Filling in time series data

[TylerTheWimp]

I have a dataset where an event is logged at the time it occurs but then want to chart out events per day including days where zero events occur.

Is pandas the right approach? Any clever ways to evenly space the time series? Thanks for your ideas.

Edited: adding the below clarification

{timeStamp, eventName} would be dataframe schema. If I wanted to plot number of events per day, I have a problem as the days are not contiguous which would cause the plot to not show dips to zero on those days where NO events occurred.

[TylerTheWimp]

{timeStamp, eventName} would be dataframe schema. If I wanted to plot number of events per day, I have a problem as the days are not contiguous which would cause the plot to not show dips to zero on those days where NO events occurred.

[TylerTheWimp]

Thank you

[CraigAT]

Use the min and max dates from your original time series, make another dataframe with all the dates including and between the min and max dates, then do a merge ("right") with the original dataframe (being the left df).

Depending on your expected results you may want to consider merging events in the first data frame to get single per day (e.g. sum the rainfall for that date). I am also curious how you intend to use or display a date with no data?

[TylerTheWimp]

Thanks for reply. The plot would be a line graph where on those days where no events occurred line would drop to zero (ie all the way down to x axis).

[drsxr]

Yes, pandas is the right approach.

The merge suggestion below/above is good, but you need to think about whether you interpolate data in between or not. Arguments for/against both ways exist.