Average over a specific time period

Question

I have a quite huge table in python from a .h5 file The start of the table looks somewhat like this:

table =
                [WIND REL DIRECTION  [deg]]  [WIND S         


        

Answer 1

I think this is the "right" way to do this. (Although it seems a little bit underdocumented to me. Anyway it works!)

You need to do a groupby on your DataFrame and use something called a TimeGrouper.

It works like this:

import pandas as pd
import numpy as np

# Create a dataframe. You can ignore all this bit!
periods = 60 * 60
random_dates = pd.date_range('2015-12-25', periods=periods, freq='s')
random_speeds = np.random.randint(100, size=periods)
random_directions = np.random.random(periods)
df = pd.DataFrame({'date': random_dates, 'wind_speed': random_speeds, 'wind_direction': random_directions})
df = df.set_index('date')

# Here's where the magic happens:
grouped15s = df.groupby(pd.TimeGrouper(freq='15S'))
averages_ws_15s = grouped15s.wind_speed.mean()

Or, if you insist on having spaces in your column names, that last line will become:

averages_ws_15s = grouped15s['Wind Speed'].mean()

This results in the following:

date
2015-12-25 00:00:00    45.800000
2015-12-25 00:00:15    48.466667
2015-12-25 00:00:30    38.066667
2015-12-25 00:00:45    54.866667
2015-12-25 00:01:00    34.866667
2015-12-25 00:01:15    37.000000
2015-12-25 00:01:30    47.133333
etc....                etc....