Unstacking values into different rows in Pandas DataFrame

Question

I have a DataFrame (below). I am interested in unstacking the from and to columns.

I need to unstack from and to columns into multiple rows for each different year between from and to. For example, the first row will produce something like this

I tried everything from pd.melt() to pd.pivot_table().

ALollz · Accepted Answer · 2020-07-30 04:52:08Z

4

Create a column of array-like objects with all of the years between 'from' and 'to' then explode on that column. It won't be the most efficient solution, but it's simple.

Sample Data

   a  b  c  d  e  from    to
0  2  9  1  7  3  1940  1945
1  5  6  2  6  1  1950  1951

Code

df['year'] = [np.arange(f,t+1) for f,t in zip(df['from'], df['to'])]
df = df.explode('year')

   a  b  c  d  e  from    to  year
0  2  9  1  7  3  1940  1945  1940
0  2  9  1  7  3  1940  1945  1941
0  2  9  1  7  3  1940  1945  1942
0  2  9  1  7  3  1940  1945  1943
0  2  9  1  7  3  1940  1945  1944
0  2  9  1  7  3  1940  1945  1945
1  5  6  2  6  1  1950  1951  1950
1  5  6  2  6  1  1950  1951  1951

answered Jul 30, 2020 at 4:52

ALollz

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1 Comment

mmustafaicer Over a year ago

Thank you. Never heard of this pd.explode() method. It worked.

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