如何最好地将包含列表或元组的Pandas列提取到多列中 [英] How best to extract a Pandas column containing lists or tuples into multiple columns

问题描述

我不小心关闭了这个问题，并提供了指向错误副本的链接.这是正确的方法: Pandas将列表的列分为多列.

I accidentally closed this question with a link to the wrong duplicate. Here is the correct one: Pandas split column of lists into multiple columns.

假设我有一个数据框，其中的一列是一个列表(长度相同且已知)或元组，例如:

Suppose I have a dataframe of which one column is a list (of a known and identical length) or tuple, for example:

df1 = pd.DataFrame(
 {'vals': [['a', 'b', 'c', 'd'],['e','f','g','h']]}
)

即:

    vals
0   [a, b, c, d]
1   [e, f, g, h]

我想将"vals"中的值添加到单独的命名列中.我可以通过遍历行来笨拙地做到这一点:

I want to extra the values in "vals" into separate named columns. I can do this clumsily by iterating through the rows:

for i in range(df1.shape[0]):
   for j in range(0,4):
      df1.loc[i, 'vals_'+j] = df1.loc[i, 'vals'] [j]

所需结果:

    vals            vals_0  vals_1  vals_2  vals_3
0   [a, b, c, d]    a       b       c       d 
1   [e, f, g, h]    e       f       g       h

是否有更整洁(矢量化)的方式?我尝试使用[]，但出现错误.

Is there a neater (vectorised) way? I tried using [] but I get an error.

   for j in range (0,4)
       df1['vals_'+str(j)] = df1['vals'][j]

给予:

ValueError: Length of values does not match length of index

熊猫似乎正在尝试将[]运算符应用于系列/数据框而不是列内容.

It looks like Pandas is trying to apply the [] operator to the series/dataframe rather than the column content.

推荐答案

您可以将assign，apply与pd.Series一起使用:

You can use assign, apply, with pd.Series:

df1.assign(**df1.vals.apply(pd.Series).add_prefix('val_'))

获取更多数据的更快方法是将.values和tolist()与数据帧构造函数一起使用:

A faster method for more data is to use .values and tolist() with dataframe constructor:

df1.assign(**pd.DataFrame(df1.vals.values.tolist()).add_prefix('val_'))

输出:

           vals val_0 val_1 val_2 val_3
0  [a, b, c, d]     a     b     c     d
1  [e, f, g, h]     e     f     g     h

这篇关于如何最好地将包含列表或元组的Pandas列提取到多列中的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！