Create Multi-Index empty DataFrame to join with main DataFrame-CodePudding

Suppose that I have a dataframe which can be created using code below

df = pd.DataFrame(data = {'date':['2021-01-01', '2021-01-02', '2021-01-05','2021-01-02', '2021-01-03', '2021-01-05'],
                          'product':['A', 'A', 'A', 'B', 'B', 'B'],
                          'price':[10, 20, 30, 40, 50, 60]
                         }
                 )
df['date'] = pd.to_datetime(df['date'])

I want to create an empty dataframe let's say main_df which will contain all dates between df.date.min() and df.date.max() for each product and on days where values in nan I want to ffill and bfill for remaning. The resulting dataframe would be as below:

 ------------ --------- ------- 
|    date    | product | price |
 ------------ --------- ------- 
| 2021-01-01 | A       |    10 |
| 2021-01-02 | A       |    20 |
| 2021-01-03 | A       |    20 |
| 2021-01-04 | A       |    20 |
| 2021-01-05 | A       |    30 |
| 2021-01-01 | B       |    40 |
| 2021-01-02 | B       |    40 |
| 2021-01-03 | B       |    50 |
| 2021-01-04 | B       |    50 |
| 2021-01-05 | B       |    60 |
 ------------ --------- -------

CodePudding user response：

First

make pivot table, upsampling by asfreq and fill null

df.pivot_table('price', 'date', 'product').asfreq('D').ffill().bfill()

output:

product     A       B
date        
2021-01-01  10.0    40.0
2021-01-02  20.0    40.0
2021-01-03  20.0    50.0
2021-01-04  20.0    50.0
2021-01-05  30.0    60.0

Second

stack result and so on (include full code)

(df.pivot_table('price', 'date', 'product').asfreq('D').ffill().bfill()
 .stack().reset_index().rename(columns={0:'price'})
 .sort_values('product').reset_index(drop=True))

output:

    date        product price
0   2021-01-01  A       10.0
1   2021-01-02  A       20.0
2   2021-01-03  A       20.0
3   2021-01-04  A       20.0
4   2021-01-05  A       30.0
5   2021-01-01  B       40.0
6   2021-01-02  B       40.0
7   2021-01-03  B       50.0
8   2021-01-04  B       50.0
9   2021-01-05  B       60.0