Python Create column based on existing column with conditions-CodePudding

i have a dataframe with this format :

Ihave created an empty column USD Amount and i want to fill it with the currnecy converted in USD. i used the below code :

for cur in df1['CurrencyCode']:
    if cur=='RMB':
        df1['USD Amount']=df1['Amount']/6.39
    elif cur=='THB':
        df1['USD Amount']=df1['Amount']/33.26
    elif cur=='INR':
        df1['USD Amount']=df1['Amount']/75.01
    elif cur=='KRW':
        df1['USD Amount']=df1['Amount']/1,171.56
    elif cur=='VND':
        df1['USD Amount']=df1['Amount']/22,759.00
    elif cur=='IDR':
        df1['USD Amount']=df1['Amount']/14,188.86
    elif cur=='MYR':
        df1['USD Amount']=df1['Amount']/4.15
    elif cur=='USD':
        df1['USD Amount']=df1['Amount']/1
    elif cur=='EUR':
        df1['USD Amount']=df1['Amount']/0.86
    elif cur=='TUS':
        df1['USD Amount']=df1['Amount']/1
    elif cur=='GBP':
        df1['USD Amount']=df1['Amount']/33.26
    else:
        df1['USD Amount']=df1['Amount']

but i get:

      7         df1['USD Amount']=df1['Amount']/75.01
      8     elif cur=='KRW':
----> 9         df1['USD Amount']=df1['Amount']/1,171.56
     10     elif cur=='VND':
     11         df1['USD Amount']=round(df1['Amount']/22,759.00,2)

ValueError: Length of values (2) does not match length of index (9892)

What am i doing wrong here?

CodePudding user response：

I think these are comma issues. I think in line 9 the value should be 1171.56 and in line 11 it should be 22759 and line 13 should be 14188.86.

CodePudding user response：

I removed the commas in the conversion rates and created a function to apply to the dataframe

dict=[{'Username':'GEO','CurrencyCode':'EUR','Amount':1000},
  {'Username':'BUCK17','CurrencyCode':'GBP','Amount':1000},
  {'Username':'DRAC77','CurrencyCode':'LBP','Amount':1000}]

df=pd.DataFrame(dict)

def ConvertCurrency(row):
    ret_val=0.0
    if row['CurrencyCode']=='RMB':
        ret_val=row['Amount']/6.39
    elif row['CurrencyCode']=='THB':
        ret_val=row['Amount']/33.26
    elif row['CurrencyCode']=='INR':
        ret_val=row['Amount']/75.01
    elif row['CurrencyCode']=='KRW':
        ret_val=row['Amount']/1171.56
    elif row['CurrencyCode']=='VND':
        ret_val=row['Amount']/22759.00
    elif row['CurrencyCode']=='IDR':
        ret_val=row['Amount']/14188.86
    elif row['CurrencyCode']=='MYR':
        ret_val=row['Amount']/4.15
    elif row['CurrencyCode']=='USD':
        ret_val=row['Amount']/1
    elif row['CurrencyCode']=='EUR':
        ret_val=row['Amount']/0.86
    elif row['CurrencyCode']=='TUS':
        ret_val=row['Amount']/1
    elif row['CurrencyCode']=='GBP':
        ret_val=row['Amount']/33.26
    else:
       ret_val=row['Amount']
    
    return ret_val

df['USD Amount']=df.apply(ConvertCurrency,axis=1)
print(df)

output:

  Username CurrencyCode  Amount   USD Amount
0      GEO          EUR    1000  1162.790698
1   BUCK17          GBP    1000    30.066146
2   DRAC77          LBP    1000  1000.000000