我有以下DataFrame(df):

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.rand(10, 5))

我通过分配添加更多列:

df['mean'] = df.mean(1)

如何将列的意思移到前面,即将其设置为第一列,而其他列的顺序保持不变?


当前回答

DataFrame.sort_index(axis=1)非常干净。请在此处检查文档。然后凹入

其他回答

简单地说,

df = df[['mean'] + df.columns[:-1].tolist()]

DataFrame.sort_index(axis=1)非常干净。请在此处检查文档。然后凹入

我认为这个函数更简单。您只需在开始或结束处或同时指定列的子集:

def reorder_df_columns(df, start=None, end=None):
    """
        This function reorder columns of a DataFrame.
        It takes columns given in the list `start` and move them to the left.
        Its also takes columns in `end` and move them to the right.
    """
    if start is None:
        start = []
    if end is None:
        end = []
    assert isinstance(start, list) and isinstance(end, list)
    cols = list(df.columns)
    for c in start:
        if c not in cols:
            start.remove(c)
    for c in end:
        if c not in cols or c in start:
            end.remove(c)
    for c in start + end:
        cols.remove(c)
    cols = start + cols + end
    return df[cols]

我想到了和Dmitriy Work一样的答案,显然是最简单的:

df["mean"] = df.mean(1)
l =  list(np.arange(0,len(df.columns) -1 ))
l.insert(0,-1)
df.iloc[:,l]

您可以使用以下名称列表对数据帧列进行重新排序:

df=df.filter(list_of_col_name)