python - 从 Dataframe 中新列的索引中提取数据

Question

如何根据不同列的索引值提取数据？

到目前为止，我能够根据同一列(5 block )中的索引号提取数据。

Dataframe 如下所示:

3017     39517.3886
3018     39517.4211
3019     39517.4683
3020     39517.5005
3021     39517.5486
5652     39628.1622
5653     39628.2104
5654     39628.2424
5655     39628.2897
5656     39628.3229
5677     39629.2020
5678     39629.2342
5679     39629.2825
5680     39629.3304
5681     39629.3628

col 中提取的数据在索引值周围 +/- 2 行

我想要一些看起来更像这样的东西:

  3017-3021   5652-5656   5677-5681
1 39517.3886  39628.1622  39629.2020
2 39517.4211  39628.2104  39629.2342
3 39517.4683  39628.2424  39629.2825
4 39517.5005  39628.2897  39629.3304
5 39517.5486  39628.3229  39629.3628

依此类推，具体取决于我要提取的数据数量。

我用来根据索引提取数据的代码是:

## find index based on the first 0 of a 000 - 111 list
a = stim_epoc[1:]
ss = [(num+1) for num,i in enumerate(zip(stim_epoc,a)) if i == (0,1)]

## extract data from a df (GCamp_ps) based on the previous index 'ss'
fin = [i for x in ss for i in range(x-2, x + 2 + 1) if i in range(len(GCaMP_ps))]
df = time_fip.loc[np.unique(fin)]
print(df)

Answer 1

形成 5 行连续的组(因为你从中心拉出 +/-2 行)。然后创建列和索引标签以及 pivot

df = df.reset_index()
s = df.index//5   # If always 5 consecutive values. I.e. +/-2 rows from a center.    

df['col'] = df.groupby(s)['index'].transform(lambda x: '-'.join(map(str, x.agg(['min', 'max']))))
df['idx'] = df.groupby(s).cumcount()

df.pivot(index='idx', columns='col', values=0)  # Assuming column named `0`

输出:

col   3017-3021   5652-5656   5677-5681
idx                                    
0    39517.3886  39628.1622  39629.2020
1    39517.4211  39628.2104  39629.2342
2    39517.4683  39628.2424  39629.2825
3    39517.5005  39628.2897  39629.3304
4    39517.5486  39628.3229  39629.3628