automatic import of python-vega-datasets

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diff --git a/.gitignore b/.gitignore
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--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/vega_datasets-0.9.0.tar.gz
diff --git a/python-vega-datasets.spec b/python-vega-datasets.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-vega-datasets
+Version:	0.9.0
+Release:	1
+Summary:	A Python package for offline access to Vega datasets
+License:	MIT
+URL:		http://github.com/altair-viz/vega_datasets
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/8f/a0/ce608d9a5b82fce2ebaa2311136b1e1d1dc2807f501bbdfa56bd174fff76/vega_datasets-0.9.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-pandas
+
+%description
+# vega_datasets
+
+[![build status](http://img.shields.io/travis/altair-viz/vega_datasets/master.svg?style=flat)](https://travis-ci.org/altair-viz/vega_datasets)
+[![github actions](https://github.com/altair-viz/vega_datasets/workflows/build/badge.svg)](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Abuild)
+[![github actions](https://github.com/altair-viz/vega_datasets/workflows/lint/badge.svg)](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Alint)
+[![code style black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
+A Python package for offline access to [vega datasets](https://github.com/vega/vega-datasets).
+
+This package has several goals:
+
+- Provide straightforward access in Python to the datasets made available at [vega-datasets](https://github.com/vega/vega-datasets).
+- return the results in the form of a Pandas dataframe.
+- wherever dataset size and/or license constraints make it possible, bundle the dataset with the package so that datasets can be loaded in the absence of a web connection.
+
+Currently the package bundles a half-dozen datasets, and falls back to using HTTP requests for the others.
+
+## Installation
+``vega_datasets`` is compatible with Python 3.5 or newer. Install with:
+```
+$ pip install vega_datasets
+```
+
+## Usage
+
+The main object in this library is ``data``:
+
+```python
+>>> from vega_datasets import data
+```
+
+It contains attributes that access all available datasets, locally if
+available. For example, here is the well-known iris dataset:
+
+```python
+>>> df = data.iris()
+>>> df.head()
+   petalLength  petalWidth  sepalLength  sepalWidth species
+0          1.4         0.2          5.1         3.5  setosa
+1          1.4         0.2          4.9         3.0  setosa
+2          1.3         0.2          4.7         3.2  setosa
+3          1.5         0.2          4.6         3.1  setosa
+4          1.4         0.2          5.0         3.6  setosa
+```
+
+If you're curious about the source data, you can access the URL for any of the available datasets:
+
+```python
+>>> data.iris.url
+'https://cdn.jsdelivr.net/npm/vega-datasets@v1.29.0/data/iris.json'
+```
+
+For datasets bundled with the package, you can also find their location on disk:
+
+```python
+>>> data.iris.filepath
+'/lib/python3.6/site-packages/vega_datasets/data/iris.json'
+```
+
+## Available Datasets
+
+To list all the available datsets, use ``list_datasets``:
+
+```python
+>>> data.list_datasets()
+['7zip', 'airports', 'anscombe', 'barley', 'birdstrikes', 'budget', 'budgets', 'burtin', 'cars', 'climate', 'co2-concentration', 'countries', 'crimea', 'disasters', 'driving', 'earthquakes', 'ffox', 'flare', 'flare-dependencies', 'flights-10k', 'flights-200k', 'flights-20k', 'flights-2k', 'flights-3m', 'flights-5k', 'flights-airport', 'gapminder', 'gapminder-health-income', 'gimp', 'github', 'graticule', 'income', 'iris', 'jobs', 'londonBoroughs', 'londonCentroids', 'londonTubeLines', 'lookup_groups', 'lookup_people', 'miserables', 'monarchs', 'movies', 'normal-2d', 'obesity', 'points', 'population', 'population_engineers_hurricanes', 'seattle-temps', 'seattle-weather', 'sf-temps', 'sp500', 'stocks', 'udistrict', 'unemployment', 'unemployment-across-industries', 'us-10m', 'us-employment', 'us-state-capitals', 'weather', 'weball26', 'wheat', 'world-110m', 'zipcodes']
+```
+
+To list local datasets (i.e. those that are bundled with the package and can be used without a web connection), use the ``local_data`` object instead:
+
+```python
+>>> from vega_datasets import local_data
+>>> local_data.list_datasets()
+
+['airports', 'anscombe', 'barley', 'burtin', 'cars', 'crimea', 'driving', 'iowa-electricity', 'iris', 'seattle-temps', 'seattle-weather', 'sf-temps', 'stocks', 'us-employment', "wheat"]
+```
+
+We plan to add more local datasets in the future, subject to size and licensing constraints. See the [local datasets issue](https://github.com/altair-viz/vega_datasets/issues/1) if you would like to help with this.
+
+## Dataset Information
+
+If you want more information about any dataset, you can use the ``description`` property:
+
+```python
+>>> data.iris.description
+'This classic dataset contains lengths and widths of petals and sepals for 150 iris flowers, drawn from three species. It was introduced by R.A. Fisher in 1936 [1]_.'
+```
+
+This information is also part of the ``data.iris`` doc string.
+Descriptions are not yet included for all the datasets in the package; we hope to add more information on this in the future.
+
+
+
+
+%package -n python3-vega-datasets
+Summary:	A Python package for offline access to Vega datasets
+Provides:	python-vega-datasets
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-vega-datasets
+# vega_datasets
+
+[![build status](http://img.shields.io/travis/altair-viz/vega_datasets/master.svg?style=flat)](https://travis-ci.org/altair-viz/vega_datasets)
+[![github actions](https://github.com/altair-viz/vega_datasets/workflows/build/badge.svg)](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Abuild)
+[![github actions](https://github.com/altair-viz/vega_datasets/workflows/lint/badge.svg)](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Alint)
+[![code style black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
+A Python package for offline access to [vega datasets](https://github.com/vega/vega-datasets).
+
+This package has several goals:
+
+- Provide straightforward access in Python to the datasets made available at [vega-datasets](https://github.com/vega/vega-datasets).
+- return the results in the form of a Pandas dataframe.
+- wherever dataset size and/or license constraints make it possible, bundle the dataset with the package so that datasets can be loaded in the absence of a web connection.
+
+Currently the package bundles a half-dozen datasets, and falls back to using HTTP requests for the others.
+
+## Installation
+``vega_datasets`` is compatible with Python 3.5 or newer. Install with:
+```
+$ pip install vega_datasets
+```
+
+## Usage
+
+The main object in this library is ``data``:
+
+```python
+>>> from vega_datasets import data
+```
+
+It contains attributes that access all available datasets, locally if
+available. For example, here is the well-known iris dataset:
+
+```python
+>>> df = data.iris()
+>>> df.head()
+   petalLength  petalWidth  sepalLength  sepalWidth species
+0          1.4         0.2          5.1         3.5  setosa
+1          1.4         0.2          4.9         3.0  setosa
+2          1.3         0.2          4.7         3.2  setosa
+3          1.5         0.2          4.6         3.1  setosa
+4          1.4         0.2          5.0         3.6  setosa
+```
+
+If you're curious about the source data, you can access the URL for any of the available datasets:
+
+```python
+>>> data.iris.url
+'https://cdn.jsdelivr.net/npm/vega-datasets@v1.29.0/data/iris.json'
+```
+
+For datasets bundled with the package, you can also find their location on disk:
+
+```python
+>>> data.iris.filepath
+'/lib/python3.6/site-packages/vega_datasets/data/iris.json'
+```
+
+## Available Datasets
+
+To list all the available datsets, use ``list_datasets``:
+
+```python
+>>> data.list_datasets()
+['7zip', 'airports', 'anscombe', 'barley', 'birdstrikes', 'budget', 'budgets', 'burtin', 'cars', 'climate', 'co2-concentration', 'countries', 'crimea', 'disasters', 'driving', 'earthquakes', 'ffox', 'flare', 'flare-dependencies', 'flights-10k', 'flights-200k', 'flights-20k', 'flights-2k', 'flights-3m', 'flights-5k', 'flights-airport', 'gapminder', 'gapminder-health-income', 'gimp', 'github', 'graticule', 'income', 'iris', 'jobs', 'londonBoroughs', 'londonCentroids', 'londonTubeLines', 'lookup_groups', 'lookup_people', 'miserables', 'monarchs', 'movies', 'normal-2d', 'obesity', 'points', 'population', 'population_engineers_hurricanes', 'seattle-temps', 'seattle-weather', 'sf-temps', 'sp500', 'stocks', 'udistrict', 'unemployment', 'unemployment-across-industries', 'us-10m', 'us-employment', 'us-state-capitals', 'weather', 'weball26', 'wheat', 'world-110m', 'zipcodes']
+```
+
+To list local datasets (i.e. those that are bundled with the package and can be used without a web connection), use the ``local_data`` object instead:
+
+```python
+>>> from vega_datasets import local_data
+>>> local_data.list_datasets()
+
+['airports', 'anscombe', 'barley', 'burtin', 'cars', 'crimea', 'driving', 'iowa-electricity', 'iris', 'seattle-temps', 'seattle-weather', 'sf-temps', 'stocks', 'us-employment', "wheat"]
+```
+
+We plan to add more local datasets in the future, subject to size and licensing constraints. See the [local datasets issue](https://github.com/altair-viz/vega_datasets/issues/1) if you would like to help with this.
+
+## Dataset Information
+
+If you want more information about any dataset, you can use the ``description`` property:
+
+```python
+>>> data.iris.description
+'This classic dataset contains lengths and widths of petals and sepals for 150 iris flowers, drawn from three species. It was introduced by R.A. Fisher in 1936 [1]_.'
+```
+
+This information is also part of the ``data.iris`` doc string.
+Descriptions are not yet included for all the datasets in the package; we hope to add more information on this in the future.
+
+
+
+
+%package help
+Summary:	Development documents and examples for vega-datasets
+Provides:	python3-vega-datasets-doc
+%description help
+# vega_datasets
+
+[![build status](http://img.shields.io/travis/altair-viz/vega_datasets/master.svg?style=flat)](https://travis-ci.org/altair-viz/vega_datasets)
+[![github actions](https://github.com/altair-viz/vega_datasets/workflows/build/badge.svg)](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Abuild)
+[![github actions](https://github.com/altair-viz/vega_datasets/workflows/lint/badge.svg)](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Alint)
+[![code style black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
+A Python package for offline access to [vega datasets](https://github.com/vega/vega-datasets).
+
+This package has several goals:
+
+- Provide straightforward access in Python to the datasets made available at [vega-datasets](https://github.com/vega/vega-datasets).
+- return the results in the form of a Pandas dataframe.
+- wherever dataset size and/or license constraints make it possible, bundle the dataset with the package so that datasets can be loaded in the absence of a web connection.
+
+Currently the package bundles a half-dozen datasets, and falls back to using HTTP requests for the others.
+
+## Installation
+``vega_datasets`` is compatible with Python 3.5 or newer. Install with:
+```
+$ pip install vega_datasets
+```
+
+## Usage
+
+The main object in this library is ``data``:
+
+```python
+>>> from vega_datasets import data
+```
+
+It contains attributes that access all available datasets, locally if
+available. For example, here is the well-known iris dataset:
+
+```python
+>>> df = data.iris()
+>>> df.head()
+   petalLength  petalWidth  sepalLength  sepalWidth species
+0          1.4         0.2          5.1         3.5  setosa
+1          1.4         0.2          4.9         3.0  setosa
+2          1.3         0.2          4.7         3.2  setosa
+3          1.5         0.2          4.6         3.1  setosa
+4          1.4         0.2          5.0         3.6  setosa
+```
+
+If you're curious about the source data, you can access the URL for any of the available datasets:
+
+```python
+>>> data.iris.url
+'https://cdn.jsdelivr.net/npm/vega-datasets@v1.29.0/data/iris.json'
+```
+
+For datasets bundled with the package, you can also find their location on disk:
+
+```python
+>>> data.iris.filepath
+'/lib/python3.6/site-packages/vega_datasets/data/iris.json'
+```
+
+## Available Datasets
+
+To list all the available datsets, use ``list_datasets``:
+
+```python
+>>> data.list_datasets()
+['7zip', 'airports', 'anscombe', 'barley', 'birdstrikes', 'budget', 'budgets', 'burtin', 'cars', 'climate', 'co2-concentration', 'countries', 'crimea', 'disasters', 'driving', 'earthquakes', 'ffox', 'flare', 'flare-dependencies', 'flights-10k', 'flights-200k', 'flights-20k', 'flights-2k', 'flights-3m', 'flights-5k', 'flights-airport', 'gapminder', 'gapminder-health-income', 'gimp', 'github', 'graticule', 'income', 'iris', 'jobs', 'londonBoroughs', 'londonCentroids', 'londonTubeLines', 'lookup_groups', 'lookup_people', 'miserables', 'monarchs', 'movies', 'normal-2d', 'obesity', 'points', 'population', 'population_engineers_hurricanes', 'seattle-temps', 'seattle-weather', 'sf-temps', 'sp500', 'stocks', 'udistrict', 'unemployment', 'unemployment-across-industries', 'us-10m', 'us-employment', 'us-state-capitals', 'weather', 'weball26', 'wheat', 'world-110m', 'zipcodes']
+```
+
+To list local datasets (i.e. those that are bundled with the package and can be used without a web connection), use the ``local_data`` object instead:
+
+```python
+>>> from vega_datasets import local_data
+>>> local_data.list_datasets()
+
+['airports', 'anscombe', 'barley', 'burtin', 'cars', 'crimea', 'driving', 'iowa-electricity', 'iris', 'seattle-temps', 'seattle-weather', 'sf-temps', 'stocks', 'us-employment', "wheat"]
+```
+
+We plan to add more local datasets in the future, subject to size and licensing constraints. See the [local datasets issue](https://github.com/altair-viz/vega_datasets/issues/1) if you would like to help with this.
+
+## Dataset Information
+
+If you want more information about any dataset, you can use the ``description`` property:
+
+```python
+>>> data.iris.description
+'This classic dataset contains lengths and widths of petals and sepals for 150 iris flowers, drawn from three species. It was introduced by R.A. Fisher in 1936 [1]_.'
+```
+
+This information is also part of the ``data.iris`` doc string.
+Descriptions are not yet included for all the datasets in the package; we hope to add more information on this in the future.
+
+
+
+
+%prep
+%autosetup -n vega-datasets-0.9.0
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-vega-datasets -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.9.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..6abd3f2
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+5a17b42f507880037f9b7040b75d2e19  vega_datasets-0.9.0.tar.gz