Adding Pandas column in custom function not working when using numpy

Question

I have the following function:

def create_col4(df):
    df['col4'] = df['col1'] + df['col2']

If I apply this function within my jupyter notebook as in

create_col4(df_test)

, df_test is persistently amended by col4.

However, if I have the following code where I apply a numpy function:

import numpy as np
def create_col4(df):
    df['col4'] = np.where(df[col1] == 1, True, False)

,

create_col4(df_test) 

does neither persistently append df_test by col4 nor does it throw an error.

Why is this?

---

The full use case code in case the reason is in the individual code:

working:

def create_leg(df):
    df['leg'] = df["dep_ap_sched"] + "-" + df["arr_ap_sched"]

also working when doing in the jupyter notebook directly:

df['rot_mismatch'] = np.where(
    df['ac_registration_x'].shift(-1).eq(df['ac_registration_x']) == True, 
    ~df['dep_ap_sched'].shift(-1).eq(df['arr_ap_sched']), 
    False 
)

not working:

create_rotmismatch(some_df) where

def create_rotmismatch(df):
    df['rot_mismatch'] = np.where(
        df['ac_registration_x'].shift(-1).eq(df['ac_registration_x']) == True, 
        ~df['dep_ap_sched'].shift(-1).eq(df['arr_ap_sched']), 
        False 
    )

Answer 1

import numpy as np
def create_col4(df_test):
    df['col4'] = np.where(df[col1] == 1, True, False)

Without inspecting further what I first saw was this. Either df_test or df but you mix names here.

Change it to:

import numpy as np
def create_col4(df):
    df['col4'] = np.where(df[col1] == 1, True, False)

About your other concerns, try to return the df at the end of your function.

def create_rotmismatch(df):
    df['rot_mismatch'] = np.where(
        df['ac_registration_x'].shift(-1).eq(df['ac_registration_x']) == True, 
        ~df['dep_ap_sched'].shift(-1).eq(df['arr_ap_sched']), 
        False 
    )
    return df

df = create_rotmismatch(df)