how to assign a dataframe as a excel table into a specific column of another dataframe?

Question

I have two dataframes df1 and df2. Here df2 is a 2D array table. I need to assign all 2D values of df2 in df1['size_chart'].

Here is my code

total_value_list = [['', 'ウエスト', '股下', '股上', 'ヒップ', '裾回り', 'パンツ丈'], ['XS', '60.5cm', '70.4cm', '24.7cm', '95cm', '35cm', '93.9cm'], ['S', '64.5cm', '71.9cm', '25.7cm', '99cm', '35.5cm', '96.4cm'], ['6XO (7XL)', '100.5cm', '85.4cm', '34.7cm', '135cm', '44.5cm', '118.9cm'], ['M', '68.5cm', '73.4cm', '26.7cm', '103cm', '36.5cm', '98.9cm'], ['L', '72.5cm', '74.9cm', '27.7cm', '107cm', '37.5cm', '101.4cm'], ['O (XL)', '76.5cm', '76.4cm', '28.7cm', '111cm', '38.5cm', '103.9cm'], ['XO (2XL)', '80.5cm', '77.9cm', '29.7cm', '115cm', '39.5cm', '106.4cm'], ['2XO (3XL)', '84.5cm', '79.4cm', '30.7cm', '119cm', '40.5cm', '108.9cm'], ['3XO (4XL)', '88.5cm', '80.9cm', '31.7cm', '123cm', '41.5cm', '111.4cm'], ['4XO (5XL)', '92.5cm', '82.4cm', '32.7cm', '127cm', '42.5cm', '113.9cm'], ['5XO (6XL)', '96.5cm', '83.9cm', '33.7cm', '131cm', '43.5cm', '116.4cm']]

df2 = pd.DataFrame(total_value_list).T

What I have done is -

df1["size_chart"] = df2

This assigns the whole data frame df2 to df1 in dataframe format but not in excel format. I want to write all the 2d array values of df1['size_chart'] in excel format.

After assigning the value of df2 into df1['size_chart'], I am expecting, df1 will look like this -

A B C size_chart D E
1 2 3 V W X Y Z  4 5
      P Q R S T
      L M N O P

Welcome to SO! please add a MRE. Maybe you should also have a look at how to ask a question — Rabinzel
– Rabinzel, Commented Jun 25, 2022 at 11:12
also not sure i understand, df2 is a table, how would it look if i put a table inside a column? — Omer Ben Haim
– Omer Ben Haim, Commented Jun 25, 2022 at 11:16
@OmerBenHaim Yes , df2 is a table. I have to create a nested excel table inside a column. That's where I am stuck. — syed towfiqur rahim
– syed towfiqur rahim, Commented Jun 25, 2022 at 11:21
@syedtowfiqurrahim stackoverflow.com/questions/51505504/pandas-nesting-dataframes i think this would help — Omer Ben Haim
– Omer Ben Haim, Commented Jun 25, 2022 at 11:23
@OmerBenHaim Sorry, the table should be in df1['size_chart'] value and the data of df2 should be in multi-index cells. Again sorry for not demonstrating the problem properly. — syed towfiqur rahim
– syed towfiqur rahim, Commented Jun 25, 2022 at 11:52

ragas · Accepted Answer · 2022-06-26 08:26:19Z

Please try this:

Original data:

total_value_list = [['', 'ウエスト', '股下', '股上', 'ヒップ', '裾回り', 'パンツ丈'], ['XS', '60.5cm', '70.4cm', '24.7cm', '95cm', '35cm', '93.9cm'], ['S', '64.5cm', '71.9cm', '25.7cm', '99cm', '35.5cm', '96.4cm'], ['6XO (7XL)', '100.5cm', '85.4cm', '34.7cm', '135cm', '44.5cm', '118.9cm'], ['M', '68.5cm', '73.4cm', '26.7cm', '103cm', '36.5cm', '98.9cm'], ['L', '72.5cm', '74.9cm', '27.7cm', '107cm', '37.5cm', '101.4cm'], ['O (XL)', '76.5cm', '76.4cm', '28.7cm', '111cm', '38.5cm', '103.9cm'], ['XO (2XL)', '80.5cm', '77.9cm', '29.7cm', '115cm', '39.5cm', '106.4cm'], ['2XO (3XL)', '84.5cm', '79.4cm', '30.7cm', '119cm', '40.5cm', '108.9cm'], ['3XO (4XL)', '88.5cm', '80.9cm', '31.7cm', '123cm', '41.5cm', '111.4cm'], ['4XO (5XL)', '92.5cm', '82.4cm', '32.7cm', '127cm', '42.5cm', '113.9cm'], ['5XO (6XL)', '96.5cm', '83.9cm', '33.7cm', '131cm', '43.5cm', '116.4cm']]

df2 = pd.DataFrame(total_value_list).T

df1 = pd.DataFrame({'A':[1,2,3,4,5,6,7]})

Updating size_cart

df2['combCol'] = df2[[0,1,2,3,4,5,6]].agg(' '.join, axis=1)

df1['size_cart'] = df2['combCol']

print(df1)


  A                                          size_cart
0    1                          XS S 6XO (7XL) M L O (XL)
1    2    ウエスト 60.5cm 64.5cm 100.5cm 68.5cm 72.5cm 76.5cm
2    3       股下 70.4cm 71.9cm 85.4cm 73.4cm 74.9cm 76.4cm
3    4       股上 24.7cm 25.7cm 34.7cm 26.7cm 27.7cm 28.7cm
4    5              ヒップ 95cm 99cm 135cm 103cm 107cm 111cm
5    6        裾回り 35cm 35.5cm 44.5cm 36.5cm 37.5cm 38.5cm
6    7  パンツ丈 93.9cm 96.4cm 118.9cm 98.9cm 101.4cm 103.9cm

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