I have this large volume of climate data (15 years), but its taken at 5 minutes interval, please how do I manage data to a workable one and make sense without distorting information within?
You can manually convert from minutes to hours ,hours to days, days to month etc. Or, you may try using CDO (Climate data operator)
Dear Nura Umar Kura ,
It depends on what type of data it is.
If it is temperature data or similar then you can average it. In other words, add the items for the hour or day and divide by the number of items in that period, i.e. with five-minute data divide by 12 for hourly data and 288 for daily data.
If it is rainfall or similar, then just add the 12 items for each hour, or add 24 of those sums to get the daily total.
Does that help?
as salaamu alykum,
We can achieve this easily using the resample() function on the pandas DataFrame. Calling this function with the argument ‘D‘ allows the loaded data indexed by date-time to be grouped by day (see all offset aliases: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html).
source: machinelearningmastery.com