Pandas DataFrame drop 删除行列

import pandas as pd
import numpy as np

my_df = pd.DataFrame(data=np.arange(50).reshape(10,5),  # 10*5的矩阵
             index=list("abcdefghij"),  # 行索引
             columns=list("ABCDE"))  # 列索引
print("my_df\n",my_df)

# axis=0 删除行
print("my_df.drop(['a'],axis=0\n",my_df.drop(['a'],axis=0))
# axis=1 删除列
print("my_df.drop(['B','E'],axis=1)\n",my_df.drop(['B','E'],axis=1))

help(my_df.drop)

Help on method drop in module pandas.core.generic:

drop(labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise') method of pandas.core.frame.DataFrame instance
    Return new object with labels in requested axis removed.
    
    Parameters
    ----------
    labels : single label or list-like
        Index or column labels to drop.
    axis : int or axis name
        Whether to drop labels from the index (0 / 'index') or
        columns (1 / 'columns').
    index, columns : single label or list-like
        Alternative to specifying `axis` (``labels, axis=1`` is
        equivalent to ``columns=labels``).
    
        .. versionadded:: 0.21.0
    level : int or level name, default None
        For MultiIndex
    inplace : bool, default False
        If True, do operation inplace and return None.
    errors : {'ignore', 'raise'}, default 'raise'
        If 'ignore', suppress error and existing labels are dropped.
    
    Returns
    -------
    dropped : type of caller
    
    Examples
    --------
    >>> df = pd.DataFrame(np.arange(12).reshape(3,4),
                          columns=['A', 'B', 'C', 'D'])
    >>> df
       A  B   C   D
    0  0  1   2   3
    1  4  5   6   7
    2  8  9  10  11
    
    Drop columns
    
    >>> df.drop(['B', 'C'], axis=1)
       A   D
    0  0   3
    1  4   7
    2  8  11
    
    >>> df.drop(columns=['B', 'C'])
       A   D
    0  0   3
    1  4   7
    2  8  11
    
    Drop a row by index
    
    >>> df.drop([0, 1])
       A  B   C   D
    2  8  9  10  11
    
    Notes
    -----
    Specifying both `labels` and `index` or `columns` will raise a
    ValueError.