geo pandas upgrade (#1084)

* un-restrict pandas and geopandas max version

* fix deprecation failure

* avoid failure by inaccuracy
(requires root cause investigation before PR is merged)

* update changelog

Author: emanuel-schmid

CHANGELOG.md

@@ -10,20 +10,29 @@ Code freeze date: YYYY-MM-DD
 
 ### Dependency Changes
 
+Added:
+
+- `fiona` >=1.10
+
+Updated:
+
+- `geopandas` >=0.14,<1.0 → >=0.14
+- `pandas` >=2.1,<2.2 → >=2.1
+
 Removed:
 
 - `pandas-datareader`
-- `intensity_thres` of `Hazard`, `StormEurope`, and `TropCyclones` object [#1065](https://github.com/CLIMADA-project/climada_python/pull/1065)
-- Deprecated method `climada.hazard.trop_cyclone.trop_cyclone.TropCyclone.set_from_tracks` [#1065](https://github.com/CLIMADA-project/climada_python/pull/1065)
 
 ### Added
+
 - Added optional parameter to `geo_im_from_array`, `plot_from_gdf`, `plot_rp_imp`, `plot_rp_intensity`,
 `plot_intensity`, `plot_fraction`, `_event_plot` to mask plotting when regions are too far from data points [#1047](https://github.com/CLIMADA-project/climada_python/pull/1047). To recreate previous plots (no masking), the parameter can be set to None.
 - Added instructions to install Climada petals on Euler cluster in `doc.guide.Guide_Euler.ipynb` [#1029](https://github.com/CLIMADA-project/climada_python/pull/1029)
 
 - `ImpactFunc` and `ImpactFuncSet` now support equality comparisons via `==` [#1027](https://github.com/CLIMADA-project/climada_python/pull/1027)
 
 ### Changed
+
 - Changed the default mask_distance in `util.plot.geo_im_from_array` to 0.03 to avoid white gaps in gridded hazard data with comparably low resolution (>80 centroids per axis) [#1073](https://github.com/CLIMADA-project/climada_python/pull/1073)
 - Increased speed of `util.plot.add_shapes` by avoiding for loops, substantially speeding up `Hazard.plot_intensity` and other functions. [#1073](https://github.com/CLIMADA-project/climada_python/pull/1073)
 - `Hazard.local_exceedance_intensity`, `Hazard.local_return_period` and `Impact.local_exceedance_impact`, `Impact.local_return_period`, using the `climada.util.interpolation` module: New default (no binning), binning on decimals, and faster implementation [#1012](https://github.com/CLIMADA-project/climada_python/pull/1012)
@@ -41,6 +50,8 @@ Removed:
 ### Removed
 
 - `climada.util.interpolation.round_to_sig_digits` [#1012](https://github.com/CLIMADA-project/climada_python/pull/1012)
+- `intensity_thres` of `Hazard`, `StormEurope`, and `TropCyclones` object [#1065](https://github.com/CLIMADA-project/climada_python/pull/1065)
+- Deprecated method `climada.hazard.trop_cyclone.trop_cyclone.TropCyclone.set_from_tracks` [#1065](https://github.com/CLIMADA-project/climada_python/pull/1065)
 
 ## 6.0.1
 

climada/engine/impact_data.py

@@ -774,7 +774,7 @@ def clean_emdat_df(
         df_data["Start Day"] = np.array(day_list, dtype="int")
         df_data["Start Year"] = np.array(year_list, dtype="int")
         for var in ["Disaster Subtype", "Disaster Type", "Country"]:
-            df_data[VARNAMES_EMDAT[target_version][var]].fillna("None", inplace=True)
+            df_data.fillna({VARNAMES_EMDAT[target_version][var]: "None"}, inplace=True)
 
     # (3) Filter by countries, year range, and disaster type
     # (3.1) Countries:

requirements/env_climada.yml

@@ -9,8 +9,9 @@ dependencies:
   - contextily>=1.6
   - dask>=2025.2
   - eccodes>=2.40
+  - fiona>=1.10
   - gdal>=3.10
-  - geopandas>=0.14,<1.0  # geopandas 1.0 does not depend on fiona anymore, hence fiona would need to be added as dependency
+  - geopandas>=0.14
   - h5py>=3.12
   - haversine>=2.9
   - matplotlib-base>=3.10
@@ -19,7 +20,7 @@ dependencies:
   - numexpr>=2.10
   - openpyxl>=3.1
   - osm-flex>=1.1
-  - pandas>=2.1,<2.2  # 2.2 is not compatible with the default pytables=3.7 and yields a very high deprecation warning number through geopandas
+  - pandas>=2.1
   - pathos>=0.3
   - pint>=0.24
   - pip