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doc(changelog): Fixes right arrow and minor bugs, typos.
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CHANGELOG.md

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@@ -42,27 +42,27 @@ Added:
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45-
- `cartopy` >=0.23 → >=0.24
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- `cfgrib` >=0.9.9,<0.9.10 &rarr; >=0.9
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- `dask` >=2024.2,<2024.3 &rarr; >=2025.2
48-
- `eccodes` >=2.27,<2.28 &rarr; >=2.40
49-
- `gdal` >=3.6 &rarr; >=3.10
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- `geopandas` >=0.14 &rarr; >=0.14,<1.0
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- `h5py` >=3.8 &rarr; >=3.12
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- `haversine` >=2.8 &rarr; >=2.9
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- `matplotlib-base` >=3.9 &rarr; >=3.10
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- `netcdf4` >=1.6 &rarr; >=1.7
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- `numba` >=0.60 &rarr; >=0.61
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- `pillow` =9.4 &rarr; =11.1
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- `pyproj` >=3.5 &rarr; >=3.7
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- `pytables` >=3.7 &rarr; >=3.10
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- `python` =3.9 &rarr; =3.11
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- `rasterio` >=1.3 &rarr; >=1.4
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- `scikit-learn` >=1.5 &rarr; >=1.6
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- `scipy` >=1.13 &rarr; >=1.14,<1.15
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- `tqdm` >=4.66 &rarr; >=4.67
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- `xarray` >=2024.6 &rarr; >=2025.1
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- `xlsxwriter` >=3.1 &rarr; >=3.2
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- `cartopy` >=0.23 >=0.24
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- `cfgrib` >=0.9.9,<0.9.10 >=0.9
47+
- `dask` >=2024.2,<2024.3 >=2025.2
48+
- `eccodes` >=2.27,<2.28 >=2.40
49+
- `gdal` >=3.6 >=3.10
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- `geopandas` >=0.14 >=0.14,<1.0
51+
- `h5py` >=3.8 >=3.12
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- `haversine` >=2.8 >=2.9
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- `matplotlib-base` >=3.9 >=3.10
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- `netcdf4` >=1.6 >=1.7
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- `numba` >=0.60 >=0.61
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- `pillow` =9.4 =11.1
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- `pyproj` >=3.5 >=3.7
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- `pytables` >=3.7 >=3.10
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- `python` =3.9 =3.11
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- `rasterio` >=1.3 >=1.4
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- `scikit-learn` >=1.5 >=1.6
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- `scipy` >=1.13 >=1.14,<1.15
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- `tqdm` >=4.66 >=4.67
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- `xarray` >=2024.6 >=2025.1
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- `xlsxwriter` >=3.1 >=3.2
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@@ -73,7 +73,7 @@ Removed:
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- `climada.hazard.tc_tracks.TCTracks.subset_years` function [#1023](https://github.com/CLIMADA-project/climada_python/pull/1023)
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- `climada.hazard.tc_tracks.TCTracks.from_FAST` function, add Australia basin (AU) [#993](https://github.com/CLIMADA-project/climada_python/pull/993)
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- Add `osm-flex` package to CLIMADA core [#981](https://github.com/CLIMADA-project/climada_python/pull/981)
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- `doc.tutorial.climada_entity_Exposures_osm.ipynb` tutorial explaining how to use `osm-flex`with CLIMADA
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- `doc.tutorial.climada_entity_Exposures_osm.ipynb` tutorial explaining how to use `osm-flex` with CLIMADA
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- `climada.util.coordinates.bounding_box_global` function [#980](https://github.com/CLIMADA-project/climada_python/pull/980)
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- `climada.util.coordinates.bounding_box_from_countries` function [#980](https://github.com/CLIMADA-project/climada_python/pull/980)
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- `climada.util.coordinates.bounding_box_from_cardinal_bounds` function [#980](https://github.com/CLIMADA-project/climada_python/pull/980)
@@ -105,8 +105,8 @@ Removed:
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- the _geometry_ column of the inherent `GeoDataFrame` is set up at initialization
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- latitude and longitude column are no longer present there (the according arrays can be retrieved as properties of the Exposures object: `exp.latitude` instead of `exp.gdf.latitude.values`).
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- `Exposures.gdf` has been renamed to `Exposures.data` (it still works though, as it is a property now pointing to the latter)
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- the `check` method does not add a default "IMPF_" column to the GeoDataFrame anymore
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- Updated IBTrACS version from v4.0 to v4.1 ([#976](https://github.com/CLIMADA-project/climada_python/pull/976)
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- the `check` method does not add a default `'IMPF_'` column to the GeoDataFrame anymore
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- Updated IBTrACS version from v4.0 to v4.1 [#976](https://github.com/CLIMADA-project/climada_python/pull/976)
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- Fix xarray future warning in TCTracks for .dims to .sizes
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- Fix hazard.concatenate type test for pathos pools
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@@ -140,20 +140,20 @@ Added:
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- `bottleneck` >=1.3 &rarr; >=1.4
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- `cartopy` >=0.22 &rarr; >=0.23
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- `contextily` >=1.5 &rarr; >=1.6
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- `dask` >=2024.1,<2024.3 &rarr; >=2024.2,<2024.3
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- `matplotlib-base` >=3.8 &rarr; >=3.9
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- `numba` >=0.59 &rarr; >=0.60
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- `numexpr` >=2.9 &rarr; >=2.10
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- `pint` >=0.23 &rarr; >=0.24
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- `pycountry` >=22.3 &rarr; >=24.6
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- `requests` >=2.31 &rarr; >=2.32
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- `salib` >=1.4 &rarr; >=1.5
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- `scikit-learn` >=1.4 &rarr; >=1.5
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- `scipy` >=1.12 &rarr; >=1.13
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- `xarray` >=2024.2 &rarr; >=2024.6
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- `bottleneck` >=1.3 >=1.4
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- `cartopy` >=0.22 >=0.23
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- `contextily` >=1.5 >=1.6
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- `dask` >=2024.1,<2024.3 >=2024.2,<2024.3
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- `matplotlib-base` >=3.8 >=3.9
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- `numba` >=0.59 >=0.60
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- `numexpr` >=2.9 >=2.10
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- `pint` >=0.23 >=0.24
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- `pycountry` >=22.3 >=24.6
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- `requests` >=2.31 >=2.32
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- `salib` >=1.4 >=1.5
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- `scikit-learn` >=1.4 >=1.5
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- `scipy` >=1.12 >=1.13
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- `xarray` >=2024.2 >=2024.6
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### Added
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- `contextily` >=1.3 &rarr; >=1.5
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- `dask` >=2023 &rarr; >=2024
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- `numba` >=0.57 &rarr; >=0.59
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- `pandas` >=2.1 &rarr; >=2.1,<2.2
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- `pint` >=0.22 &rarr; >=0.23
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- `scikit-learn` >=1.3 &rarr; >=1.4
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- `scipy` >=1.11 &rarr; >=1.12
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- `sparse` >=0.14 &rarr; >=0.15
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- `xarray` >=2023.8 &rarr; >=2024.1
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- `overpy` =0.6 &rarr; =0.7
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- `peewee` =3.16.3 &rarr; =3.17.1
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- `contextily` >=1.3 >=1.5
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- `dask` >=2023 >=2024
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- `numba` >=0.57 >=0.59
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- `pandas` >=2.1 >=2.1,<2.2
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- `pint` >=0.22 >=0.23
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- `scikit-learn` >=1.3 >=1.4
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- `scipy` >=1.11 >=1.12
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- `sparse` >=0.14 >=0.15
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- `xarray` >=2023.8 >=2024.1
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- `overpy` =0.6 =0.7
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- `peewee` =3.16.3 =3.17.1
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@@ -311,13 +311,13 @@ Release date: 2023-09-27
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- `matplotlib-base` None &rarr; >=3.8
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- `matplotlib-base` None >=3.8
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- `geopandas` >=0.13 &rarr; >=0.14
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- `pandas` >=1.5,<2.0 &rarr; >=2.1
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- `salib` >=1.3.0 &rarr; >=1.4.7
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- `geopandas` >=0.13 >=0.14
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- `pandas` >=1.5,<2.0 >=2.1
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- `salib` >=1.3.0 >=1.4.7
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- `cartopy` >=0.20.0,<0.20.3 &rarr; >=0.21
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- `cfgrib` >=0.9.7,<0.9.10 &rarr; =0.9.9
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- `contextily` >=1.0 &rarr; >=1.3
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- `dask` >=2.25 &rarr; >=2023
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- `eccodes` [auto] &rarr; =2.27
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- `gdal` !=3.4.1 &rarr; >=3.6
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- `geopandas` >=0.8 &rarr; >=0.13
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- `h5py` >=2.10 &rarr; >=3.8
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- `haversine` >=2.3 &rarr; >=2.8
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- `matplotlib` >=3.2,< 3.6 &rarr; >=3.7
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- `netcdf4` >=1.5 &rarr; >=1.6
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- `numba` >=0.51,!=0.55.0 &rarr; >=0.57
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- `openpyxl` >=3.0 &rarr; >=3.1
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- `pandas-datareader` >=0.9 &rarr; >=0.10
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- `pathos` >=0.2 &rarr; >=0.3
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- `pint` >=0.15 &rarr; >=0.22
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- `proj` !=9.0.0 &rarr; >=9.1
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- `pycountry` >=20.7 &rarr; >=22.3
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- `pytables` >=3.6 &rarr; >=3.7
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- `rasterio` >=1.2.7,<1.3 &rarr; >=1.3
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- `requests` >=2.24 &rarr; >=2.31
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- `salib` >=1.3.0 &rarr; >=1.4
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- `scikit-learn` >=1.0 &rarr; >=1.2
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- `scipy` >=1.6 &rarr; >=1.10
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- `sparse` >=0.13 &rarr; >=0.14
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- `statsmodels` >=0.11 &rarr; >=0.14
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- `tabulate` >=0.8 &rarr; >=0.9
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- `tqdm` >=4.48 &rarr; >=4.65
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- `xarray` >=0.13 &rarr; >=2023.5
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- `xlrd` >=1.2 &rarr; >=2.0
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- `xlsxwriter` >=1.3 &rarr; >=3.1
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- `cartopy` >=0.20.0,<0.20.3 >=0.21
350+
- `cfgrib` >=0.9.7,<0.9.10 =0.9.9
351+
- `contextily` >=1.0 >=1.3
352+
- `dask` >=2.25 >=2023
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- `eccodes` [auto] =2.27
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- `gdal` !=3.4.1 >=3.6
355+
- `geopandas` >=0.8 >=0.13
356+
- `h5py` >=2.10 >=3.8
357+
- `haversine` >=2.3 >=2.8
358+
- `matplotlib` >=3.2,< 3.6 >=3.7
359+
- `netcdf4` >=1.5 >=1.6
360+
- `numba` >=0.51,!=0.55.0 >=0.57
361+
- `openpyxl` >=3.0 >=3.1
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- `pandas-datareader` >=0.9 >=0.10
363+
- `pathos` >=0.2 >=0.3
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- `pint` >=0.15 >=0.22
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- `proj` !=9.0.0 >=9.1
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- `pycountry` >=20.7 >=22.3
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- `pytables` >=3.6 >=3.7
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- `rasterio` >=1.2.7,<1.3 >=1.3
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- `requests` >=2.24 >=2.31
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- `salib` >=1.3.0 >=1.4
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- `scikit-learn` >=1.0 >=1.2
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- `scipy` >=1.6 >=1.10
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- `sparse` >=0.13 >=0.14
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- `statsmodels` >=0.11 >=0.14
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- `tabulate` >=0.8 >=0.9
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- `tqdm` >=4.48 >=4.65
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- `xarray` >=0.13 >=2023.5
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- `xlrd` >=1.2 >=2.0
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- `xlsxwriter` >=1.3 >=3.1
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