Pythonic方式过滤列然后创建新列

Question

我有一个.xlsx文件,我打开这个代码:

import pandas as pd

df = pd.read_excel(open('file.xlsx','rb'))
df['Description'].head

我有以下结果,看起来很不错.

ID     | Description
:----- | :-----------------------------
0      | Some Description with no hash
1      | Text with #one hash
2      | Text with #two #hashes

现在我想创建一个新列,只保留以#开头的单词,如下所示:

ID     | Description                      |  Only_Hash
:----- | :-----------------------------   |  :-----------------
0      | Some Description with no hash    |   Nan
1      | Text with #one hash              |   #one
2      | Text with #two #hashes           |   #two #hashes

我能用#计算/分隔线:

descriptionWithHash = df['Description'].str.contains('#').sum()

但现在我想像上面描述的那样创建列.最简单的方法是什么？

问候!

PS:它应该在问题中显示表格格式,但我无法弄清楚它为什么显示错误!

Answer 1

你可以用str.findall与str.join:

df['new'] =  df['Description'].str.findall('(\#\w+)').str.join(' ')
print(df)
   ID                    Description           new
0   0  Some Description with no hash              
1   1            Text with #one hash          #one
2   2         Text with #two #hashes  #two #hashes

对于NaNs:

df['new'] = df['Description'].str.findall('(\#\w+)').str.join(' ').replace('',np.nan)
print(df)
   ID                    Description           new
0   0  Some Description with no hash           NaN
1   1            Text with #one hash          #one
2   2         Text with #two #hashes  #two #hashes

Answer 2

In [126]: df.join(df.Description
     ...:           .str.extractall(r'(\#\w+)')
     ...:           .unstack(-1)
     ...:           .T.apply(lambda x: x.str.cat(sep=' ')).T
     ...:           .to_frame(name='Hash'))
Out[126]:
   ID                    Description          Hash
0   0  Some Description with no hash           NaN
1   1            Text with #one hash          #one
2   2         Text with #two #hashes  #two #hashes