Merging two dataframes at only different rows and columns

Question

I have the following dataframes:

df1

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and df2

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I want to merge the two dataframes at only the uncommon rows and columns such that the outcomes will be like the below as df_merged:

enter image description here

Can anyone suggest the best way to get the result dataframe as shown above?

Have you looked through the pandas tag wiki and read the canonical question on merging dataframes? — Paul H, Aug 22 '23 at 13:36
Does this answer your question? [Pandas Merging 101](https://stackoverflow.com/questions/53645882/pandas-merging-101) — PV8, Aug 22 '23 at 13:38

score 0 · Accepted Answer · answered Aug 22 '23 at 13:54

What you want is to concatenate the dataframes, not merge them. You can do that and then sort on parameter and date, finally filling NaN with ''.

df1 = pd.DataFrame({ 'parameter' : ['A', 'B'], 'date' : ['2023-01-01', '2023-01-02'], 'column2' : ['A2_1', 'B2_2'], 'column3' : ['A3_1', 'B3_2'], 'column4' : ['A4_1', 'B4_2'], 'column5' : ['A5_1', 'B5_2'] })
df2 = pd.DataFrame({ 'parameter' : ['A', 'C'], 'date' : ['2023-01-02', '2023-01-03'], 'column4' : ['A4_2', 'C4_3'], 'column5' : ['A5_2', 'C5_3'], 'column6' : ['A6_2', 'C6_3'], 'column7' : ['A7_2', 'C7_3'] })
res = pd.concat([df1, df2]).sort_values(['parameter', 'date']).fillna('').reset_index(drop=True)
print(res)

Output:

  parameter        date column2 column3 column4 column5 column6 column7
0         A  2023-01-01    A2_1    A3_1    A4_1    A5_1
1         A  2023-01-02                    A4_2    A5_2    A6_2    A7_2
2         B  2023-01-02    B2_2    B3_2    B4_2    B5_2
3         C  2023-01-03                    C4_3    C5_3    C6_3    C7_3

Thank you Nick for the answer. This solution worked out for the problem. — python_beginner, Aug 23 '23 at 09:17

Merging two dataframes at only different rows and columns

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