如何合并两个不同时间范围的数据集？

Question

I have two datasets that look like this:

df1 :

Date	City	State	Quantity
2019-01	Chicago	IL	35
2019-01	Orlando	FL	322
...	....	...	...
2021-07	Chicago	IL	334
2021-07	Orlando	FL	4332

df2 :

Date	City	State	Sales
2020-03	Chicago	IL	30
2020-03	Orlando	FL	319
...	...	...	...
2021-07	Chicago	IL	331
2021-07	Orlando	FL	4000

My date is in format period[M] for both datasets. I have tried using the df1.join(df2,how='outer') and (df2.join(df1,how='outer') commands but they don't add up correctly, essentially, in 2019-01 , I have sales for 2020-03 . How can I join these two datasets such that my output is as follows:

I have not been able to use merge() because I would have to merge with a combination of City and State and Date

Date	City	State	Quantity	Sales
2019-01	Chicago	IL	35	NaN
2019-01	Orlando	FL	322	NaN
...	...	...	...	...
2021-07	Chicago	IL	334	331
2021-07	Orlando	FL	4332	4000

Answer 1

You can outer-merge . By not specifying the columns to merge on, you merge on the intersection of the columns in both DataFrames (in this case, Date , City and State ).

out = df1.merge(df2, how='outer').sort_values(by='Date')

Output:

      Date     City State  Quantity   Sales
0  2019-01  Chicago    IL      35.0     NaN
1  2019-01  Orlando    FL     322.0     NaN
4  2020-03  Chicago    IL       NaN    30.0
5  2020-03  Orlando    FL       NaN   319.0
2  2021-07  Chicago    IL     334.0   331.0
3  2021-07  Orlando    FL    4332.0  4000.0