Timeseries data charts

Read in tutorial data and show a summary

This gallery uses the scenario data from the first-steps tutorial.

If you haven’t cloned the pyam GitHub repository to your machine, you can download the file from https://github.com/IAMconsortium/pyam/tree/main/docs/tutorials.

Make sure to place the data file in the same folder as this script/notebook.

import pyam

df = pyam.IamDataFrame("tutorial_data.csv")
df

<class 'pyam.core.IamDataFrame'>
Index:
 * model    : AIM/CGE 2.1, GENeSYS-MOD 1.0, ... WITCH-GLOBIOM 4.4 (8)
 * scenario : 1.0, CD-LINKS_INDCi, CD-LINKS_NPi, ... Faster Transition Scenario (8)
Timeseries data coordinates:
   region   : R5ASIA, R5LAM, R5MAF, R5OECD90+EU, R5REF, R5ROWO, World (7)
   variable : ... (6)
   unit     : EJ/yr, Mt CO2/yr, °C (3)
   year     : 2010, 2020, 2030, 2040, 2050, 2060, 2070, 2080, ... 2100 (10)

A simple line chart

We show a simple line chart of the regional components of CO2 emissions for one scenario.

Then, also show the data as a wide IAMC-style dataframe.

model, scenario = "REMIND-MAgPIE 1.7-3.0", "CD-LINKS_INDCi"

data = df.filter(model=model, scenario=scenario, variable="Emissions|CO2").filter(
    region="World", keep=False
)

data.plot(color="region", title="CO2 emissions by region")
data.timeseries()

					2010	2020	2030	2040	2050	2060	2070	2080	2090	2100
model	scenario	region	variable	unit
REMIND-MAgPIE 1.7-3.0	CD-LINKS_INDCi	R5ASIA	Emissions|CO2	Mt CO2/yr	13319.0940	17953.8288	18860.5696	20919.9611	21346.1127	20797.3295	20655.9721	20852.5609	19611.0956	18684.4507
		R5LAM	Emissions|CO2	Mt CO2/yr	3841.7418	4100.6996	3293.7924	2044.4228	2348.7068	2546.6130	2466.7808	2357.3265	2160.2127	1898.8835
		R5MAF	Emissions|CO2	Mt CO2/yr	3338.4200	5794.1257	7223.7294	8619.6929	10859.7901	12689.7547	13635.7874	14349.2884	14149.6996	13582.5528
		R5OECD90+EU	Emissions|CO2	Mt CO2/yr	13425.7405	11886.5214	9499.4507	8374.9951	7484.1184	6456.2150	5624.2110	5243.8898	4656.6352	4315.5721
		R5REF	Emissions|CO2	Mt CO2/yr	1437.8754	1692.1186	1856.6008	1959.4409	2085.8475	2021.2251	1720.9301	1374.2122	1067.1381	894.9409