validating columns in pandas on the basis of dtypes

1import pandas as pd
2import pandera as pa
3
4df = pd.DataFrame({
5    "column1": [1, 2, 3],
6    "column2": ["a", "b", "c"],
7})
8
9column1_schema = pa.Column(pa.Int, name="column1")
10column2_schema = pa.Column(pa.String, name="column2")
11
12# pass the dataframe as an argument to the Column object callable
13df = column1_schema(df)
14validated_df = column2_schema(df)
15
16# or explicitly use the validate method
17df = column1_schema.validate(df)
18validated_df = column2_schema.validate(df)
19
20# use the DataFrame.pipe method to validate two columns
21validated_df = df.pipe(column1_schema).pipe(column2_schema)
22