1

I have a dataframe with a datetime column in string type, like this:

>>> df2
       date     a    b
0  2020/1/1   8.0  5.0
1  2020/1/2  10.0  7.0
2  2020/1/3   6.0  1.0
3  2020/1/4   6.0  3.0

I want use its 'date' column to generate a new index with various length by multiply a array, like this:

>>> idx_list = [2,3,1,2]
>>> df2.date*idx_list

but I got a unexpected result:

>>> df2.date*idx_list
0            2020/1/12020/1/1
1    2020/1/22020/1/22020/1/2
2                    2020/1/3
3            2020/1/42020/1/4

Is there a way to make a new index series to be a sequential data, like:

0 2020/1/1
1 2020/1/1
2 2020/1/2
3 2020/1/2
4 2020/1/2
5 2020/1/3
6 2020/1/4
7 2020/1/4

Thank you!

2 Answers2

1

Try this

df2 = pd.DataFrame({'date': ['2020/1/1', '2020/1/2', '2020/1/3', '2020/1/4'],
                    'a':    [8.0, 10.0, 6.0, 6.0],
                    'b':    [5.0, 7.0, 1.0, 3.0]})
idx_list = [2,3,1,2]
# use repeat
df2['date'].repeat(idx_list)
0    2020/1/1
0    2020/1/1
1    2020/1/2
1    2020/1/2
1    2020/1/2
2    2020/1/3
3    2020/1/4
3    2020/1/4
Name: date, dtype: object

If you want to make date the index, then try this

# make date the index
df2 = df2.set_index('date')
idx_list = [2,3,1,2]
use repeat and loc to create duplicated rows
df2 = df2.loc[df2.index.repeat(idx_list)]
print(df2)
             a    b
date               
2020/1/1   8.0  5.0
2020/1/1   8.0  5.0
2020/1/2  10.0  7.0
2020/1/2  10.0  7.0
2020/1/2  10.0  7.0
2020/1/3   6.0  1.0
2020/1/4   6.0  3.0
2020/1/4   6.0  3.0
cottontail
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0

You can try repeat the list n times then explode

idx_list = [2,3,1,2]

df = (df.assign(date=df['date'].apply(lambda x: [x]) * idx_list)
      .explode('date'))
print(df)

       date     a    b
0  2020/1/1   8.0  5.0
0  2020/1/1   8.0  5.0
1  2020/1/2  10.0  7.0
1  2020/1/2  10.0  7.0
1  2020/1/2  10.0  7.0
2  2020/1/3   6.0  1.0
3  2020/1/4   6.0  3.0
3  2020/1/4   6.0  3.0
Ynjxsjmh
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