Timeline for python / pandas - Find common columns between two dataframes, and create another one with same columns showing their difference
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| S Dec 22, 2020 at 19:51 | history | suggested | sophocles | CC BY-SA 4.0 |
made the reading clearer
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| Dec 22, 2020 at 18:19 | review | Suggested edits | |||
| S Dec 22, 2020 at 19:51 | |||||
| Dec 2, 2020 at 15:48 | comment | added | Satarupa | sorry at first I thought concatenation was the problem, I have attached a small code. | |
| Dec 2, 2020 at 14:50 | comment | added | sophocles | I don't think that answers my question. I am not just referring about merging the 2 files. I am referring at substracting the common columns between the new files, and store the results in a new data frame, wich all the common columns in it. Thank you though. | |
| Dec 2, 2020 at 14:31 | comment | added | Satarupa | Doesn't this stackoverflow.com/questions/21231834/…. answer the question | |
| Dec 2, 2020 at 14:29 | comment | added | Satarupa | Then in that case you can use pandas.concat([df1['c'], df2['c']], axis=1, keys=['df1', 'df2']) | |
| Dec 2, 2020 at 14:25 | comment | added | sophocles | Yeah I did try, but how does that help me? The problem is appending the new info in the new dataframe, not looping over the columns. | |
| Dec 2, 2020 at 14:23 | history | answered | Satarupa | CC BY-SA 4.0 |