Replace the column value with certain conditions

March 8, 2022

My dataframe looks like the below and name of the dataframe is "Assert_data"

System_Name  Type
ABC          Test-3451
BCS          Dev-2323
ASD          Dev-1213
FGS          Prod-1212
ASC          Tes-1244

Need help to replace the column value , If the Type column has a value as "Prod" , It should be replaced to "Production"

Likewise for Dev ==> Development & Tes ==> Test

I tired the following coding , But it throws "ValueError: either both or neither of x and y should be given"

df['Instance_type'] = np.where(Assert_data['Type'].str.contains("Prod"), "Production",
                                np.where(Assert_data['Type'].str.contains("Dev"), "Development",
                                np.where(Assert_data['Type'].str.contains("Tes"), "Test")))

Tried using pd.np.where – Same error message.

>Solution :

For last np.where is missing value y – if not match any condition:

Assert_data['Instance_type'] = np.where(Assert_data['Type'].str.contains("Prod"), "Production",
                               np.where(Assert_data['Type'].str.contains("Dev"), "Development",
                               np.where(Assert_data['Type'].str.contains("Tes"), "Test", None)))

print (Assert_data)
  System_Name       Type Instance_type
0         ABC  Test-3451          Test
1         BCS   Dev-2323   Development
2         ASD   Dev-1213   Development
3         FGS  Prod-1212    Production
4         ASC   Tes-1244          Test

Or use numpy.select:

Assert_data['Instance_type'] = np.select([Assert_data['Type'].str.contains("Prod"),
                                          Assert_data['Type'].str.contains("Dev"),
                                          Assert_data['Type'].str.contains("Tes")],
                                         [ "Production","Development","Test"],
                                         default=None)

Or use Series.str.extract with Series.map:

d = {'Prod': "Production","Dev":"Development","Tes":"Test"}

Assert_data['Instance_type'] = Assert_data['Type'].str.extract(f'({"|".join(d)})', expand=False).map(d)