General functions

pyam.concat(objs, ignore_meta_conflict=False, **kwargs)

Concatenate a series of IamDataFrame-like objects

Parameters:

objsiterable of IamDataFrames

A list of objects castable to IamDataFrame

ignore_meta_conflictbool, optional

If False, raise an error if any meta columns present in dfs are not identical. If True, values in earlier elements of dfs take precedence.

**kwargs

Passed to IamDataFrame(other, **kwargs) for any item of dfs which isn’t already an IamDataFrame.

Returns:

IamDataFrame

Raises:

TypeError

If dfs is not a list.

ValueError

If time domain or other timeseries data index dimension don’t match.

Notes

The meta attributes are merged only for those objects of objs that are passed as IamDataFrame instances.

The dimensions and index names of all elements of dfs must be identical. The returned IamDataFrame inherits the dimensions and index names.

pyam.compare(left, right, left_label='left', right_label='right', drop_close=True, **kwargs)

Compare the data in two IamDataFrames and return a pandas.DataFrame

Parameters:

left, rightIamDataFrames

Two IamDataFrame instances to be compared

left_label, right_labelstr, optional

Column names of the returned pandas.DataFrame

drop_closebool, optional

Remove all data where left and right are close

**kwargsarguments for comparison of values

Passed to numpy.isclose()

pyam.require_variable(*args, **kwargs)

This method is deprecated, use IamDataFrame.require_data() instead.

pyam.validate(df, criteria={}, exclude_on_fail=False, **kwargs)

This method is deprecated, use IamDataFrame.validate() instead.

pyam.categorize(df, name, value, criteria, color=None, marker=None, linestyle=None, **kwargs)

This method is deprecated, use IamDataFrame.categorize() instead.

pyam.check_aggregate(df, variable, components=None, exclude_on_fail=False, multiplier=1, **kwargs)

Check whether the timeseries values match the aggregation of sub-categories

Parameters:

dfIamDataFrame

**kwargs

Passed to IamDataFrame.filter()