For example i have a dataframe like this :
import pandas as pd
df = pd.DataFrame([[1, 2.], [3, 4.]], columns=['a', 'b'])
print df
a b
0 1 2.0
1 3 4.0
I want to get a dataframe as follows :
a b
0 [1,3] [2,4]
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1 Answer
One approach -
df_out = pd.DataFrame([df.values.T.astype(int).tolist()], columns=df.columns)
To retrieve back -
N = len(df_out.columns)
arr_back = np.concatenate(np.concatenate(df_out.values)).reshape(N,-1).T
df_back = pd.DataFrame(arr_back, columns=df_out.columns)
Sample run -
In [164]: df
Out[164]:
a b
0 1 2.0
1 3 4.0
2 5 6.0
In [165]: df_out
Out[165]:
a b
0 [1, 3, 5] [2, 4, 6]
In [166]: df_back
Out[166]:
a b
0 1 2
1 3 4
2 5 6
1 Comment
Ibrahima Khalil
if i want to back