Timeseries functions¶
The pyam
package includes several utility functions for working
with timeseries data formatted as pandas.Series
that have
the time dimension as index.
Warning
Not all pyam functions currently support continuoustime formats. Please reach out via our Slack channel, mailing list or GitHub issues if you are not sure whether your use case is supported.
Functions:

Returns a list of the years in which a timeseries crosses a threshold 

Returns the cumulative sum of a timeseries 

Returns the timeseries value at a point in time by linear interpolation 

Compute the annualized growth rate from timeseries data 
 pyam.timeseries.cross_threshold(x, threshold=0, direction=['from above', 'from below'], return_type=<class 'int'>)[source]¶
Returns a list of the years in which a timeseries crosses a threshold
 Parameters:
 x
pandas.Series
A timeseries indexed over years (as integers)
 thresholdfloat, optional
The threshold that the timeseries is checked against
 directionstr, optional
Whether to return all years where the threshold is crossed or only where threshold is crossed in a specific direction
 return_typetype, optional
Whether to cast the returned values to integer (years)
 x
 pyam.timeseries.cumulative(x, first_year, last_year)[source]¶
Returns the cumulative sum of a timeseries
This function implements linear interpolation between years and ignores nan’s in the range. The function includes the lastyear value of the series, and raises a warning if start_year or last_year is outside of the timeseries range and returns nan
 Parameters:
 xpandas.Series
a timeseries to be summed over time
 first_yearint
first year of the sum
 last_yearint
last year of the sum (inclusive)
 pyam.timeseries.fill_series(x, time)[source]¶
Returns the timeseries value at a point in time by linear interpolation
 Parameters:
 xpandas.Series
a timeseries to be interpolated
 timeint or pandas.datetime
year or datetime to interpolate
 pyam.timeseries.growth_rate(x)[source]¶
Compute the annualized growth rate from timeseries data
The annualized growth rate parameter in period t is computed assuming exponential growth based on the changes from period t to period t+1.
 Parameters:
 x
pandas.Series
Timeseries data indexed over the time domain.
 x
 Returns:
 Indexed
pandas.Series
of annualized growth rates
 Indexed
 Raises:
 ValueError
Math domain error when timeseries crosses 0.
See also
pyam.IamComputeAccessor.growth_rate