using pandas apply lambda with conditions
Question:
Product
Price
Timestamp
AdjPrice
A1
1142
1/3/2022
A1
1148
1/4/2022
A1
1177
1/5/2022
A1
1163
1/6/2022
A1
1160
1/7/2022
I have the above dataframe. The last column (AdjPrice) must be populated by multiplying the Price with a static factor (0.15 for instance), if the Timestamp is less than a given date (1/5/2022).
mydate = pd.to_datetime("1/5/2022",format='%d/%m/%Y')
df['AdjPrice'] = df['AdjPrice'].apply(lambda x: (df['Price'] * 0.15) if x['Timestamp'] < mydate else df['Price']
gives me the following error.
TypeError: string indices must be integers
I’m not sure how to achieve this. Help?
Answers:
This code will fix your problem:
mydate = pd.to_datetime("1/5/2022",format='%d/%m/%Y')
df['AdjPrice'] = df.apply(lambda x: x['Price'] * 0.15 if pd.to_datetime(x['Timestamp']) < mydate else x['Price'], axis=1)
| Product | Price | Timestamp | AdjPrice |
|---|---|---|---|
| A1 | 1142 | 1/3/2022 | |
| A1 | 1148 | 1/4/2022 | |
| A1 | 1177 | 1/5/2022 | |
| A1 | 1163 | 1/6/2022 | |
| A1 | 1160 | 1/7/2022 |
I have the above dataframe. The last column (AdjPrice) must be populated by multiplying the Price with a static factor (0.15 for instance), if the Timestamp is less than a given date (1/5/2022).
mydate = pd.to_datetime("1/5/2022",format='%d/%m/%Y')
df['AdjPrice'] = df['AdjPrice'].apply(lambda x: (df['Price'] * 0.15) if x['Timestamp'] < mydate else df['Price']
gives me the following error.
TypeError: string indices must be integers
I’m not sure how to achieve this. Help?
This code will fix your problem:
mydate = pd.to_datetime("1/5/2022",format='%d/%m/%Y')
df['AdjPrice'] = df.apply(lambda x: x['Price'] * 0.15 if pd.to_datetime(x['Timestamp']) < mydate else x['Price'], axis=1)