To add a missing value for a classification value

Asked 1 weeks ago, Updated 1 weeks ago, 0 views

Here's the basic data content!

I classified the data above by date and time

df4 = pd.pivot_table (df, index=["month-to-month", day-to-month", parking time zone", values=["count"], aggfunc=np.sum)


It came out as above

Date not in the data (ex-2021-01-02) and time zone not in the data (ex - January 1, 2021 2 hours, 3 hours, 4 hours...etc.)

All dates for 1 year and

I'd like to classify it as less than an hour per day, 1 hour, 2 hours, 3 hours ------12 hours, 13 hours or more

Expected Results


2022-09-20 08:42

1 Answers

If I were you, I'd make a column called "Parking Time Category" in the original df first.

def time zone to time zone category (time zone):
    If "min" in time zone: return "less than 1 hour"
    n = int (time zone.split ("time") [0])
    if > 12: return "more than 13 hours"
    Return time zone

df["Park Time Category"] = df["Park Time Zone"].apply (time to time category)

2022-09-20 08:42

If you have any answers or tips

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