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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
[](https://travis-ci.org/altair-viz/vega_datasets)
[](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Abuild)
[](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Alint)
[](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
[](https://travis-ci.org/altair-viz/vega_datasets)
[](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Abuild)
[](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Alint)
[](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
[](https://travis-ci.org/altair-viz/vega_datasets)
[](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Abuild)
[](https://github.com/altair-viz/vega_datasets/actions?query=workflow%3Alint)
[](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
|
