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Pandas DataFrame convert_dtypes() Method

❮ DataFrame Reference


Example

Convert the data types to better fit the content:

import pandas as pd

data = {
  "name": ["Sally", "Mary", pd.NA],
  "qualified": [True, False, pd.NA]
}

df = pd.DataFrame(data)

print("Original dtypes:")
print(df.dtypes)

newdf = df.convert_dtypes()

print("New dtypes:")
print(newdf.dtypes)
Try it Yourself »

Definition and Usage

The convert_dtypes() method returns a new DataFrame where each column has been changed to the best possible data type.


Syntax

dataframe.convert_dtypes(infer_objects, convert_string, convert_integer, convert_boolean, convert_floating)

Parameters

The parameters are keyword arguments.

Parameter Value Description
infer_objects  True|False Optional. Default True. Specifies whether to convert object dtypes to the best possible dtype or not.
convert_string  True|False Optional. Default True. Specifies whether to convert object dtypes to strings or not.
convert_integer  True|False Optional. Default True. Specifies whether to convert object dtypes to integers or not.
convert_boolean True|False Optional. Default True. Specifies whether to convert object dtypes to booleans or not.
convert_floating  True|False Optional. Default True. Specifies whether to convert object dtypes to floating types or not.

Return Value

a Pandas DataFrame with the converted result.


❮ DataFrame Reference