pandas修改DataFrame中的列名&调整列的顺序

以你之姓@ 2023-06-16 04:52 42阅读 0赞

### 修改列名： ###

直接调用接口：

df.rename()

看一下接口中的定义：

def rename(self, *args, **kwargs):
            """
            Alter axes labels.
    
            Function / dict values must be unique (1-to-1). Labels not contained in
            a dict / Series will be left as-is. Extra labels listed don't throw an
            error.
    
            See the :ref:`user guide <basics.rename>` for more.
    
            Parameters
            ----------
            mapper, index, columns : dict-like or function, optional
                dict-like or functions transformations to apply to
                that axis' values. Use either ``mapper`` and ``axis`` to
                specify the axis to target with ``mapper``, or ``index`` and
                ``columns``.
            axis : int or str, optional
                Axis to target with ``mapper``. Can be either the axis name
                ('index', 'columns') or number (0, 1). The default is 'index'.
            copy : boolean, default True
                Also copy underlying data
            inplace : boolean, default False
                Whether to return a new DataFrame. If True then value of copy is
                ignored.
            level : int or level name, default None
                In case of a MultiIndex, only rename labels in the specified
                level.
    
            Returns
            -------
            renamed : DataFrame
    
            See Also
            --------
            pandas.DataFrame.rename_axis
    
            Examples
            --------
    
            ``DataFrame.rename`` supports two calling conventions
    
            * ``(index=index_mapper, columns=columns_mapper, ...)``
            * ``(mapper, axis={'index', 'columns'}, ...)``
    
            We *highly* recommend using keyword arguments to clarify your
            intent.
    
            >>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
            >>> df.rename(index=str, columns={"A": "a", "B": "c"})
               a  c
            0  1  4
            1  2  5
            2  3  6
    
            >>> df.rename(index=str, columns={"A": "a", "C": "c"})
               a  B
            0  1  4
            1  2  5
            2  3  6
    
            Using axis-style parameters
    
            >>> df.rename(str.lower, axis='columns')
               a  b
            0  1  4
            1  2  5
            2  3  6
    
            >>> df.rename({1: 2, 2: 4}, axis='index')
               A  B
            0  1  4
            2  2  5
            4  3  6
            """
            axes = validate_axis_style_args(self, args, kwargs, 'mapper', 'rename')
            kwargs.update(axes)
            # Pop these, since the values are in `kwargs` under different names
            kwargs.pop('axis', None)
            kwargs.pop('mapper', None)
            return super(DataFrame, self).rename(**kwargs)

注意：

*  一个\*，输入可以是数组、元组，会把输入的数组或元组拆分成一个个元素。
 *  两个\*，输入必须是字典格式

示例：

>>>import pandas as pd
    >>>a = pd.DataFrame({'A':[1,2,3], 'B':[4,5,6], 'C':[7,8,9]})
    >>> a 
       A  B  C
    0  1  4  7
    1  2  5  8
    2  3  6  9
    
    
    #将列名A替换为列名a，B改为b，C改为c
    >>>a.rename(columns={'A':'a', 'B':'b', 'C':'c'}, inplace = True)
    >>>a
       a  b  c
    0  1  4  7
    1  2  5  8
    2  3  6  9

### 调整列的顺序： ###

如：

>>> import pandas
    >>> dict_a = {'user_id':['webbang','webbang','webbang'],'book_id':['3713327','4074636','26873486'],'rating':['4','4','4'],
    'mark_date':['2017-03-07','2017-03-07','2017-03-07']}
    
    >>> df = pandas.DataFrame(dict_a) # 从字典创建DataFrame
    >>> df # 创建好的df列名默认按首字母顺序排序，和字典中的先后顺序并不一样，字典中'user_id','book_id','rating','mark_date'
    
     book_id mark_date rating user_id
    0 3713327 2017-03-07  4 webbang
    1 4074636 2017-03-07  4 webbang
    2 26873486 2017-03-07  4 webbang

直接修改列名：

>>> df = df[['user_id','book_id','rating','mark_date']] # 调整列顺序为'user_id','book_id','rating','mark_date'
    >>> df
    
     user_id book_id rating mark_date
    0 webbang 3713327  4 2017-03-07
    1 webbang 4074636  4 2017-03-07
    2 webbang 26873486  4 2017-03-07

就可以了。