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Release/v0.1.5 (#25)
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* Frame index col (#23)

* somewhat working

* now working reliable for 2d arrays

* diryt support for labels, legend

* multiplot working with pandas

* added test for multiplot

* cleaned up pandas api testing

* minor updates to pandas api

* updated docs with pandas walk through

* updated docs with pandas walk through

* fixing the tests

* Datetime axis (#24)

* added conversion from datetime to numeric

* added timedelta rounding

* somewhat works

* basic changes to docs

* works a bit better

* tests passing

* added more test

* updated docs

* updated docs

* cleaning up axis

* updated changelog
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@CDonnerer
CDonnerer committed Jan 18, 2021
1 parent 18fa9d9 commit 0975533
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8 changes: 8 additions & 0 deletions CHANGELOG.rst
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Expand Up @@ -3,6 +3,14 @@ Changelog
=========


Version 0.1.5
-------------
- Allow to plot multiple scatters via 2d np arrays
- Added support for datetime types
- Added pandas visualisation example docs
- General support for adding legend to plot via ``label`` keyword


Version 0.1.4
-------------
- Fixed bug in x-axis drawing, spurious rounding
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217 changes: 131 additions & 86 deletions docs/examples/basic_usage.rst
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Expand Up @@ -16,33 +16,39 @@ Scatter plots can be created via the ``plot`` function::
>>> y = np.cos(x)
>>> plt.plot(x, y)

1.0┤ ++++++
| +++ +++
| ++ ++
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0.5┤ ++ ++
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-1.0┤ ++++++ ++++++
└┬----------------┬----------------┬-----------------┬----------------┬
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1.0┤ ++++++
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It is possible to modify the appearance of the plot by passing keyword args,
Expand Down Expand Up @@ -93,6 +99,43 @@ using a similar syntax to `matplotlib`_. E.g. we could modify the above call to

Please refer to :ref:`api_reference` for the full list of possible options.

Multiple scatters can be plotted by using 2d arrays::


>>> import numpy as np
>>> import shellplot as plt
>>> x1 = np.arange(-3, 6, 0.01)
>>> y1 = np.cos(x)
>>> y2 = np.sin(x)
>>> x, y = np.vstack((x1, x1)), np.vstack((y1, y2))
>>> plt.plot(x, y, label=("cos", "sin"), figsize=(61, 21))

1.0┤ +++++ ****** +
| +++ +++ ** ** +++
| ++ ++** ** ++
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-0.5┤ ** + ** + ** + **
| **++ ** ++ **++ **
| ** ** ++ ** **
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| +++ ** ** +++ +++ ** ** + cos
-1.0┤++ ****** +++++ ***** * sin
└┬------------┬-------------┬------------┬------------┬-------
-3 -1 1 3 5



Histogram
-------------------

Expand All @@ -102,36 +145,42 @@ Histogram plots can be created via the ``hist`` function::
>>> import numpy as np
>>> import shellplot as plt
>>> x = np.random.randn(10000)
>>> plt.hist(x, bins=10)

counts
2836┤ -----
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>>> plt.hist(x, bins=8)

counts
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Expand All @@ -144,35 +193,31 @@ Bar plots can be created via the ``bar`` function::
>>> import numpy as np
>>> import shellplot as plt
>>> x = np.logspace(0, 1, 3)
>>> plt.barh(x, labels=np.array(["bar_1", "bar_b", "bar_3"]))

|---------------------------------------------------------------------┐
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└┬-------------┬-------------┬------------┬-------------┬-------------┬
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>>> plt.barh(x, labels=np.array(["bar_1", "bar_b", "bar_3"]), figsize=(61, 19))

|------------------------------------------------------------
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|------------------------------------------------------------
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|-------------------
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bar_1┤ |
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|------
└┬-----------┬-----------┬-----------┬-----------┬-----------┬
0.0 2.0 4.0 6.0 8.0 10.0



Box plot
-------------------
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1 change: 1 addition & 0 deletions docs/examples/index.rst
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Expand Up @@ -7,4 +7,5 @@ Examples
:maxdepth: 2

Basic usage <basic_usage>
Pandas visualisation <pandas>
EDA: Penguins <penguins_eda>

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