将二维数组变成两列数据框 pandas [英] turning a two dimensional array into a two column dataframe pandas

问题描述

如果我具有以下内容，如何使pd.DataFrame()将此数组转换为具有两列的数据帧.最有效的方法是什么?我当前的方法涉及将每个副本创建为一系列，并从中创建数据框.

if I have the following, how do I make pd.DataFrame() turn this array into a dataframe with two columns. What's the most efficient way? My current approach involves creating copies out of each into a series and making dataframes out of them.

从此:

([[u'294 (24%) L', u'294 (26%) R'],
  [u'981 (71%) L', u'981 (82%) R'],])

到

x    y
294  294
981  981

而不是

x
[u'294 (24%) L', u'294 (26%) R']

我目前的做法.寻找更有效的东西

my current approach. Looking for something more efficient

numL = pd.Series(numlist).map(lambda x: x[0])
    numR = pd.Series(numlist).map(lambda x: x[1])

    nL = pd.DataFrame(numL, columns=['left_num'])
    nR = pd.DataFrame(numR, columns=['right_num'])

    nLR = nL.join(nR)

    nLR

更新**

我注意到我的错误仅归结于当您pd.DataFrame()一个列表而不是一个序列时.当您从列表中创建数据框时，它会将项目合并到同一列中.列表不是这样.那以最有效的方式解决了我的问题.

I noticed that my error simply comes down to when you pd.DataFrame() a list versus a series. WHen you create a dataframe out of a list, it merges the items into the same column. Not so with a list. That solved my problem in the most efficient way.

推荐答案

In [172]: data = [[u'294 (24%) L', u'294 (26%) R'],  [u'981 (71%) L', u'981 (82%) R'],]

In [173]: clean_data = [[int(item.split()[0]) for item in row] for row in data]

In [174]: clean_data
Out[174]: [[294, 294], [981, 981]]

In [175]: pd.DataFrame(clean_data, columns=list('xy'))
Out[175]: 
     x    y
0  294  294
1  981  981

[2 rows x 2 columns]

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