在 PANDAS 中每第 n 行转置一列中的数据 [英] Transpose the data in a column every nth rows in PANDAS

问题描述

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.但是，我需要水平呈现每个人的信息，而不是像现在这样垂直呈现.例如，这就是我现在所拥有的.我只有一列无组织的数据.

For a research project, I need to process every individual's information from the website into an excel file. I have copied and pasted everything I need from the website onto a single column in an excel file, and I loaded that file using PANDAS. However, I need to present each individual's information horizontally instead of vertically like it is now. For example, this is what I have right now. I only have one column of unorganized data.

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

数据:

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.

I want transpose every 5 lines to organize the data into this organizational format; the labels below are labels of the columns.

Name School Music Mentor1 Mentor2

最有效的方法是什么?

推荐答案

如果没有数据缺失，可以使用 numpy.reshape:

If no data are missing, you can use numpy.reshape:

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

通过shape 除以列数:

More general solution with generating length of new array by shape divide by number of columns:

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piRSquared 另一个解决方案:

Thank you piRSquared for another solution:

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

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