How to store a DataFrame inside a DataFrame

Question

I have a DataFrame with various text and numeric columns which I use like a database. Since a column can be of dtype object, I can also store more complex objects inside a single cell, like a numpy array.

How could I store another DataFrame inside a cell?

df1=pd.DataFrame([1,'a'])
df2=pd.DataFrame([2,'b'])

This assigment fails:

df1.loc[0,0] = df2

ValueError: Incompatible indexer with DataFrame

PS. It is not a duplicate question as suggested below since I do not want to concatenate the "sub"-DataFrames

What is the purpose of nesting a dataframe within one? This sounds like an XY Problem. Consider a dictionary or list of dataframes. — Parfait
– Parfait, Commented Jan 22, 2018 at 2:55

Allen Qin · Accepted Answer · 2018-01-22 00:31:19Z

6

You can use set_value:

df1.set_value(0,0,df2)

or:

df1.iat[0,0]=df2

Since .set_value has been deprecated since version 0.21.0.

answered Jan 22, 2018 at 0:31

Allen Qin

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1 Comment

adr Over a year ago

...or df1.at[0,0]=df2 for labels... Thanks!

BENY · Accepted Answer · 2018-01-21 22:49:30Z

1

Convert your df1 to a dict by using to_dict

df1.loc[0,0] = [df2.to_dict()]
df1
Out[862]:
                       0
0  [{0: {0: 2, 1: 'b'}}]
1                      a

If you need convert it back to dataframe , You can using dataframe constructor

pd.DataFrame(df1.loc[0,0][0])


Out[864]: 
   0
0  2
1  b

answered Jan 21, 2018 at 22:49

BENY

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