Creating a 3D pandas dataframe by using 2 data frames

Question

I try to obtain a 3D dataframe from 2 dataframes that have the same shape. If we take the below script as the example, I want to create a 3D dataframe that have 2 rows (a and b), 3 columns (A, B and C), and 2 items (df1 and df2). And also to be clear, I tried to explain my problem with a figure.

import pandas as pd
df1 = pd.DataFrame([[1, 2, 11], [3, 4, 12]], columns=['A', 'B', 'C'], index=['a', 'b'])
df2 = pd.DataFrame([[5, 6, 13], [7, 8, 14]], columns=['A', 'B', 'C'], index=['a', 'b'])

I saw related questions and tried some of them. I have tried to use pd.MultiIndex, but I obtained error as “ValueError: Length of levels and labels must be the same.”

Is there any way to obtain a 3D dataframe as described in below figure?

Thanks.

r-beginners · Accepted Answer · 2020-08-23 14:20:56Z

1

This library can be implemented to support this. I was not aware of this library's existence. This is the first time I installed it with this question and got the information from the official reference to create a response. Thank you for this opportunity.

import pandas as pd

df1 = pd.DataFrame([[1, 2, 11], [3, 4, 12]], columns=['A', 'B', 'C'], index=['a', 'b'])
df2 = pd.DataFrame([[5, 6, 13], [7, 8, 14]], columns=['A', 'B', 'C'], index=['a', 'b'])
ds1 = df1.to_xarray()

ds2 = df2.to_xarray()

import xarray as xr ds_all = xr.concat([ds1,ds2], dim='new_dim')

df_all = ds_all.to_dataframe()
df_all
        A   B   C
index   new_dim         
a   0   1   2   11
    1   5   6   13
b   0   3   4   12
    1   7   8   14

answered Aug 23, 2020 at 14:20

r-beginners

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Pubudu Sitinamaluwa · Accepted Answer · 2020-08-23 14:47:02Z

0

Simply, you can do it like this.

import pandas as pd

df = pd.DataFrame(columns=['col'])

df1 = pd.DataFrame([[1, 2, 11], [3, 4, 12]], columns=['A', 'B', 'C'], index=['a', 'b'])
df2 = pd.DataFrame([[5, 6, 13], [7, 8, 14]], columns=['A', 'B', 'C'], index=['a', 'b'])

df = df.append({'col': df1}, ignore_index=True)
df = df.append({'col': df2}, ignore_index=True)

print(df)

print(df.iloc[1])

answered Aug 23, 2020 at 14:47

Pubudu Sitinamaluwa

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