create a "Business Hour" column to indicate whether a particular timestamp was within business hours in pandas

I'm trying to add a "Buiness_hour" to the dataframe base on value of the datetime index. Say if an entry is fall between 0800 to 1800, the entry under the "Business_hour" would return "Yes" else "No".

The existing df is like:

I would like to insert the "business hr" column so I can find out the number of transactions made outside business hours

I tried using apply with lambda function

df['Business_hour'] = df.index.apply(
    lambda x: 'Yes' if df.index.hour >= 9 and df.index.hour < 18 else 'No')

and it says that 'DatetimeIndex' object has no attribute 'apply'

i then tried the more basic solution and having the same results:

def business_hr(x):
    if x >= 8:
        return 'Yes'
    if x <= 18:
        return "Yes"
    else:
        'No'

df['Business_hr'] = df.index.hour.apply(business_hr)

Use np.where:

m = (9 <= df.index.hour) & (df.index.hour < 18)
df['Business_hour'] = np.where(m, 'Yes', 'No')
print(df)

# Output
                     UserID Business_hour
2021-03-31 20:54:54  143173            No
2021-03-31 22:54:54  143173            No
2021-03-31 09:54:54  143173           Yes

If you want to use your function, replace apply (DataFrame) by map (Series):

def business_hr(x):
    return 'Yes' if 8 <= x < 18 else 'No'

df['Business_hour'] = df.index.hour.map(business_hr)
print(df)

# Output
                     UserID Business_hour
2021-03-31 20:54:54  143173            No
2021-03-31 22:54:54  143173            No
2021-03-31 09:54:54  143173           Yes