How to turn every three column into rows?-CodePudding

I have a dataframe:

col1  col2  col3  col4 col5 col6  col7 col8 col9
a1     b1    c1    d1    e1  f1    g1   h1  i1
a2     b2    c2    d2    e2  f2    g2   h2  i2

I want to to turn every three column into rows:

col1  col2  col3    
a1     b1    c1    
a2     b2    c2  
d1     e1    f1 
d2     e2    f2 
g1     h1    i1
g2     h2    i2

how to do that?

CodePudding user response：

You can simply reshape the .values of the dataframe and use the reshaped array to create a new dataframe:

df_reshaped = pd.DataFrame(df.values.reshape((-1, 3)), columns=df.columns[:3])

The shape argument to reshape has -1 in as the first dimension because we want as many rows as can be made from the original data with three columns.

which gives:

  col1 col2 col3
0   a1   b1   c1
1   d1   e1   f1
2   g1   h1   i1
3   a2   b2   c2
4   d2   e2   f2
5   g2   h2   i2

CodePudding user response：

Use df.values.reshape to change the shape of the data frame and then assign the column names.

CODE

import pandas as pd

df = pd.DataFrame({"col1": ["a1", "a2"], "col2": ["b1", "b2"], "col3": ["c1", "c2"],
                   "col4": ["d1", "d2"], "col5": ["e1", "e2"], "col6": ["f1", "f2"],
                   "col7": ["g1", "g2"], "col8": ["h1", "h2"], "col9": ["i1", "i2"]})


newdf = pd.DataFrame(df.values.reshape(-1, 3), columns=['col1', 'col2', 'col3'])
print(newdf)

OUTPUT

   col1 col2 col3
0   a1   b1   c1
1   d1   e1   f1
2   g1   h1   i1
3   a2   b2   c2
4   d2   e2   f2
5   g2   h2   i2