How to split a Series into time intervals? (python)

Question

I have this dataframe:

And I should split the rows of the ''Time.s'' column into intervals, calculate the average of each interval, and finally the deviation of each average.

I can't split the lines that have Volt.mv > 0.95 into a group for each second. I tried with GroupBy, but it creates problems with the second table:

I used this code, calculating the average directly, but I certainly did something wrong:

ecg.groupby("Time.s").apply(lambda x: x["Volt.mv"].mean())

Can anyone help me?

Answer 1

Before doing the groupby, you need to map Time.s to an interval. Otherwise each group will have only a single row (most of the time).

Here is how to group into intervals of 0.1 seconds and compute the mean and standard deviation for each interval:

interval_length = 0.1
df_aggregated = (
    df
    .assign(interval=df["Time.s"].div(interval_length).astype("int").mul(interval_length))
    .groupby("interval")
    .agg(volt_mean=("Volt.mv", "mean"), volt_std=("Volt.mv", "std"))
)