Pandas add values from DataFrame multiple times

Question

The following is easy on SQL but I cannot figure out how to do it on Pandas.

My inputs are:

import pandas as p    
symb = p.DataFrame(['a', 'b', 'c'], columns=['symb'])
fld = p.DataFrame(['field1', 'field2', 'field3'], columns=['fld'])

I want to be able to get the following DataFrame as output:

symb  fld
a     field1
a     field2
a     field3
b     field1
b     field2
b     field3
c     field1
c     field2
c     field3

Any idea on how to get to this result?

Thanks!

jezrael · Accepted Answer · 2016-05-11 17:21:05Z

3

First create new columns with same values in both DataFrames. Then use merge by them and then drop helper column:

symb['one'] = 1
fld['one'] = 1
print pd.merge(symb, fld, on='one').drop('one', axis=1)
  symb     fld
0    a  field1
1    a  field2
2    a  field3
3    b  field1
4    b  field2
5    b  field3
6    c  field1
7    c  field2
8    c  field3

answered May 11, 2016 at 17:21

jezrael

868k103 gold badges1.4k silver badges1.3k bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

Yona Over a year ago

Just one comment ... do you guys know how this is called ? I could not even google how to do this as I was not aware how this operation is defined (join, merge and other will link to pages showing the general instructions). This could help future users to find this page.

jezrael Over a year ago

I think it is called Cartesian product or cross join

piRSquared · Accepted Answer · 2016-05-11 17:31:53Z

1

Solution

pd.DataFrame(index=symb.symb, columns=fld.fld).fillna(0).stack().reset_index()[['symb', 'fld']]

answered May 11, 2016 at 17:31

piRSquared

296k68 gold badges509 silver badges654 bronze badges

1 Comment

Ajean Over a year ago

While this code may answer the question, providing additional context regarding why and/or how this code answers the question improves its long-term value.

Collectives™ on Stack Overflow

Pandas add values from DataFrame multiple times

2 Answers 2

2 Comments

Solution

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

2 Comments

Solution

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related