Pandas DataFrame | select_dtypes method
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Pandas DataFrame.select_dtypes(~) returns a subset of columns that match (or not match) the specified type.
Parameters
1. include | scalar or array-like | optional
The data-types to include.
2. exclude | scalar or array-like | optional
The data-types to exclude.
At least one of two parameters must be provided.
Here are some of the data-types you can specify:
Type | Description |
|---|---|
| Matches all numeric types like |
| Matches all floats |
| Matches all ints |
| Matches all objects such as strings, lists, dictionaries and so on |
| Matches all datetimes |
| Matches all timedeltas |
| Matches all categories |
| Matches all booleans |
Return value
A DataFrame holding a subset of columns that match (or not match) the specified type.
Examples
Consider the following DataFrame:
df = pd.DataFrame({"A":[4,5], "B":["M","L"], "C": [8,9]}, index=["a","b"])df
A B Ca 4 M 8b 5 L 9
To fetch all numeric columns:
df.select_dtypes(include="number")
A Ca 4 8b 5 9
To fetch all columns except numeric ones:
df.select_dtypes(exclude="number")
Ba Mb L
