Add multiple columns after pandas if-else if condition-CodePudding

I have a DateFrame:

what I am trying to achieve is to do add 2-3 columns after checking specific conditions

The condition is

limit_a = 1000
limit_b = 500
limit_c = 2000

if df['input_amount']>limit_a and df['type']=="A":
    df['approved amount'] = limit_a
    df['comment'] = 'limit reached for A'
else:
    df['approved amount'] = df['input_amount']
    df['comment'] = 'limit not reached for A'

if df['input_amount']>limit_b and df['type']=="B":
    df['approved amount'] = limit_b
    df['comment'] = 'limit reached for B'
else:
    df['approved amount'] = df['input_amount']
    df['comment'] = 'limit not reached for B'

This wasn't working for me.

This will be the resulting output.

CodePudding user response：

One way using map and min:

limits = {"A":1000,"B": 500, "C":2000}

df["approved_amount"] = df["type"].map(limits)
df["approved_amount"] = df[["input_amount", "approved_amount"]].min(axis=1)

Output:

   input_amount type  approved_amount
0          2000    A             1000
1           300    B              300
2           526    A              526
3          1000    A             1000
4          1500    C             1500
5          1350    B              500

CodePudding user response：

Use Series.clip with Series.map, for new column comment compare columns for not equal and set new values by numpy.where:

limit_a = 1000
limit_b = 500
limit_c = 2000
d = {'A':limit_a, 'B':limit_b, 'C':limit_c}
df['approved_amount']  = df['input_amount'].clip(upper=df['type'].map(d))

m = df['approved_amount'].ne(df['input_amount'])
df['comment'] = np.where(m, 'limit reached for ', 'limit not reached for ')   df['type']
print (df)
   input_amount type  approved_amount  approved amount  \
0          2000    A             1000             1000   
1           300    B              300              300   
2           526    A              526              526   
3          1000    A             1000             1000   
4          1500    C             1500             1500   
5          1350    B              500              500   

                   comment  
0      limit reached for A  
1  limit not reached for B  
2  limit not reached for A  
3  limit not reached for A  
4  limit not reached for C  
5      limit reached for B