text_plain_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sns

train = pd.read_csv('../input/30-days-of-ml/train.csv')
test = pd.read_csv('../input/30-days-of-ml/test.csv')
submission = pd.read_csv('../input/30-days-of-ml/sample_submission.csv')

(train.shape, test.shape, submission.shape)

train.drop('id', axis=1, inplace=True)
test.drop('id', axis=1, inplace=True)

train.nunique()

fig, axes = plt.subplots(5, 2, figsize=(15, 15), sharex=True)
axes = axes.flatten()
object_bol = train.dtypes == 'object'
for ax, catplot in zip(axes, train.dtypes[object_bol].index):
    sns.countplot(y=catplot, data=train, ax=ax)
plt.tight_layout()
plt.show()