CODEWITHSUNDEEP
pythonpandas
Pysnek313
Pysnek313

Reputation: 134

Pandas: If value is present in one column than replace it

Trying to write a For loop that looks to see if a number exists in the Pay_Day_Supply_Count column and if so, replace the day number in the Days column with a 0.

Example Dataframe

|Days   | Pay_Day_Supply_Count  |
--------------------------------|
|   0   |     15                |
| -456  |     50                |
|  121  |     10                |
|   0   |     15                |
|   0   |     10                |
|  323  |     20                |
|   0   |     05                |
| -444  |     10                |
|  141  |     20                |
---------------------------------

Expected Output

|Days   | Pay_Day_Supply_Count  |
--------------------------------|
|   0   |     15                |
|   0   |     50                |
|   0   |     10                |
|   0   |     15                |
|   0   |     10                |
|   0   |     20                |
|   0   |     05                |
|   0   |     10                |
|   0   |     20                |
---------------------------------

This is what i've tried so far:

for i, p in enumerate(df["Days"]):
    if df["PAY_DAY_SUPPLY_CNT"] != '': 
        p1 = p.replace('%d', 0)
        df.at[i, 'Days'] = p1

Returned error

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Upvotes: 0

Views: 2090

Answers (2)

Quickbeam2k1
Quickbeam2k1

Reputation: 5437

Maybe using boolean masking could help. Unsure about your dtypes though:

mask = df[Pay_Day_Supply_Count].notna()
df.loc[mask, "Day"]=0

Upvotes: 3

Mohsen_Fatemi
Mohsen_Fatemi

Reputation: 3391

You can use numpy.where function to do this in one line :

import pandas as pd
import numpy as np

df['Days'] = np.where(df["PAY_DAY_SUPPLY_CNT"] != '', 0 , df['Days'] )

Upvotes: 1

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