在pandas DataFrame中将非空单元格移到左侧 [英] Move non-empty cells to the left in pandas DataFrame

问题描述

假设我有以下形式的数据

Suppose I have data of the form

Name    h1    h2    h3    h4
A       1     nan   2     3
B       nan   nan   1     3
C       1     3     2     nan

我想将所有非nan单元格移到左侧(或在新列中收集所有非nan数据)，同时保留从左到右的顺序，得到

I want to move all non-nan cells to the left (or collect all non-nan data in new columns) while preserving the order from left to right, getting

Name    h1    h2    h3    h4
A       1     2     3     nan
B       1     3     nan   nan
C       1     3     2     nan

我当然可以逐行这样做.但我希望知道是否还有其他方法可以改善性能.

I can of course do so row by row. But I hope to know if there are other ways with better performance.

推荐答案

这就是我所做的:

我将您的数据框拆开成更长的格式，然后按名称列分组.在每个组中，我放下NaN，然后​​将其重新索引为以h4为底的完整h1，从而在右侧重新创建您的NaN.

I unstacked your dataframe into a longer format, then grouped by the name column. Within each group, I drop the NaNs, but then reindex to the full h1 thought h4 set, thus re-creating your NaNs to the right.

from io import StringIO
import pandas

def defragment(x):
    values = x.dropna().values
    return pandas.Series(values, index=df.columns[:len(values)])

datastring = StringIO("""\
Name    h1    h2    h3    h4
A       1     nan   2     3
B       nan   nan   1     3
C       1     3     2     nan""")

df = pandas.read_table(datastring, sep='\s+').set_index('Name')
long_index = pandas.MultiIndex.from_product([df.index, df.columns])

print(
    df.stack()
      .groupby(level='Name')
      .apply(defragment)
      .reindex(long_index)  
      .unstack()  
)

所以我得到了

   h1  h2  h3  h4
A   1   2   3 NaN
B   1   3 NaN NaN
C   1   3   2 NaN

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