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Ayxan
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pip
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.venv/Lib/site-packages/altair-4.2.0.dist-info/LICENSE
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.venv/Lib/site-packages/altair-4.2.0.dist-info/LICENSE
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Copyright (c) 2015, Brian E. Granger and Jake Vanderplas
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All rights reserved.
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||||
|
||||
Redistribution and use in source and binary forms, with or without
|
||||
modification, are permitted provided that the following conditions are met:
|
||||
|
||||
* Redistributions of source code must retain the above copyright notice, this
|
||||
list of conditions and the following disclaimer.
|
||||
|
||||
* Redistributions in binary form must reproduce the above copyright notice,
|
||||
this list of conditions and the following disclaimer in the documentation
|
||||
and/or other materials provided with the distribution.
|
||||
|
||||
* Neither the name of altair nor the names of its
|
||||
contributors may be used to endorse or promote products derived from
|
||||
this software without specific prior written permission.
|
||||
|
||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
||||
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
||||
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
|
||||
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
|
||||
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
|
||||
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
|
||||
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
|
||||
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
||||
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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|
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.venv/Lib/site-packages/altair-4.2.0.dist-info/METADATA
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.venv/Lib/site-packages/altair-4.2.0.dist-info/METADATA
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Metadata-Version: 2.1
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Name: altair
|
||||
Version: 4.2.0
|
||||
Summary: Altair: A declarative statistical visualization library for Python.
|
||||
Home-page: http://altair-viz.github.io
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||||
Author: Brian E. Granger / Jake VanderPlas
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||||
Author-email: jakevdp@gmail.com
|
||||
License: BSD 3-clause
|
||||
Download-URL: http://github.com/altair-viz/altair/
|
||||
Platform: UNKNOWN
|
||||
Classifier: Development Status :: 5 - Production/Stable
|
||||
Classifier: Environment :: Console
|
||||
Classifier: Intended Audience :: Science/Research
|
||||
Classifier: License :: OSI Approved :: BSD License
|
||||
Classifier: Natural Language :: English
|
||||
Classifier: Programming Language :: Python :: 3.7
|
||||
Classifier: Programming Language :: Python :: 3.8
|
||||
Classifier: Programming Language :: Python :: 3.9
|
||||
Classifier: Programming Language :: Python :: 3.10
|
||||
Requires-Python: >=3.7
|
||||
Description-Content-Type: text/markdown
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Requires-Dist: entrypoints
|
||||
Requires-Dist: jinja2
|
||||
Requires-Dist: jsonschema (>=3.0)
|
||||
Requires-Dist: numpy
|
||||
Requires-Dist: pandas (>=0.18)
|
||||
Requires-Dist: toolz
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||||
Provides-Extra: dev
|
||||
Requires-Dist: black ; extra == 'dev'
|
||||
Requires-Dist: docutils ; extra == 'dev'
|
||||
Requires-Dist: ipython ; extra == 'dev'
|
||||
Requires-Dist: flake8 ; extra == 'dev'
|
||||
Requires-Dist: pytest ; extra == 'dev'
|
||||
Requires-Dist: sphinx ; extra == 'dev'
|
||||
Requires-Dist: mistune (<2.0.0) ; extra == 'dev'
|
||||
Requires-Dist: m2r ; extra == 'dev'
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Requires-Dist: vega-datasets ; extra == 'dev'
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Requires-Dist: recommonmark ; extra == 'dev'
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|
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# Altair <a href="https://altair-viz.github.io/"><img align="right" src="https://altair-viz.github.io/_static/altair-logo-light.png" height="50"></img></a>
|
||||
|
||||
[](https://travis-ci.org/altair-viz/altair)
|
||||
[](https://github.com/altair-viz/altair/actions?query=workflow%3Abuild)
|
||||
[](https://github.com/psf/black)
|
||||
[](https://joss.theoj.org/papers/10.21105/joss.01057)
|
||||
[](https://pypi.org/project/altair)
|
||||
[](https://mybinder.org/v2/gh/altair-viz/altair_notebooks/master?urlpath=lab/tree/notebooks/Index.ipynb)
|
||||
[](https://colab.research.google.com/github/altair-viz/altair_notebooks/blob/master/notebooks/Index.ipynb)
|
||||
|
||||
[https://altair-viz.github.io](https://altair-viz.github.io)
|
||||
|
||||
**Altair** is a declarative statistical visualization library for Python. With Altair, you can spend more time understanding your data and its meaning. Altair's
|
||||
API is simple, friendly and consistent and built on top of the powerful
|
||||
[Vega-Lite](https://github.com/vega/vega-lite) JSON specification. This elegant
|
||||
simplicity produces beautiful and effective visualizations with a minimal amount of code. *Altair is developed by [Jake Vanderplas](https://github.com/jakevdp) and [Brian
|
||||
Granger](https://github.com/ellisonbg) in close collaboration with the [UW
|
||||
Interactive Data Lab](https://idl.cs.washington.edu/).*
|
||||
|
||||
## Altair Documentation
|
||||
|
||||
See [Altair's Documentation Site](https://altair-viz.github.io),
|
||||
as well as Altair's [Tutorial Notebooks](https://github.com/altair-viz/altair_notebooks).
|
||||
|
||||
## Example
|
||||
|
||||
Here is an example using Altair to quickly visualize and display a dataset with the native Vega-Lite renderer in the JupyterLab:
|
||||
|
||||
```python
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||||
import altair as alt
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|
||||
# load a simple dataset as a pandas DataFrame
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from vega_datasets import data
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||||
cars = data.cars()
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|
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alt.Chart(cars).mark_point().encode(
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x='Horsepower',
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y='Miles_per_Gallon',
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||||
color='Origin',
|
||||
)
|
||||
```
|
||||
|
||||
|
||||
|
||||
One of the unique features of Altair, inherited from Vega-Lite, is a declarative grammar of not just visualization, but _interaction_.
|
||||
With a few modifications to the example above we can create a linked histogram that is filtered based on a selection of the scatter plot.
|
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|
||||
```python
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import altair as alt
|
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from vega_datasets import data
|
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|
||||
source = data.cars()
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|
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brush = alt.selection(type='interval')
|
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|
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points = alt.Chart(source).mark_point().encode(
|
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x='Horsepower',
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y='Miles_per_Gallon',
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color=alt.condition(brush, 'Origin', alt.value('lightgray'))
|
||||
).add_selection(
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||||
brush
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||||
)
|
||||
|
||||
bars = alt.Chart(source).mark_bar().encode(
|
||||
y='Origin',
|
||||
color='Origin',
|
||||
x='count(Origin)'
|
||||
).transform_filter(
|
||||
brush
|
||||
)
|
||||
|
||||
points & bars
|
||||
```
|
||||
|
||||
|
||||
|
||||
|
||||
## Getting your Questions Answered
|
||||
|
||||
If you have a question that is not addressed in the documentation, there are several ways to ask:
|
||||
|
||||
- open a [Github Issue](https://github.com/altair-viz/altair/issues)
|
||||
- post a [StackOverflow Question](https://stackoverflow.com/questions/tagged/altair) (be sure to use the `altair` tag)
|
||||
- ask on the [Altair Google Group](https://groups.google.com/forum/#!forum/altair-viz)
|
||||
|
||||
We'll do our best to get your question answered
|
||||
|
||||
## A Python API for statistical visualizations
|
||||
|
||||
Altair provides a Python API for building statistical visualizations in a declarative
|
||||
manner. By statistical visualization we mean:
|
||||
|
||||
* The **data source** is a `DataFrame` that consists of columns of different data types (quantitative, ordinal, nominal and date/time).
|
||||
* The `DataFrame` is in a [tidy format](https://vita.had.co.nz/papers/tidy-data.pdf)
|
||||
where the rows correspond to samples and the columns correspond to the observed variables.
|
||||
* The data is mapped to the **visual properties** (position, color, size, shape,
|
||||
faceting, etc.) using the group-by data transformation.
|
||||
|
||||
The Altair API contains no actual visualization rendering code but instead
|
||||
emits JSON data structures following the
|
||||
[Vega-Lite](https://github.com/vega/vega-lite) specification. The resulting
|
||||
Vega-Lite JSON data can be rendered in the following user-interfaces:
|
||||
|
||||
* [Jupyter Notebook](https://github.com/jupyter/notebook) (by installing [ipyvega](https://github.com/vega/ipyvega)).
|
||||
* [JupyterLab](https://github.com/jupyterlab/jupyterlab) (no additional dependencies needed).
|
||||
* [nteract](https://github.com/nteract/nteract) (no additional dependencies needed).
|
||||
|
||||
## Features
|
||||
|
||||
* Carefully-designed, declarative Python API based on
|
||||
[traitlets](https://github.com/ipython/traitlets).
|
||||
* Auto-generated internal Python API that guarantees visualizations are type-checked and
|
||||
in full conformance with the [Vega-Lite](https://github.com/vega/vega-lite)
|
||||
specification.
|
||||
* Auto-generate Altair Python code from a Vega-Lite JSON spec.
|
||||
* Display visualizations in the live Jupyter Notebook, JupyterLab, nteract, on GitHub and
|
||||
[nbviewer](https://nbviewer.jupyter.org/).
|
||||
* Export visualizations to PNG/SVG images, stand-alone HTML pages and the
|
||||
[Online Vega-Lite Editor](https://vega.github.io/editor/#/).
|
||||
* Serialize visualizations as JSON files.
|
||||
* Explore Altair with dozens of examples in the [Example Gallery](https://altair-viz.github.io/gallery/index.html)
|
||||
|
||||
## Installation
|
||||
|
||||
To use Altair for visualization, you need to install two sets of tools
|
||||
|
||||
1. The core Altair Package and its dependencies
|
||||
|
||||
2. The renderer for the frontend you wish to use (i.e. `Jupyter Notebook`,
|
||||
`JupyterLab`, or `nteract`)
|
||||
|
||||
Altair can be installed with either ``pip`` or with ``conda``.
|
||||
For full installation instructions, please see
|
||||
https://altair-viz.github.io/getting_started/installation.html
|
||||
|
||||
## Example and tutorial notebooks
|
||||
|
||||
We maintain a separate Github repository of Jupyter Notebooks that contain an
|
||||
interactive tutorial and examples:
|
||||
|
||||
https://github.com/altair-viz/altair_notebooks
|
||||
|
||||
To launch a live notebook server with those notebook using [binder](https://mybinder.org/) or
|
||||
[Colab](https://colab.research.google.com), click on one of the following badges:
|
||||
|
||||
[](https://beta.mybinder.org/v2/gh/altair-viz/altair_notebooks/master)
|
||||
[](https://colab.research.google.com/github/altair-viz/altair_notebooks/blob/master/notebooks/Index.ipynb)
|
||||
|
||||
## Project philosophy
|
||||
|
||||
Many excellent plotting libraries exist in Python, including the main ones:
|
||||
|
||||
* [Matplotlib](https://matplotlib.org/)
|
||||
* [Bokeh](https://bokeh.pydata.org/en/latest/)
|
||||
* [Seaborn](https://seaborn.pydata.org/)
|
||||
* [Lightning](https://github.com/lightning-viz/lightning)
|
||||
* [Plotly](https://plot.ly/)
|
||||
* [Pandas built-in plotting](https://pandas.pydata.org/pandas-docs/stable/visualization.html)
|
||||
* [HoloViews](https://holoviews.org)
|
||||
* [VisPy](https://vispy.org/)
|
||||
* [pygg](https://www.github.com/sirrice/pygg)
|
||||
|
||||
Each library does a particular set of things well.
|
||||
|
||||
### User challenges
|
||||
|
||||
However, such a proliferation of options creates great difficulty for users
|
||||
as they have to wade through all of these APIs to find which of them is the
|
||||
best for the task at hand. None of these libraries are optimized for
|
||||
high-level statistical visualization, so users have to assemble their own
|
||||
using a mishmash of APIs. For individuals just learning data science, this
|
||||
forces them to focus on learning APIs rather than exploring their data.
|
||||
|
||||
Another challenge is current plotting APIs require the user to write code,
|
||||
even for incidental details of a visualization. This results in an unfortunate
|
||||
and unnecessary cognitive burden as the visualization type (histogram,
|
||||
scatterplot, etc.) can often be inferred using basic information such as the
|
||||
columns of interest and the data types of those columns.
|
||||
|
||||
For example, if you are interested in the visualization of two numerical
|
||||
columns, a scatterplot is almost certainly a good starting point. If you add
|
||||
a categorical column to that, you probably want to encode that column using
|
||||
colors or facets. If inferring the visualization proves difficult at times, a
|
||||
simple user interface can construct a visualization without any coding.
|
||||
[Tableau](https://www.tableau.com/) and the [Interactive Data
|
||||
Lab's](https://idl.cs.washington.edu/)
|
||||
[Polestar](https://github.com/vega/polestar) and
|
||||
[Voyager](https://github.com/vega/voyager) are excellent examples of such UIs.
|
||||
|
||||
### Design approach and solution
|
||||
|
||||
We believe that these challenges can be addressed without the creation of yet
|
||||
another visualization library that has a programmatic API and built-in
|
||||
rendering. Altair's approach to building visualizations uses a layered design
|
||||
that leverages the full capabilities of existing visualization libraries:
|
||||
|
||||
1. Create a constrained, simple Python API (Altair) that is purely declarative
|
||||
2. Use the API (Altair) to emit JSON output that follows the Vega-Lite spec
|
||||
3. Render that spec using existing visualization libraries
|
||||
|
||||
This approach enables users to perform exploratory visualizations with a much
|
||||
simpler API initially, pick an appropriate renderer for their usage case, and
|
||||
then leverage the full capabilities of that renderer for more advanced plot
|
||||
customization.
|
||||
|
||||
We realize that a declarative API will necessarily be limited compared to the
|
||||
full programmatic APIs of Matplotlib, Bokeh, etc. That is a deliberate design
|
||||
choice we feel is needed to simplify the user experience of exploratory
|
||||
visualization.
|
||||
|
||||
## Development install
|
||||
|
||||
Altair requires the following dependencies:
|
||||
|
||||
* [pandas](https://pandas.pydata.org/)
|
||||
* [traitlets](https://github.com/ipython/traitlets)
|
||||
* [IPython](https://github.com/ipython/ipython)
|
||||
|
||||
If you have cloned the repository, run the following command from the root of the repository:
|
||||
|
||||
```
|
||||
pip install -e .[dev]
|
||||
```
|
||||
|
||||
If you do not wish to clone the repository, you can install using:
|
||||
|
||||
```
|
||||
pip install git+https://github.com/altair-viz/altair
|
||||
```
|
||||
|
||||
## Testing
|
||||
|
||||
To run the test suite you must have [py.test](https://pytest.org/latest/) installed.
|
||||
To run the tests, use
|
||||
|
||||
```
|
||||
py.test --pyargs altair
|
||||
```
|
||||
(you can omit the `--pyargs` flag if you are running the tests from a source checkout).
|
||||
|
||||
## Feedback and Contribution
|
||||
|
||||
See [`CONTRIBUTING.md`](https://github.com/altair-viz/altair/blob/master/CONTRIBUTING.md)
|
||||
|
||||
## Citing Altair
|
||||
|
||||
[](https://joss.theoj.org/papers/10.21105/joss.01057)
|
||||
|
||||
If you use Altair in academic work, please consider citing https://joss.theoj.org/papers/10.21105/joss.01057 as
|
||||
|
||||
```bib
|
||||
@article{VanderPlas2018,
|
||||
doi = {10.21105/joss.01057},
|
||||
url = {https://doi.org/10.21105/joss.01057},
|
||||
year = {2018},
|
||||
publisher = {The Open Journal},
|
||||
volume = {3},
|
||||
number = {32},
|
||||
pages = {1057},
|
||||
author = {Jacob VanderPlas and Brian Granger and Jeffrey Heer and Dominik Moritz and Kanit Wongsuphasawat and Arvind Satyanarayan and Eitan Lees and Ilia Timofeev and Ben Welsh and Scott Sievert},
|
||||
title = {Altair: Interactive Statistical Visualizations for Python},
|
||||
journal = {Journal of Open Source Software}
|
||||
}
|
||||
```
|
||||
Please additionally consider citing the [vega-lite](https://vega.github.io/vega-lite/) project, which Altair is based on: https://dl.acm.org/doi/10.1109/TVCG.2016.2599030
|
||||
```bib
|
||||
@article{Satyanarayan2017,
|
||||
author={Satyanarayan, Arvind and Moritz, Dominik and Wongsuphasawat, Kanit and Heer, Jeffrey},
|
||||
title={Vega-Lite: A Grammar of Interactive Graphics},
|
||||
journal={IEEE transactions on visualization and computer graphics},
|
||||
year={2017},
|
||||
volume={23},
|
||||
number={1},
|
||||
pages={341-350},
|
||||
publisher={IEEE}
|
||||
}
|
||||
```
|
||||
|
||||
## Whence Altair?
|
||||
|
||||
Altair is the [brightest star](https://en.wikipedia.org/wiki/Altair) in the constellation Aquila, and along with Deneb and Vega forms the northern-hemisphere asterism known as the [Summer Triangle](https://en.wikipedia.org/wiki/Summer_Triangle).
|
||||
|
||||
|
||||
507
.venv/Lib/site-packages/altair-4.2.0.dist-info/RECORD
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507
.venv/Lib/site-packages/altair-4.2.0.dist-info/RECORD
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@ -0,0 +1,507 @@
|
||||
altair-4.2.0.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
|
||||
altair-4.2.0.dist-info/LICENSE,sha256=MvF85LRhteZoWExdbH9i4AD03ei0RnKFg6nnMEDsqPg,1501
|
||||
altair-4.2.0.dist-info/METADATA,sha256=I5ceMR-71d8WbJN_75py53oiCm2cwyLnWCtlejkUDlM,13746
|
||||
altair-4.2.0.dist-info/RECORD,,
|
||||
altair-4.2.0.dist-info/WHEEL,sha256=OqRkF0eY5GHssMorFjlbTIq072vpHpF60fIQA6lS9xA,92
|
||||
altair-4.2.0.dist-info/top_level.txt,sha256=JMBcunbUG0vYB5joP_RPeeOVAvx4F4HGmQ7B-dlv6qI,7
|
||||
altair/__init__.py,sha256=qhSavqxzXSQE7eeMl3ub0_Gbmg_LL5-1NXAMw1-DRdY,269
|
||||
altair/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/__pycache__/_magics.cpython-310.pyc,,
|
||||
altair/__pycache__/datasets.cpython-310.pyc,,
|
||||
altair/_magics.py,sha256=ze4PT_Uu0vdsS9ve5OfZ-ZDQw19HaONqFGwwTGqVHZM,5203
|
||||
altair/datasets.py,sha256=IQMisnfDA0QRNQmplMRY2lFJiHAf3ajY5MW3_kw2ExU,645
|
||||
altair/examples/__init__.py,sha256=M3X7GJu5K7hu2KZCUWJmcy90ZeRgrcQ78jACsH0Wx3Y,558
|
||||
altair/examples/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/examples/__pycache__/airport_connections.cpython-310.pyc,,
|
||||
altair/examples/__pycache__/airports.cpython-310.pyc,,
|
||||
altair/examples/__pycache__/airports_count.cpython-310.pyc,,
|
||||
altair/examples/__pycache__/anscombe_plot.cpython-310.pyc,,
|
||||
altair/examples/__pycache__/area_chart_gradient.cpython-310.pyc,,
|
||||
altair/examples/__pycache__/bar_and_line_with_dual_axis.cpython-310.pyc,,
|
||||
altair/examples/__pycache__/bar_chart_horizontal.cpython-310.pyc,,
|
||||
altair/examples/__pycache__/bar_chart_sorted.cpython-310.pyc,,
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altair/utils/core.py,sha256=vUCFdhnkHdOXMN1cTmPQ5fsMcrQyQGiU3q5-AU42wD0,21957
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||||
altair/utils/data.py,sha256=SIaxDkFowJ1jYmvLc6jKeS3bPcGR-slrQ2nOg3inz-I,8047
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||||
altair/utils/deprecation.py,sha256=8X8JTIubRAeYCU7FdCh_62hiZsjItKe2goi2KDlU3PM,1744
|
||||
altair/utils/display.py,sha256=0w4B5FQn4yhrIheSvkEjE9gDLNI1qfsulFvMLy9fd9A,6269
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||||
altair/utils/execeval.py,sha256=8dcrGym8BA2OEXeA-bzF-eeEDYaMgYJZUfE5a2cqixU,1598
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||||
altair/utils/html.py,sha256=IjSMS1O4OtlF_1VTFbZjRT3hd6gajGMwLtAaa6pTG7c,7908
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||||
altair/utils/mimebundle.py,sha256=YCjaN0mF3Z4MxKzqfibjl8i3fxAGe6nefsGV3LdbVbA,2857
|
||||
altair/utils/plugin_registry.py,sha256=s6l99oh8gEEmNr-WL8L6p-9KJhSK1RCq7czmYrKJoww,7000
|
||||
altair/utils/save.py,sha256=zhvOBzj8yyb5jpPWyxA5dLcOtsiEnbgHldOKIoBIfpE,4455
|
||||
altair/utils/schemapi.py,sha256=9fwLnHDxIjElh8tLFZHRsKnQP3i9v13BHTESwEcNq3Q,20141
|
||||
altair/utils/server.py,sha256=0H0ZfGOSoHwwm6Tg8SYSk6lr4YPAB5vvMBt4kkPEs78,4091
|
||||
altair/utils/tests/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
|
||||
altair/utils/tests/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_core.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_data.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_deprecation.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_execeval.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_html.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_mimebundle.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_plugin_registry.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_schemapi.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_server.cpython-310.pyc,,
|
||||
altair/utils/tests/__pycache__/test_utils.cpython-310.pyc,,
|
||||
altair/utils/tests/test_core.py,sha256=mRK3DD2A_YHBU3DfiPEbYliAWyvc88Ie7qcg8sYVEoI,8233
|
||||
altair/utils/tests/test_data.py,sha256=Cc_SzNP-o-dq79Jy_RZRn4BMTO77wRIa_1KXT25Kux4,3861
|
||||
altair/utils/tests/test_deprecation.py,sha256=DJtaSu6iSUW-dKvsgFEkKXK6_YfA1PK2_9fgr0JJn1I,690
|
||||
altair/utils/tests/test_execeval.py,sha256=F4Lcq49_0DHWRBapHh2cVh9MfMhbvETTDngzZ5mDHfw,530
|
||||
altair/utils/tests/test_html.py,sha256=cd-7TQUoYgtmT7acVywAGKPl_3QC4tmyYqQ7_QndRd8,1439
|
||||
altair/utils/tests/test_mimebundle.py,sha256=yaxlAqxDkU9X_MDA6v0cjAR8h-Xg6NitXGA8ZUFqBdM,6400
|
||||
altair/utils/tests/test_plugin_registry.py,sha256=WvwWO9A30bf5tu8PU_mRlFKLwFY86f4DGwxlukHl_3w,3619
|
||||
altair/utils/tests/test_schemapi.py,sha256=_ulbI1ztx0dYJ1gGzQPyp0P3QkiL8eR2oE4r8vo_Eis,9385
|
||||
altair/utils/tests/test_server.py,sha256=btAdR-s-NGo2XHKMINrfEvZIs2Gz0U3BhEced3MeOE4,230
|
||||
altair/utils/tests/test_utils.py,sha256=RVqHi9WdNTB5NDU2pX9k2ARkmXQRbdz9oVymgzBTG0Q,6552
|
||||
altair/utils/theme.py,sha256=b1VS--VOilgE8hrw05-DjIz_d5ND8qVqTrT-OWTqD_Y,221
|
||||
altair/vega/__init__.py,sha256=EGYjKbYbl2ZRaw1vUIw7LhqbomxaYV8kLb71r_2UWYM,33
|
||||
altair/vega/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vega/__pycache__/data.cpython-310.pyc,,
|
||||
altair/vega/__pycache__/display.cpython-310.pyc,,
|
||||
altair/vega/data.py,sha256=BXgUhbfanZLhUgLjGz2ucwPHjhN7LVUGjDKqe9gNJE0,1024
|
||||
altair/vega/display.py,sha256=z2LFWYDNtk9OPq9_luZMqS6oqVxSxV9RwddQQK4ZEtE,306
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||||
altair/vega/tests/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
|
||||
altair/vega/tests/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vega/tests/__pycache__/test_import.cpython-310.pyc,,
|
||||
altair/vega/tests/test_import.py,sha256=1EC96TP388IZMuHyRJ0NBPGd1HUqBBijsHw4JPtbPOM,120
|
||||
altair/vega/v5/__init__.py,sha256=hktWy2j69jvtBm_n5cZWI68JCqhb0G7gJQRzbTIV92M,222
|
||||
altair/vega/v5/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vega/v5/__pycache__/data.cpython-310.pyc,,
|
||||
altair/vega/v5/__pycache__/display.cpython-310.pyc,,
|
||||
altair/vega/v5/data.py,sha256=UtCpYu_MdLHYCjLJgj9fUqqrHbdi6OuvUOWwLA7DjGw,522
|
||||
altair/vega/v5/display.py,sha256=8zPJauo3aoXfVBG4F8xrK8JCGJBirCSerzJDPMVWrl4,2962
|
||||
altair/vega/v5/schema/__init__.py,sha256=yOWCNUMnPuWF3LXP5joooTxiGk4iBnPN8Bm-BjO_hmk,126
|
||||
altair/vega/v5/schema/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vega/v5/schema/__pycache__/core.cpython-310.pyc,,
|
||||
altair/vega/v5/schema/core.py,sha256=bE6_b6O50EVayrtYc4Qx0DEZtxZSb3pe9jiRJUao3rs,111093
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||||
altair/vega/v5/schema/vega-schema.json,sha256=Tq6GmZs0fUuetFMQkibodoja9KfOuhHxTBdhC7Dz2W4,399098
|
||||
altair/vegalite/__init__.py,sha256=Z4Kae_gmqsdjLhutwrKTLHw-2j3_OPEAx0SVuVcyvFw,33
|
||||
altair/vegalite/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vegalite/__pycache__/api.cpython-310.pyc,,
|
||||
altair/vegalite/__pycache__/data.cpython-310.pyc,,
|
||||
altair/vegalite/__pycache__/display.cpython-310.pyc,,
|
||||
altair/vegalite/__pycache__/schema.cpython-310.pyc,,
|
||||
altair/vegalite/api.py,sha256=1jaXpR7lyPrmBEihR40BtuytE2ozdLOxCqz3nExQTjo,37
|
||||
altair/vegalite/data.py,sha256=6D0PSRFDDNhLEkM9AXx7yQEloR43u8G6FmjvbSdS7z0,1008
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||||
altair/vegalite/display.py,sha256=i5WPQsUD4x7vfI6yaOe1DX6vRr7ftcHBgYgXR9R0LWQ,276
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||||
altair/vegalite/schema.py,sha256=aQpkwVeKCpZGhrFAPUI1SXZ3t5xotojaTONEU9Y_9xc,69
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||||
altair/vegalite/tests/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
|
||||
altair/vegalite/tests/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vegalite/tests/__pycache__/test_common.cpython-310.pyc,,
|
||||
altair/vegalite/tests/test_common.py,sha256=G2_NVFkpwlt1S_vRACCIYY8EAcqcA6-OP7B1o05GKmQ,2602
|
||||
altair/vegalite/v3/__init__.py,sha256=H9UO08bngQg5jRC3DHGRndemGEtdtYVu1kljag2pRzw,409
|
||||
altair/vegalite/v3/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vegalite/v3/__pycache__/_deprecated.cpython-310.pyc,,
|
||||
altair/vegalite/v3/__pycache__/api.cpython-310.pyc,,
|
||||
altair/vegalite/v3/__pycache__/data.cpython-310.pyc,,
|
||||
altair/vegalite/v3/__pycache__/display.cpython-310.pyc,,
|
||||
altair/vegalite/v3/__pycache__/theme.cpython-310.pyc,,
|
||||
altair/vegalite/v3/_deprecated.py,sha256=JJmcGZAAy499ZDIwfQe2zoTCuzFu0r6aWxn0VMEhwx4,1058
|
||||
altair/vegalite/v3/api.py,sha256=5pZNIyI-fOwK0r4BSBDJk_Z8mHzPNoiG1yGIjlKGaOI,76424
|
||||
altair/vegalite/v3/data.py,sha256=Xh1iAwQynQEU0aGhISWKG4JpjsvWhvgjAx3Jxic9zSg,961
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||||
altair/vegalite/v3/display.py,sha256=Sq1Ak_LWj6CFU5xFH05dI3TmbNyJeYmge2-frReZxkw,4133
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altair/vegalite/v3/schema/__init__.py,sha256=WwFnvbwSfSXjQ4NSg5VsCS_ii8RBtg-kZVbEuz4rDJQ,152
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||||
altair/vegalite/v3/schema/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vegalite/v3/schema/__pycache__/channels.cpython-310.pyc,,
|
||||
altair/vegalite/v3/schema/__pycache__/core.cpython-310.pyc,,
|
||||
altair/vegalite/v3/schema/__pycache__/mixins.cpython-310.pyc,,
|
||||
altair/vegalite/v3/schema/channels.py,sha256=G35HMHAUByV_iBhX5TnPjSSlsahBkuBSGkDH-Et2WU8,263403
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||||
altair/vegalite/v3/schema/core.py,sha256=1AdpreX9RH0cPB952PI8fzmKwDsWoPG6lWMxxz7fxhw,751732
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||||
altair/vegalite/v3/schema/mixins.py,sha256=-rmQuE5Ow3jdPIuLnLjPmkqR71teUnhUBSOqpaiMnxQ,47162
|
||||
altair/vegalite/v3/schema/vega-lite-schema.json,sha256=a0r_kdFQ-8L2BJj2bEaNvFIDQ9kDQm4882oeK3_yfEQ,678330
|
||||
altair/vegalite/v3/tests/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
|
||||
altair/vegalite/v3/tests/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vegalite/v3/tests/__pycache__/test_api.cpython-310.pyc,,
|
||||
altair/vegalite/v3/tests/__pycache__/test_data.cpython-310.pyc,,
|
||||
altair/vegalite/v3/tests/__pycache__/test_display.cpython-310.pyc,,
|
||||
altair/vegalite/v3/tests/__pycache__/test_geo_interface.cpython-310.pyc,,
|
||||
altair/vegalite/v3/tests/__pycache__/test_renderers.cpython-310.pyc,,
|
||||
altair/vegalite/v3/tests/__pycache__/test_theme.cpython-310.pyc,,
|
||||
altair/vegalite/v3/tests/test_api.py,sha256=evdq8qG-BO3g7cI8wc-5mTj_YQmpZXo4YgzItArz0fQ,29937
|
||||
altair/vegalite/v3/tests/test_data.py,sha256=cKfkUP015m6pYsYq9kf5fTkjwy7oY1TmWzlRGsc7PAo,966
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||||
altair/vegalite/v3/tests/test_display.py,sha256=SiDZmqiNjva-Z-VRPxncC_T9WOTbNRAww9Q4bN5MWJM,1976
|
||||
altair/vegalite/v3/tests/test_geo_interface.py,sha256=VehjMM4o4MvmP-xMTX_uzXrLVha6sZ23S6aaDW0GTPE,6496
|
||||
altair/vegalite/v3/tests/test_renderers.py,sha256=RTEGP_aerLC4R2Rkow9SJqgFltqhzItdecRwDSgULcM,2993
|
||||
altair/vegalite/v3/tests/test_theme.py,sha256=bJfvbZAqrShvtSc6gyqRxvmnocx572MWr6Mdfa7q1rM,525
|
||||
altair/vegalite/v3/theme.py,sha256=meH6Qy5EOXP7kLS_TUBTjbg18h4deVe6pPMFifkrphc,1435
|
||||
altair/vegalite/v4/__init__.py,sha256=ncmtsjAQ_9U7ZXJNEMqWxJ8pCl_G5MayleE_74O3og0,382
|
||||
altair/vegalite/v4/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vegalite/v4/__pycache__/api.cpython-310.pyc,,
|
||||
altair/vegalite/v4/__pycache__/data.cpython-310.pyc,,
|
||||
altair/vegalite/v4/__pycache__/display.cpython-310.pyc,,
|
||||
altair/vegalite/v4/__pycache__/theme.cpython-310.pyc,,
|
||||
altair/vegalite/v4/api.py,sha256=lF9oI8B7f_xLxjdETnC1ei0zal1YBcmASOfBH-7cQ7E,89700
|
||||
altair/vegalite/v4/data.py,sha256=puAJ0gsSRS4d7FBI8H3el9spu_UIFykLPrU8HldT6-c,961
|
||||
altair/vegalite/v4/display.py,sha256=GcsGE0qehKAdvdPMHrkPJuw40ujcshDjEgfjolHxSYU,3522
|
||||
altair/vegalite/v4/schema/__init__.py,sha256=hnPGkzXrf8kzWWX8SGCUSGEJbtFNKVhV4_jbBxzN4a4,154
|
||||
altair/vegalite/v4/schema/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vegalite/v4/schema/__pycache__/channels.cpython-310.pyc,,
|
||||
altair/vegalite/v4/schema/__pycache__/core.cpython-310.pyc,,
|
||||
altair/vegalite/v4/schema/__pycache__/mixins.cpython-310.pyc,,
|
||||
altair/vegalite/v4/schema/channels.py,sha256=WrSUJ7rPI05vxyuLAghSV2W1NtNJnodghVihrK_9s0w,583838
|
||||
altair/vegalite/v4/schema/core.py,sha256=Wm4EYUPy41RzKEtYXqeetHyvT8D1E2HBiAoP8ffwZbc,973217
|
||||
altair/vegalite/v4/schema/mixins.py,sha256=R2IItJP-yiP__nX2PFiXPoQ8nSo4RB0bLHgUn7Q-F80,85182
|
||||
altair/vegalite/v4/schema/vega-lite-schema.json,sha256=IfCmoCg4dEdFQdbx-IcShsfmvybY7i6phMc_MdzRwj4,1813485
|
||||
altair/vegalite/v4/tests/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
|
||||
altair/vegalite/v4/tests/__pycache__/__init__.cpython-310.pyc,,
|
||||
altair/vegalite/v4/tests/__pycache__/test_api.cpython-310.pyc,,
|
||||
altair/vegalite/v4/tests/__pycache__/test_data.cpython-310.pyc,,
|
||||
altair/vegalite/v4/tests/__pycache__/test_display.cpython-310.pyc,,
|
||||
altair/vegalite/v4/tests/__pycache__/test_geo_interface.cpython-310.pyc,,
|
||||
altair/vegalite/v4/tests/__pycache__/test_renderers.cpython-310.pyc,,
|
||||
altair/vegalite/v4/tests/__pycache__/test_theme.cpython-310.pyc,,
|
||||
altair/vegalite/v4/tests/test_api.py,sha256=xCt3YJCQFYxL1rk-hoj3UtGMQNhFbTJfzgDr39VuKF8,30953
|
||||
altair/vegalite/v4/tests/test_data.py,sha256=cKfkUP015m6pYsYq9kf5fTkjwy7oY1TmWzlRGsc7PAo,966
|
||||
altair/vegalite/v4/tests/test_display.py,sha256=l382FqqwaeJ1mgIx2aBYL7xSrJcv_gdtCH_K1EJ7GvY,1976
|
||||
altair/vegalite/v4/tests/test_geo_interface.py,sha256=9K4YqtljdMo9ZqG_XEyyHMmN7eLQYiQ_wvWTJB1mlug,6496
|
||||
altair/vegalite/v4/tests/test_renderers.py,sha256=OQkoRdCpMLxiHbMsC4c_cVS5caMr6ZJPbZ9_4hCB7zA,2477
|
||||
altair/vegalite/v4/tests/test_theme.py,sha256=khpwI-KNQvPicOru4mGU8Kl9lxPqaoEh2ePC8_AiERA,505
|
||||
altair/vegalite/v4/theme.py,sha256=jd1OmLc0ic2jPkgdgk4DqF-hBCDOqyw7KyZbuACDRRs,1390
|
||||
5
.venv/Lib/site-packages/altair-4.2.0.dist-info/WHEEL
Normal file
5
.venv/Lib/site-packages/altair-4.2.0.dist-info/WHEEL
Normal file
@ -0,0 +1,5 @@
|
||||
Wheel-Version: 1.0
|
||||
Generator: bdist_wheel (0.36.2)
|
||||
Root-Is-Purelib: true
|
||||
Tag: py3-none-any
|
||||
|
||||
@ -0,0 +1 @@
|
||||
altair
|
||||
Reference in New Issue
Block a user