在 Pandas 中将元组中的字符串拆分为列 [英] Split strings in tuples into columns, in Pandas

问题描述

我有以下 DataFrame，其中 Track ID 是行索引.如何将 stats 列中的字符串拆分为 5 列数字?

I have the following DataFrame, where Track ID is the row index. How can I split the string in the stats column into 5 columns of numbers?

Track ID    stats
14.0    (-0.00924175824176, 0.41, -0.742016492568, 0.0036830094242, 0.00251748449963)
28.0    (0.0411538461538, 0.318230769231, 0.758717081514, 0.00264000622468, 0.0106535783677)
42.0    (-0.0144351648352, 0.168438461538, -0.80870348637, 0.000816872566404, 0.00316572586742)
56.0    (0.0343461538462, 0.288730769231, 0.950844962874, 6.1608706775e-07, 0.00337262030771)
70.0    (0.00905164835165, 0.151030769231, 0.670257006716, 0.0121790506745, 0.00302182567957)
84.0    (-0.0047967032967, 0.171615384615, -0.552879463981, 0.0500316517755, 0.00217970256969)

推荐答案

对于另一种情况，假设它是看起来像元组的字符串:

And for the other case, assuming it are strings that look like tuples:

In [74]: df['stats'].str[1:-1].str.split(',', expand=True).astype(float)
Out[74]:
          0         1         2         3         4
0 -0.009242  0.410000 -0.742016  0.003683  0.002517
1  0.041154  0.318231  0.758717  0.002640  0.010654
2 -0.014435  0.168438 -0.808703  0.000817  0.003166
3  0.034346  0.288731  0.950845  0.000001  0.003373
4  0.009052  0.151031  0.670257  0.012179  0.003022
5 -0.004797  0.171615 -0.552879  0.050032  0.002180

(注意:对于旧版本的 Pandas(<0.16.1)，您需要使用 return_type='frame' 而不是 expand 关键字)

(note: for older versions of pandas (< 0.16.1), you need to use return_type='frame' instead of the expand keyword)

顺便说一句，如果它是元组而不是字符串，您可以简单地执行以下操作:

By the way, if it are tuples and not strings, you can simply do the following:

pd.DataFrame(df['stats'].tolist(), index=df.index)

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