PR #420 added
an object IamDataFrame._data to handle timeseries data internally.
This is implemented as a pandas.Series (instead of the previous long-format
pandas.DataFrame) to improve performance.
The previous behaviour with IamDataFrame.data is maintained
via getter and setter functions.
- #424 Add a tutorial reading results from a GAMS model (via a gdx file).
- #420 Add a
_dataobject (implemented as a pandas.Series) to handle timeseries data internally. - #418 Read data from World Bank Open Data Catalogue as IamDataFrame.
- #416 Include
metain new IamDataFrames returned by aggregation functions.
- Add new features for aggregating and downscaling timeseries data.
- Update the plotting library for compatibility with the latest matplotlib release.
- Refactor the feature to read data directly from an IIASA scenario database API.
- Migrate the continuous-integration (CI) infrastructure from Travis & Appveyor to GitHub Actions and use CodeCov.io instead of coveralls.io for test coverage metrics.
PR #413 changed the
return type of pyam.read_iiasa() and pyam.iiasa.Connection.query()
to an IamDataFrame (instead of a pandas.DataFrame)
and loads meta-indicators by default.
Also, the following functions were deprecated for package consistency:
index()replacesscenario_list()for an overview of all scenariosmeta_columns(attribute) replacesavailable_metadata()meta()replacesmetadata()
PR #402 changed the default
behaviour of as_pandas() to include all columns of meta in the returned
dataframe, or only merge columns given by the renamed argument meta_cols.
The feature to discover meta-columns from a dictionary was split out into
a utility function pyam.plotting.mpl_args_to_meta_cols().
- #413 Refactor IIASA-connection-API and rework all related tests.
- #412 Add building the docs to GitHub Actions CI.
- #411 Add feature to pass an explicit weight dataframe to
downscale_region(). - #410 Activate tutorial tests on GitHub Actions CI (py3.8).
- #409 Remove travis and appveyor CI config.
- #408 Update badges on the docs page and readme.
- #407 Add Codecov to Github Actions CI.
- #405 Add ability for recursivley aggregating variables.
- #402 Refactor
as_pandas()and docs for more consistent description ofmeta. - #401 Read credentials for IIASA-API-Connection by default from known location.
- #396 Enable casting to
IamDataFramemultiple times. - #394 Switch CI to Github Actions.
- #393 Import ABC from collections.abc for Python 3.10 compatibility.
- #380 Add compatibility with latest matplotlib and py3.8
- Add feature to aggregate timeseries at sub-annual time resolution
- Refactored the iam-units utility from a submodule to a dependency
- Clean up documentation and dependencies
- #386 Enables unit conversion to apply to strings with "-equiv" in them.
- #384 Add documentation for the pyam.iiasa.Connection class.
- #382 Streamline dependencies and implementation of xlsx-io
- #373 Extends the error message when initializing with duplicate rows.
- #370 Allowed filter to work with np.int64 years and np.datetime64 dates.
- #369
convert_unit()supports GWP conversion of same GHG species without context, lower-case aliases for species symbols. - #361 iam-units refactored from a Git submodule to a Python dependency of pyam.
- #322 Add feature to aggregate timeseries at sub-annual time resolution
- Improved feature for unit conversion using the pint package and the IAMconsortium/units repository, providing out-of-the-box conversion of unit definitions commonly used in integrated assessment research and energy systems modelling; see this tutorial for more information
- Increased support for operations on timeseries data with continuous-time resolution
- New tutorial for working with various input data formats; take a look
- Rewrite and extension of the documentation pages for the API; read the new docs!
PR #341 changed
the API of IamDataFrame.convert_unit() from a dictionary to explicit kwargs
current, to and factor (now optional, using pint if not specified).
PR #334 changed the arguments
of IamDataFrame.interpolate() and pyam.fill_series() to time. It can still
be an integer (i.e., a year).
With PR #337, initializing
an IamDataFrame with n/a entries in columns other than value raises an error.
- #354 Fixes formatting of API parameter docstrings
- #352 Bugfix when using
interpolate()on data with extra columns - #349 Fixes an issue with checking that time columns are equal when appending IamDataFrames
- #348 Extend pages for API docs, clean up docstrings, and harmonize formatting
- #347 Enable contexts and custom UnitRegistry with unit conversion
- #341 Use
pintand IIASA-ene-units repo for unit conversion - #339 Add tutorial for dataframe format io
- #337 IamDataFrame to throw an error when initialized with n/a entries in columns other than
value - #334 Enable interpolate to work on datetimes
This is a patch release to enable compatibility with pandas v1.0.
It also adds experimental support of the frictionless datapackage format.
- #324 Enable compatibility with pandas v1.0
- #323 Support import/export of frictionless
datapackageformat
- New feature: downscale regional timeseries data to subregions using a proxy variable
- Improved features to support aggregation by sectors and regions: support weighted-average, min/max, etc. (including a reworked tutorial)
- Streamlined I/O: include
metatable when reading from/writing to xlsx files - Standardized logger behaviour
PR #305 changed the default
behaviour of aggregate_region() regarding the treatment of components at the
region-level. To keep the previous behaviour, add components=True.
PR #315 changed the return
type of aggregate[_region]() to an IamDataFrame instance.
To keep the previous behaviour, add timeseries().
The object returned by [check_]aggregate[_region]() now includes both the
actual and the expected value as a pd.DataFrame instance.
The function check_internal_consistency() now returns a concatenated dataframe
rather than a dictionary and also includes optional treatment of components
(see paragraph above). To keep the previous behaviour, add components=True.
- #315 Add
equals()feature, change return types of[check_]aggregate[_region](), rework aggregation tutorial - #314 Update IPCC color scheme colors and add SSP-only colors
- #313 Add feature to
downscaletimeseries data to subregions using another variable as proxy - #312 Allow passing list of variables to
aggregatefunctions - #305 Add
methodandweightoptions to the (region) aggregation functions - #302 Rework the tutorials
- #301 Bugfix when using
to_excel()with apd.ExcelWriter - #297 Add
emptyattribute, better error fortimeseries()on empty dataframe - #295 Include
metatable when writing to or reading fromxlsxfiles - #292 Add warning message if
datais empty at initialization (after formatting) - #288 Put
pyamlogger in its own namespace (see here) - #285 Add ability to fetch regions with synonyms from IXMP API
- Streamlined generation of quantitative metadata indicators from timeseries data using
set_meta_from_data() - Better support for accessing public and private IIASA scenario explorer databases via the REST API
- More extensive documentation of the
pyamdata model and the IAMC format - Compatible with recent
pandasv0.25
- #277 Restructure and extend the docs pages, switch to RTD-supported theme
- #275 Completely removes all features related to region plotting, notably
region_plot()andread_shapefile() - #270 Include variables with zeros in
stack_plot(see #266) - #269 Ensure append doesn't accidentally swap indexes
- #268 Update
aggregate_regionso it can find variables below sub-cateogories too - #267 Make clear error message if variable-region pair is missing when
check_aggregate_regionis called - #261 Add a check that
keepinfilter()is a boolean - #254 Hotfix for aggregating missing regions and filtering empty dataframes
- #243 Update
pyam.iiasa.Connectionto support all public and private database connections. DEPRECATED: the argument 'iamc15' has been deprecated in favor of names as queryable directly from the REST API. - #241 Add
set_meta_from_datafeature - #236 Add
swap_time_for_yearmethod and confirm datetime column is compatible with pyam features - #273 Fix several issues accessing IXMP API (passing correct credentials, improve reliability for optional fields in result payload)
- the
filtersargument inIamDataFrame.filter()has been deprecated pd.date_timenow has experimental supported for time-related columns- plots now support the official IPCC scenario color palatte
- native support for putting legends outside of plot axes
- dataframes can now be initialized with default values, making reading raw datasets easier
- #228 Update development environment creation instructions and make pandas requirement more specific
- #219 Add ability to query metadata from iiasa data sources
- #214 Tidy up requirements specifications a little
- #213 Add support for IPCC colors, see the new tutorial "Using IPCC Color Palattes"
- #212 Now natively support reading R-style data frames with year columns like "X2015"
- #207 Add a
aggregate_region()function to sum a variable from subregions and add components that are only defined at the region level - #202 Extend the
df.rename()function with acheck_duplicates (default True)validation option - #201 Added native support for legends outside of plots with
pyam.plotting.OUTSIDE_LEGENDwith a tutorial - #200 Bugfix when providing
cmapandcolorarguments to plotting functions - #199 Initializing an
IamDataFrameaccepts kwargs to fill or create from the data any missing required columns - #198 Update stack plot functionality and add aggregation tutorial. Also adds a
copymethod toIamDataFrame. - #197 Added a
normalizefunction that normalizes all data in a data frame to a specific time period. - #195 Fix filtering for
time,dayandhourto use genericpattern_match()(if such a column exists) in 'year'-formmatted IamDataFrames - #192 Extend
utils.find_depth()to optionally return depth (as list of ints) rather than assert level tests - #190 Add
concat()function - #189 Fix over-zealous
dropna()inscatter() - #186 Fix over-zealous
dropna()inline_plot(), reworkas_pandas()to (optionally) discover meta columns to be joined - #178 Add a kwarg
appendto the functionrename(), change behaviour of mapping to only apply to data where all given columns are matched - #177 Modified formatting of time column on init to allow subclasses to avoid pandas limitation (https://stackoverflow.com/a/37226672)
- #176 Corrected title setting operation in line_plot function
- #175 Update link to tutorial in readme.md
- #174 Add a function
difference()to compare two IamDataFrames - #171 Fix a bug when reading from an
ixmp.TimeSeriesobject, refactor to mitigate circular dependency - #162 Add a function to sum and append timeseries components to an aggregate variable
- #152 Fix bug where scatter plots did not work with property metadata when using two variables (#136, #152)
- #151 Fix bug where excel files were not being written on Windows and MacOSX (#149)
- #145 Support full semantic and VCS-style versioning with
versioneer - #132 support time columns using the
datetimeformat and additionalstrcolumns indata
- #114 extends
append()such that data can be added to existing scenarios - #111 extends
set_meta()such that it requires a name (not None) - #109 add ability to fill between and add data ranges in
line_plot() - #104 fixes a bug with timeseries utils functions, ensures that years are cast as integers
- #101 add function
cross_threshold()to determine years where a timeseries crosses a given threshold - #98 add a module to compute and format summary statistics for timeseries data (wrapper for
pd.describe() - #95 add a
scatter()chart in the plotting library using metadata - #94
set_meta()can take pd.DataFrame (with columns['model', 'scenario']) asindexarg - #93 IamDataFrame can be initilialzed from pd.DataFrame with index
- #92 Adding
$to the pseudo-regexp syntax inpattern_match(), adds override option - #90 Adding a function to
set_panel_label()as part of the plotting library - #88 Adding
check_aggregate_regionsandcheck_internal_consistencyto help with database validation, especially for emissions users - #87 Extending
rename()to work with model and scenario names - #85 Improved functionality for importing metadata and bugfix for filtering for strings if
nanvalues exist in metadata - #83 Extending
filter_by_meta()to work with non-matching indices betweendfand `data - #81 Bug-fix when using
set_meta()with unnamed pd.Series and nonamekwarg - #80 Extend the pseudo-regexp syntax for filtering in
pattern_match() - #73 Adds ability to remove labels for markers, colors, or linestyles
- #72 line_plot now drops NaNs so that lines are fully plotted
- #71 Line plots
legendkeyword can now be a dictionary of legend arguments - #70 Support reading of both SSP and RCP data files downloaded from the IIASA database.
- #66 Fixes a bug in the
interpolate()function (duplication of data points if already defined) - #65 Add a
filter_by_meta()function to filter/join a pd.DataFrame with an IamDataFrame.meta table