text_html_output_1.png
import pandas as pd

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

train = pd.read_csv('/kaggle/input/tabular-playground-series-mar-2022/train.csv')
test = pd.read_csv('/kaggle/input/tabular-playground-series-mar-2022/test.csv')
submission = pd.read_csv('/kaggle/input/tabular-playground-series-mar-2022/test.csv')

print(f'\x1b[92mNumber of rows in the table: {test.shape[0]}')
print(f'\x1b[94mNumber of columns in the table: {test.shape[1]}')
print(f'\x1b[91mNumber of observations in the table: {test.count().sum()}')
print(f'\x1b[91mNumber of missing values in the table: {sum(test.isnull().sum())}')
print(f'\x1b[91mNumber of duplicated records: {test.duplicated().sum()}')
print()
print(f'\x1b[95mData types')
print(f'\x1b[90m{test.dtypes}')
print()
print(f'\x1b[95mData type counts')
print(f'\x1b[90m{test.dtypes.value_counts()}')
print()
print(f'\x1b[95mUnique value in each column')
print(f'\x1b[90m{test.nunique()}')