hoping you can help me solve this one. I am working on a project which involves tracking lapse time between when an order is placed and when it's delivered. The date formats of the file I'm working with is as follows: "Calendar Day :hour:minute:second"

That said, I was able to create datetime64[ns] objects for the attributes using the following code:

df["Customer placed order datetime"] = pd.to_datetime(data["Customer placed order datetime"], format='%d %H:%M:%S')
data["Delivered to consumer datetime"] = pd.to_datetime(data["Delivered to consumer datetime"], format='%d %H:%M:%S')

I am then taking the difference of when an order is delivered - when it was placed to get the total time lapse

data["lapse"] = data["Delivered to consumer datetime"] - data["Customer placed order datetime"]

This works great for orders delivered the same day, however I am running into a problem with orders placed late at night and delivered the next day. Please see example below:

Customer placed order | datetime Delivered to consumer datetime | lapse

1900-01-31 23:59:46 | 1900-01-01 01:49:07 | 31 days 01:49:21

Any suggestions on how to fix this issue?

Thanks!

CodePudding user response：

It doesn't look like there's an issue with your code. The dates you gave as an example actually have 31 days between them. Do you have a typo in your dates data?

CodePudding user response：

The example provided doesn't reflect the problem you are trying to solve. The dates in the example are a month apart from one another. Try to recreate the error using a valid example and see if the issue still persists