Tutorials¶
Jupyter notebooks¶
All tutorials currently use the IAMC template for yearly data,
but pyam
also supports timeseries data with a sub-annual resolution.
Please read the Data Model section for more information.
The source code is available in the folder
docs/tutorials of the pyam
GitHub repository.
- First steps with the pyam package
- Importing various data table formats
- Performing unit conversions
- Algebraic operations on timeseries data
- Working with Percentiles (and Quantiles) of Distributions
- Query data from the IIASA database infrastructure
- Read directly from the UNFCCC Data Inventory
- Importing results from a GAMS model to an IamDataFrame
- Aggregating and downscaling timeseries data
- Aggregating subannual timeseries data
- Using IPCC Color Palettes
- Customizing legends
- Plotting aggregate variables
- Make our Logo!
Workshops and recordings¶
The Energy, Climate and Environment program (ECE) at IIASA is regularly holding workshops and trainings for the pyam package. You can find recordings of these workshops and related material at https://teaching.ece.iiasa.ac.at/pyam.html.