for Loop multiple conditions

Question

I am trying to create a new variable (column) which values depend on the values of other variable, therefore I try to create a for loop with multiple conditions.

Here is the code that I tried:

ABC_Levels = []
for i in range(len(df_ABC)):
    if df_ABC.loc[i,'ABC']>=5.7:
        ABC_Levels.append('High')
    elif df_ABC.loc[i,'ABC']<5.4:
        ABC_Levels.append('Low')
    else:
        ABC_Levels.append('Intermediate')
ABC_Levels

It returns the following error:

KeyError: 0

The above exception was the direct cause of the following exception:

I guess that is something related with the first row because if I change the code for this one:

ABC_Levels = []
for i in range(len(df_ABC['ABC'])):
    if df_ABC.loc[i]>=5.7:
        ABC_Levels.append('High')
    elif df_ABC.loc[i]<5.4:
        ABC_Levels.append('Low')
    else:
        ABC_Levels.append('Intermediate')
ABC_Levels

It returns the value of the first row.

I’ll appreciate any help

Asked By: Alex

||

Source

Answer 1

Not an answer (at least a full one), but personally I would try to use np.select instead of enumerating the dataframe. For example:

series = df_ABC['ABC']
conds = [series >= 5.7, series < 5.4]
choices = ['High', 'Low'] 
np.select(conds, choices, default='Intermediate').tolist()

UPD

Modification which worked for OP:

conditions = [ (df_ABC['ABC'] >= 5.7), (df_ABC['ABC'] <= 5.4) ] 
choices = ['High', 'Low'] 
df_ABC['ABC_expression'] = np.select(conditions, choices, default='Intermediate')
df_ABC

Answered By: Guru Stron

for Loop multiple conditions

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