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Tag: datetime

How would I find the quarterly averages of these monthly figures?

My dataset is similar to the below: How can I add columns to this which show the quarterly figure, which is an average of the preceding three months? Eg, suppose we started at adding a column after ‘Dec-21’ called Q4 2021 which took the average of the columns called ‘Oct-21’, ‘Nov-21’ and ‘Dec-21’. Will I need to create a function

Pandas dataframe – fillna with last of next month

I’ve been staring at this way too long and I think Ive lost my mind, it really shouldn’t be as complicated as I’m making it. I have a df: Date1 Date2 2022-04-01 2022-06-17 2022-04-15 2022-04-15 2022-03-03 NaT 2022-04-22 NaT 2022-05-06 2022-06-06 I want to fill the blanks in ‘Date2’ where it keeps the values from ‘Date2’ if they are present

Taking the recency time of client purchase with PySpark

The sample of the dataset I am working on: I’d like to take the customer’s most recent purchase (the customer’s date.max()) and the previous maximum purchase (the penultimate purchase) and take the difference between the two (I’m assuming the same product on all purchases). I still haven’t found something in pyspark that does this. One example of my idea was

How can I fix the list index out of range problem?

So I wanna fill NaN value of the pay date with the date one month after the join date. Join date Payday1 Okt’10 NaN Des’10 NaN My expectation output is: Join date Payday1 Okt’10 Nov’10 Des’10 Jan’11 I try this code: This code is error in this code month=months[months.index(month)+1], it said list index out of range. So how to fix

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