Pandas DataFrame convert_dtypes() Method
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.
