text_plain_output_1.png
import matplotlib.pyplot as plt

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

import seaborn as sns

import seaborn as sns
import matplotlib.pyplot as plt
df = pd.read_csv('/kaggle/input/house-rent-prediction-dataset/House_Rent_Dataset.csv')

colors = ['#E557C4', '#57C4E5', '#293241']

def count(df, x, ax, main_color):
    ax.bar_label(ax.containers[0], color='black', fontsize='large')
    ax.tick_params(axis='y', which='both', left=False, right=False, labelleft=False)
    ax.tick_params(axis='x', which='both', bottom=False, top=False)
    sns.despine(ax=ax, left=True)

count_cols = ['Area Type', 'City', 'Furnishing Status', 'Tenant Preferred', 'Bathroom', 'Point of Contact', 'BHK']
fig, axs = plt.subplots(4, 2, figsize=(20, 22), sharey=True)
for i, col in enumerate(count_cols):
    r_i = i // 2
    c_i = i % 2
    count(df, col, axs[r_i][c_i], colors[0])
fig.delaxes(axs[3, 1])
plt.show()