In Pandas, there is an integer type column, but in one row the value is missing (NULL). What data type will this column have?

In Pandas, if a column was originally of type int, but one of the rows has a missing value (NULL), Pandas automatically converts the column's type to float64. This is because the standard int type in Pandas does not support NaN values, whereas float64 does.

Example:

import pandas as pd
import numpy as np

df = pd.DataFrame({'A': [1, 2, np.nan]})
print(df.dtypes)

The output will be:

A    float64
dtype: object

If you want to keep an integer type that supports missing values, you can use the Int64 type (with a capital I), which supports nullable integers:

df = pd.DataFrame({'A': pd.Series([1, 2, None], dtype='Int64')})
print(df.dtypes)

Output:

A    Int64
dtype: object