Release candidate 1.8 (#736)

IAMconsortium · Mar 6, 2023 · 4aa433a · 4aa433a
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diff --git a/RELEASE_NOTES.md b/RELEASE_NOTES.md
@@ -1,4 +1,10 @@
-# Next Release
+# Release v1.8.0
+
+## Highlights
+
+- **Performance improvement** at initialization and in internal operations
+- Update the **IIASA-Connection API** in preparation of a new database backend
+- Improve the **tutorials**
 
 ## API changes
 
@@ -9,8 +15,8 @@ IIASA-Connection methods was renamed to `default_only`.
 
 - [#734](https://github.com/IAMconsortium/pyam/pull/734) Validation for illegal column names in `data`
 - [#733](https://github.com/IAMconsortium/pyam/pull/733) Change IIASA-Connection argument to `default_only`
-- [#731](https://github.com/IAMconsortium/pyam/pull/731) Add fast-path to initialization for sufficient multiindex
 - [#732](https://github.com/IAMconsortium/pyam/pull/732) Fix a few typos in tutorials
+- [#731](https://github.com/IAMconsortium/pyam/pull/731) Add fast-path to initialization for sufficient multi-index
 - [#730](https://github.com/IAMconsortium/pyam/pull/730) Refactor initialization code
 - [#729](https://github.com/IAMconsortium/pyam/pull/729) Improve performance at initialization
 - [#723](https://github.com/IAMconsortium/pyam/pull/723) Ensure correct order of `time` attribute

diff --git a/RELEASE_PROCEDURE.md b/RELEASE_PROCEDURE.md
@@ -2,9 +2,11 @@
 
 ## Required accounts and admin privileges
 
-- pip: https://pypi.org/project/pyam-iamc/ and https://test.pypi.org/project/pyam-iamc/
+- pip (automated via GitHub Actions):
+   - https://pypi.org/project/pyam-iamc/ 
+   - https://test.pypi.org/project/pyam-iamc/
 - conda: https://github.com/conda-forge/pyam-feedstock/
-- rtd: https://readthedocs.org/projects/pyam-iamc/
+- ReadTheDocs (automated): https://readthedocs.org/projects/pyam-iamc/
 
 ## Steps for publishing a new release
 

diff --git a/docs/tutorials/transport_tutorial.gdx b/docs/tutorials/transport_tutorial.gdx
diff --git a/pyam/plotting.py b/pyam/plotting.py
@@ -1070,7 +1070,7 @@ def line(
     label = kwargs.pop("label", None)
 
     # plot data, keeping track of which legend labels to apply
-    for col, data in df.iteritems():
+    for col, data in df.items():
         # handle case where columns are not strings or only have 1 dimension
         col = list(map(str, to_list(col)))
         pargs = {}