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Tag: timestamp

Compare two DataFrames and find missing timestamps

I have the following two dataframes: and in df2 I have some missing timestamps compared to df1. I am able to find those timestamps using the following code: I want to populate those missing timestamps in df2 and fill in the values of the columns with the average value of the two previous rows. So the new df2 should look

Create a dataframe containing all weekends in a given year

Good afternoon, I would like to create a function that, given a year, would return a dataframe with all the dates in Timestamp format related to the Saturdays and Sundays of that year. That is to say: The function would return: If you can tell me an optimal way to get that dataframe I would be grateful. Answer Well here’s

Timestamp of Outlook emails using Python

Is it possible to use Python to extract timestamps from received email? I’m using the following code but to no avail: I only get one date published repeatedly for each email. (i.e., 2021-11-22, 2021-11-22, 2021-11-22…….) Any help will be much appreciated. Answer Well, of course – you only retrieve ReceivedTime once:

Dropping rows at specific minutes

I am trying to drop rows at specific minutes ( 05,10, 20 ) I have datetime as an index Then I run below it returnes invalid syntax error. Answer You can just do it using boolean indexing, assuming that the index is already parsed as datetime. Or the opposite of the same answer:

Python: Round decimal places after seconds in timestamp

I have this series: Initially, I wanted to round to seconds by doing: However, I am trying to merge this dataset to another of higher frequency. So I’d like to round the decimal places of the timestamp instead. Example: 2021-06-15 16:23:04.388 would become 2021-06-15 16:23:04.380 How can I do this? to a timestamp? Answer If .388 should become .380 we

Why does my date column change when I convert to an ndarray

below is my dataframe when I convert my ‘Year” column to list(), they are saved as time stamp However, when I convert to values they are saved as datetime64 How do I get my array in Timestamp itself (instead of datetime64 format)? Answer It’s converted to a datetime64 because numpy arrays only hold certain datatypes. Timestamp objects are not one

What is the best practice to convert HTTP timestamps to standard format during dataframing using pandas in python?

I’m trying to convert HTTP timestamps into standard timestamp for complete data framing and getting time-series plots. I’m looking for an efficient way to do this for the large dataset. My actual data frame is as follows: I have tried couple of the following methods and get errors: This returns me NaT which is strange! I updated the format and