函数接口
DataFrame.select_dtypes(include=None, exclude=None)
Return a subset of the DataFrame's columns based on the column dtypes.
-
Parameters:include, exclude:scalar or list-like
A selection of dtypes or strings to be included/excluded. At least one of these parameters must be supplied. -
Returns:DataFrame
The subset of the frame including the dtypes in include and excluding the dtypes in exclude. -
Raises:ValueError
- If both of include and exclude are empty
- If include and exclude have overlapping elements
- If any kind of string dtype is passed in.
注意
-
To select all numeric types, use np.number or 'number'
-
To select strings you must use the object dtype, but note that this will return all object dtype columns
-
See the numpy dtype hierarchy
-
To select datetimes, use np.datetime64, 'datetime' or 'datetime64'
-
To select timedeltas, use np.timedelta64, 'timedelta' or 'timedelta64'
-
To select Pandas categorical dtypes, use 'category'
-
To select Pandas datetimetz dtypes, use 'datetimetz' (new in 0.20.0) or 'datetime64[ns, tz]'
例子
df = pd.DataFrame({'a': [1, 2] * 3,
'b': [True, False] * 3,
'c': [1.0, 2.0] * 3})
df
a b c
0 1 True 1.0
1 2 False 2.0
2 1 True 1.0
3 2 False 2.0
4 1 True 1.0
5 2 False 2.0
df.select_dtypes(include='bool')
b
0 True
1 False
2 True
3 False
4 True
5 False
df.select_dtypes(include=['float64'])
c
0 1.0
1 2.0
2 1.0
3 2.0
4 1.0
5 2.0
df.select_dtypes(exclude=['int64'])
b c
0 True 1.0
1 False 2.0
2 True 1.0
3 False 2.0
4 True 1.0
5 False 2.0