How to create new Dataframe and new columns derived from existing values?

Asked Aug 24 '21 at 02:58

Active Aug 24 '21 at 02:58

Viewed 15 times

I have a dataframe df1 in this format:

df = pd.DataFrame(
{'Date': ['2015-02-24','2015-02-24','2015-02-25','2015-02-26'],
'Class': ['E','M','M','H'], 
'Value':[100,200,200,300]})

Date      Class Value
2015-02-24  E   100
2015-02-24  M   200
2015-02-25  M   200
2015-02-26  H   300

How can I do in python to make df to df1 in this format: Make classes "E, M, H" as new column names, and fill in values.

Expected output:

Date         E     M     H
2015-02-24  100   200   NaN
2015-02-25  NaN   200   NaN
2015-02-26  NaN   NaN   300

asked Aug 24 '21 at 02:58

Kath

See this https://stackoverflow.com/a/22799916 does it answer your question? – Ewelina Luczak Aug 24 '21 at 03:08
`df.pivot(index='Date', columns='Class', values='Value')` – Henry Ecker Aug 24 '21 at 03:10
Or `df.pivot(index='Date', columns='Class', values='Value').reindex(columns=pd.Index(['E', 'M', 'H'])).reset_index()` for same order columns in output. – Henry Ecker Aug 24 '21 at 03:11

How to create new Dataframe and new columns derived from existing values?

0 Answers0