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

test = pd.read_csv('/kaggle/input/playground-series-s3e8/test.csv')
train = pd.read_csv('/kaggle/input/playground-series-s3e8/train.csv')
sub = pd.read_csv('/kaggle/input/playground-series-s3e8/sample_submission.csv')

train.isnull().sum()

print('************************************************\n',train['cut'].value_counts(), '\n************************************************')
plt.figure(figsize=(6,5))

ax = sns.countplot(data=train, x='cut')
ax.bar_label(ax.containers[0])
plt.show()

print('************************************************\n',train['color'].value_counts(), '\n************************************************')
plt.figure(figsize=(6,5))

ax = sns.countplot(data=train, x='color')
ax.bar_label(ax.containers[0])
plt.show()

print('************************************************\n', train['clarity'].value_counts(), '\n************************************************')
plt.figure(figsize=(6, 5))
ax = sns.countplot(data=train, x='clarity')
ax.bar_label(ax.containers[0])
plt.show()