Using Conditional statements in Pandas DataFrame to derive new columns with specific values

Question

I have a data set like this

ID    Status
1     Completed
2     Completed
3     Cancelled
4     Cancelled
5     Not Available
6     Not Available

I want to create new column and put value 1 wherever status got completed

ID    Status          Supply
1     Completed         1
2     Completed         1 
3     Cancelled
4     Cancelled
5     Not Available
6     Not Available

Thanks

Answer 1

If df is your DataFrame

           Status
ID               
0       Completed
1       Completed
2       Cancelled
3       Cancelled
4   Not available
5   Not available

Use df["Status"] == "Completed" to find the rows where condition is fulfilled and then convert the boolean to integer using .astype(int).

df["Supply"] = (df["Status"] == "Completed").astype(int)

The result is

          Status     Supply
ID                       
0       Completed       1
1       Completed       1
2       Cancelled       0
3       Cancelled       0
4   Not available       0
5   Not available       0

Answer 2

Please explain your question carefully and use code sample format to write codes. From what i understood this is what you want:

import pandas as pd
import numpy as np
#Existing Data
data={'id':[1,2,3,4,5,6],'status':['Completed','Completed','Cancelled','Cancelled','Na','Na']}
#Create a dataframe
df=pd.DataFrame(data)
#Add the 'Supply' Column
df['supply']=np.where(df['status']=='Completed',1,0)

Check this for more info: Pandas Conditional creation of DataFrame

Also please post the code of what you tried.

Good Luck!

May the Code be with you!