I have this dataframe:
Category 3,Chapter I,Chapter II,Chapter III
prima,126,97,83
da,38,24,24
sps.,22,17,18
How to make it like:
prima,126,Chapter I
prima, 97, Chapter II
prima, 83, Chapter III
da, 38, Chapter I
[...]
Asked
Active
Viewed 44 times
0
Anna
- 369
- 2
- 10
-
1`df.melt('Category 3')`? – ansev Jul 02 '20 at 17:51
-
1Does this answer your question? [pandas convert some columns into rows](https://stackoverflow.com/questions/28654047/pandas-convert-some-columns-into-rows) – Shubham Sharma Jul 02 '20 at 17:51
-
df.stack() would basically do the job, as it stack a level from the columns as the inner most labels in the rows. – Borut Flis Jul 02 '20 at 18:58
1 Answers
0
You can run:
result = df.set_index('Category 3').stack().rename('Value').reset_index()
For your data sample the result is:
Category 3 level_1 Value
0 prima Chapter I 126
1 prima Chapter II 97
2 prima Chapter III 83
3 da Chapter I 38
4 da Chapter II 24
5 da Chapter III 24
6 sps. Chapter I 22
7 sps. Chapter II 17
8 sps. Chapter III 18
If you want, rename level_1 column to any meaningful name and change the order of columns.
Valdi_Bo
- 30,023
- 4
- 23
- 41