How to turn every three column into rows?

user_17378883 0
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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?

dataframe python-3.x function python
2 Answers

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
user_8439530

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
user_190920530
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