PANDAS 中每第 n 行转置一列中的数据

对于一个研究项目，我需要将网站上每个人的信息处理成一个 Excel 文件。我已将网站上所需的所有内容复制并粘贴到 Excel 文件中的单个列中，然后使用 PANDAS 加载该文件。然而，我需要水平地呈现每个人的信息，而不是像现在这样垂直地呈现。 例如，这就是我现在拥有的。我只有一列无组织的数据。

df= pd.read_csv("ior work.csv", encoding = "ISO-8859-1")

Data:

0 Andrew
1 School of Music
2 Music: Sound of the wind
3 Dr. Seuss
4 Dr.Sass
5 Michelle
6 School of Theatrics
7 Music: Voice
8 Dr. A
9 Dr. B

我想每5行转置一次，将数据组织成这种组织格式；下面的标签是列的标签。

Name School Music Mentor1 Mentor2

做到这一点最有效的方法是什么？

如果没有丢失数据，您可以使用numpy.reshape http://docs.scipy.org/doc/numpy/reference/generated/numpy.reshape.html:

print (np.reshape(df.values,(2,5)))
[['Andrew' 'School of Music' 'Music: Sound of the wind' 'Dr. Seuss'
  'Dr.Sass']
 ['Michelle' 'School of Theatrics' 'Music: Voice' 'Dr. A' 'Dr. B']]

print (pd.DataFrame(np.reshape(df.values,(2,5)), 
                    columns=['Name','School','Music','Mentor1','Mentor2']))
       Name               School                     Music    Mentor1  Mentor2
0    Andrew      School of Music  Music: Sound of the wind  Dr. Seuss  Dr.Sass
1  Michelle  School of Theatrics              Music: Voice      Dr. A    Dr. B

生成更通用的解决方案length of new array by shape http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.shape.html除以列数：

print (pd.DataFrame(np.reshape(df.values,(df.shape[0] / 5,5)), 
                    columns=['Name','School','Music','Mentor1','Mentor2']))
       Name               School                     Music    Mentor1  Mentor2
0    Andrew      School of Music  Music: Sound of the wind  Dr. Seuss  Dr.Sass
1  Michelle  School of Theatrics              Music: Voice      Dr. A    Dr. B

谢谢皮尔方 https://stackoverflow.com/questions/39761366/transpose-the-data-in-a-column-every-nth-rows-in-pandas/39762293?noredirect=1#comment66820514_39762293另一个解决方案：

print (pd.DataFrame(df.values.reshape(-1, 5), 
                    columns=['Name','School','Music','Mentor1','Mentor2']))