I have few dataframes:
DF_1
| | TYPE | SYMBOL | DESCRIPTION | OPOL | FIRST_INTEREST_DATE |
|----|------|--------|-------------|------|---------------------|
| 0 | BOND | 1 | FIRST | 10 | 20220531 |
| 1 | BOND | 2 | SECOND | 20 | 20220515 |
| 2 | BOND | 3 | THIRD | 30 | 20220630 |
| 3 | BOND | 4 | FOURTH | 40 | 20210815 |
DF_2
| | TYPE | SYMBOL | DESCRIPTION | OPOL | ISIN |
|----|-------|--------|-------------|------|--------------|
| 0 | STOCK | 1 | FIRST | 101 | ABCDEFGHIKLM |
| 1 | STOCK | 7 | SEVENTH | 202 | MLKIHGFEDCBA |
| 2 | STOCK | 9 | NINETH | 303 | OPQRSTUVWXYZ |
| 3 | STOCK | 13 | THIRTEENTH | 404 | ZYXWVUTSRQPO |
| 4 | STOCK | 17 | SEVENTEENTH | 505 | ABCDEFFEDCBA |
How can i get dataframe DF_3 like table in bottom? And is it possible to transorm DF_3 in sql format?
| | TYPE | SYMBOL | DESCRIPTION | OPOL |FIRST_INTEREST_DATE| ISIN |
|----|-------|--------|---------------|--------|-------------------|--------------|
| 0 | BOND | 1 | FIRST | 10 | 20220531 | |
| 1 | BOND | 2 | SECOND | 20 | 20220515 | |
| 2 | BOND | 3 | THIRD | 30 | 20220630 | |
| 3 | BOND | 4 | FOURTH | 40 | 20210815 | |
| 4 | STOCK | 1 | FIRST | 101 | | ABCDEFGHIKLM |
| 5 | STOCK | 7 | SEVENTH | 202 | | MLKIHGFEDCBA |
| 6 | STOCK | 9 | NINETH | 303 | | OPQRSTUVWXYZ |
| 7 | STOCK | 13 | THIRTEENTH | 404 | | ZYXWVUTSRQPO |
| 8 | STOCK | 17 | SEVENTEENTH | 505 | | ABCDEFFEDCBA |
>Solution :
you need to upload code or show a sample of your data.
Anyways here’s a solution based on a limited information that you’ve provided:
df_3 = pd.concat([df_1, df_2], axis=0)
then you can use
from sqlalchemy import create_engine
engine = create_engine('sqlite://', echo=False)
df_3.to_sql('your_df_name', con=engine)