Pandas Propagate Data
Question:
newbie here.
Working whith Pandas
I have this df
SPT.ant
Dif_Sig
Order_Price
NaN
True
Nan
19297
True
19297
19297
False
0
19302
False
0
19350
True
19350
19345
False
0
19355
False
0
19360
False
0
The way "Order_Price" is calculated is :
df[‘Order_Price’] = df[‘SPT.ant’] * df[‘Dif_Sig’]
and need to propagate de value of "Order_Price" from row 2 "19297" and row 5 "19350" utill a new value is diferent to 0
so the table would result
SPT.ant
Dif_Sig
Order_Price
NaN
True
Nan
19297
True
19297
19297
False
19297
19302
False
19297
19350
True
19350
19345
False
19350
19355
False
19350
19360
False
19350
it would be ok to have this in another column as well, whatever is easier.
SPT.ant
Dif_Sig
Order_Price
Position_Price
NaN
True
Nan
Nan
19297
True
19297
19297
19297
False
0
19297
19302
False
0
19297
19350
True
19350
19350
19345
False
0
19350
19355
False
0
19350
19360
False
0
19350
I would like to input the values without having to iterate de df but dont know if posible.
I tried many ways but got even more confused now.
Any help would apreciate
Answers:
You basically need to forward fill the zeros (ffill method)
df['Position_Price'] = df['Order_Price'].replace(to_replace=0, method='ffill')
newbie here.
Working whith Pandas
I have this df
| SPT.ant | Dif_Sig | Order_Price |
|---|---|---|
| NaN | True | Nan |
| 19297 | True | 19297 |
| 19297 | False | 0 |
| 19302 | False | 0 |
| 19350 | True | 19350 |
| 19345 | False | 0 |
| 19355 | False | 0 |
| 19360 | False | 0 |
The way "Order_Price" is calculated is :
df[‘Order_Price’] = df[‘SPT.ant’] * df[‘Dif_Sig’]
and need to propagate de value of "Order_Price" from row 2 "19297" and row 5 "19350" utill a new value is diferent to 0
so the table would result
| SPT.ant | Dif_Sig | Order_Price |
|---|---|---|
| NaN | True | Nan |
| 19297 | True | 19297 |
| 19297 | False | 19297 |
| 19302 | False | 19297 |
| 19350 | True | 19350 |
| 19345 | False | 19350 |
| 19355 | False | 19350 |
| 19360 | False | 19350 |
it would be ok to have this in another column as well, whatever is easier.
| SPT.ant | Dif_Sig | Order_Price | Position_Price |
|---|---|---|---|
| NaN | True | Nan | Nan |
| 19297 | True | 19297 | 19297 |
| 19297 | False | 0 | 19297 |
| 19302 | False | 0 | 19297 |
| 19350 | True | 19350 | 19350 |
| 19345 | False | 0 | 19350 |
| 19355 | False | 0 | 19350 |
| 19360 | False | 0 | 19350 |
I would like to input the values without having to iterate de df but dont know if posible.
I tried many ways but got even more confused now.
Any help would apreciate
You basically need to forward fill the zeros (ffill method)
df['Position_Price'] = df['Order_Price'].replace(to_replace=0, method='ffill')