I have hourly data on electricity consumption for a specific day. I would like to use this data to “predict” the hourly electricity consumption for the following days. The value for the following day should be the value from the same hour the day before, multiplied by a scaling factor f (e.g. 2). The dataframe df that I have looks
Tag: datetimeindex
Datetime rolling count per category in Pandas
Starting from a DataFrame with a date and user column, I’d like to add a third count_past_5_days column to indicate the rolling count of occurrences of each row’s user during the past 5 days: date user count_past_5_days 2020-01-01 abc 1 2020-01-01 def 1 2020-01-02 abc 2 2020-01-03 abc 3 2020-01-04 abc 4 2020-01-04 def 2 2020-01-04 ghi 1 2020-01-05 abc
How to filter a pandas series with a datetime index on the quarter and year
I have a Series, called ‘scores’, with a datetime index. I wish to subset it by quarter and year pseudocode: series.loc[‘q2 of 2013’] Attempts so far: s.dt.quarter AttributeError: Can only use .dt accessor with datetimelike values s.index.dt.quarter AttributeError: ‘DatetimeIndex’ object has no attribute ‘dt’ This works (inspired by this answer), but I can’t believe it is the right way to