How can I breakdown a row in csv with pandas in python?

Question

I'm working with csv on pandas. I'm trying to break a row like this:

| col1  | col2  | jan | feb | mar |
|-------|-------|-----|-----|-----|
| name1 | place | 23  | 32  | 42  |
| name2 | place | 43  | 666 | 3   |
| name3 | place | 2   | 532 | 420 |

into this:

| col1  | col2  |months | quantity |
|-------|-------|-------|----------|
| name1 | place | jan   | 23       |
| name1 | place | feb   | 32       |
| name1 | place | mar   | 42       |
| name2 | place | jan   | 43       |
| name2 | place | feb   | 666      |
| name2 | place | mar   | 3        |
| name3 | place | jan   | 2        |
| name3 | place | feb   | 532      |
| name3 | place | mar   | 420      |

any function to breakdown rows on pandas?

pandas.melt() does not work as i want, because it does not create the order i intended.

This is a typical case of `unpivot` or in pandas we call it `melt`. Use the following to get your output: `pd.melt(df, id_vars=['col1', 'col2'])` — Erfan, May 08 '19 at 00:04
@Erfan while `melt` yields the same *set* of data, orders are different from what OP asks for, which may or may not be important. — Quang Hoang, May 08 '19 at 00:11
@DYZ really? What if `col1` is not ordered in original dataframe? — Quang Hoang, May 08 '19 at 00:14

score 1 · Accepted Answer · answered May 08 '19 at 00:02

1

Try:

df.set_index(['col1','col2']).stack().reset_index()

You may need to rename some columns afterwards.

answered May 08 '19 at 00:02

Quang Hoang

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How can I breakdown a row in csv with pandas in python?

1 Answers1