2])
axes[1].set_title('Qolgan va qaytgan mijozrlarning parvoz turi')
plt.show()