Create pandas dataframe with each element a tuple created from other dataframes

Question

i need to create a dataframe containing tuples from a series of dataframes arrays. What I need is the following:

I have dataframes a and b:

a = pd.DataFrame(np.array([[1, 2],[3, 4]]), columns=['one', 'two'])
b = pd.DataFrame(np.array([[5, 6],[7, 8]]), columns=['one', 'two'])

a:
   one  two
0    1    2
1    3    4

b: 
   one  two
0    5    6
1    7    8

I want to create a dataframe a_b in which each element is a tuple formed from the corresponding elements in a and b, i.e.

a_b = pd.DataFrame([[(1, 5), (2, 6)],[(3, 7), (4, 8)]], columns=['one', 'two'])

a_b: 
      one     two
0  (1, 5)  (2, 6)
1  (3, 7)  (4, 8)

Ideally i would like to do this with an arbitrary number of dataframes. I was hoping there was a more elegant way than using a for cycle I'm using python 3

MaxU - stand with Ukraine · Accepted Answer · 2017-01-28 11:02:20Z

4

you can use numpy.rec.fromarrays((a.values, b.values)).tolist():

In [34]: pd.DataFrame(np.rec.fromarrays((a.values, b.values)).tolist(), 
                      columns=a.columns,
                      index=a.index)
Out[34]:
      one     two
0  (1, 5)  (2, 6)
1  (3, 7)  (4, 8)

merging three DF's:

In [36]: pd.DataFrame(np.rec.fromarrays((a.values, b.values, a.values)).tolist(),
                      columns=a.columns,
                      index=a.index)
Out[36]:
         one        two
0  (1, 5, 1)  (2, 6, 2)
1  (3, 7, 3)  (4, 8, 4)

UPDATE:

suppose you don't know in advance the number of dataframes, how would you do?

In [60]: dfs = [a,b,a]

In [62]: tuple_of_dfs = (x.values for x in dfs)

In [63]: pd.DataFrame(np.rec.fromarrays(tuple_of_dfs).tolist(), columns=a.columns, index=a.index)
Out[63]:
         one        two
0  (1, 5, 1)  (2, 6, 2)
1  (3, 7, 3)  (4, 8, 4)

edited Jan 28, 2017 at 11:02

answered Jan 28, 2017 at 10:43

MaxU - stand with Ukraine

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2 Comments

gionni Over a year ago

Thanks, this works great, but suppose you don't know in advance the number of dataframes, how would you do?

MaxU - stand with Ukraine Over a year ago

@gionni, please see UPDATE section

Zero · Accepted Answer · 2017-01-28 10:46:31Z

2

You could use zip over columns of a, b

In [31]: pd.DataFrame({x: zip(a[x], b[x]) for x in a.columns})
Out[31]:
      one     two
0  (1, 5)  (2, 6)
1  (3, 7)  (4, 8)

answered Jan 28, 2017 at 10:46

Zero

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