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Merge pull request spotify#72 from spotify/chris/bar_color
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Better control over bar color
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@cphalpert
cphalpert authored Mar 8, 2019
2 parents 55a0783 + 8281ff2 commit e188526
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15 changes: 15 additions & 0 deletions HISTORY.rst
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Expand Up @@ -2,6 +2,21 @@
History
=======

2.6.0 (2019-03-08)
------------------

Improvements:

* Allows users to plot colors on bar charts that aren't contained in the
categorical axis.


Bugfixes:

* Fixed bug that caused float types to break when plotted with categorical
text plots (Thanks for finding @danela!)
* Fixed broken readme links.

2.5.0 (2019-02-17)
------------------

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6 changes: 3 additions & 3 deletions README.rst
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Expand Up @@ -4,7 +4,7 @@ Chartify
|status| |release| |python|

.. |status| image:: https://img.shields.io/badge/Status-Beta-blue.svg
.. |release| image:: https://img.shields.io/badge/Release-2.5.0-blue.svg
.. |release| image:: https://img.shields.io/badge/Release-2.6.0-blue.svg
.. |python| image:: https://img.shields.io/badge/Python-3.6-blue.svg

Chartify is a Python library that makes it easy for data scientists to create charts.
Expand Down Expand Up @@ -46,9 +46,9 @@ Installation
Getting started
---------------

This `tutorial notebook </examples/Chartify%20Tutorial.ipynb>`_ is the best place to get started with a guided tour of the core concepts of Chartify.
This `tutorial notebook <https://github.com/spotify/chartify/blob/master/examples/Chartify%20Tutorial.ipynb>`_ is the best place to get started with a guided tour of the core concepts of Chartify.

From there, check out the `example notebook </examples/Examples.ipynb>`_ for a list of all the available plots.
From there, check out the `example notebook <https://github.com/spotify/chartify/blob/master/examples/Examples.ipynb>`_ for a list of all the available plots.

Getting support
---------------
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2 changes: 1 addition & 1 deletion chartify/__init__.py
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Expand Up @@ -22,7 +22,7 @@

__author__ = """Chris Halpert"""
__email__ = '[email protected]'
__version__ = '2.5.0'
__version__ = '2.6.0'

_IPYTHON_INSTANCE = False

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95 changes: 69 additions & 26 deletions chartify/_core/plot.py
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Expand Up @@ -90,17 +90,22 @@ def _get_color_and_order(self,
if categorical_columns is None: # Numeric data
colors = next_colors
else:
# Color column must be in the categorical_columns
try:
color_index = categorical_columns.index(color_column)
except ValueError:
raise ValueError(
'''`color_column` must be present
in the `categorical_columns`'''
)
# # Color column must be in the categorical_columns
# try:
# color_index = categorical_columns.index(color_column)
# color_label = 'factors'
# except ValueError:
# color_label = 'color_column'
# color_index = 0
# raise ValueError(
# '''`color_column` must be present
# in the `categorical_columns`'''
# )
color_label = 'color_column'
color_index = 0
color_order = [str(factor) for factor in color_order]
colors = bokeh.transform.factor_cmap(
'factors',
color_label,
palette=next_colors,
factors=color_order,
start=color_index,
Expand Down Expand Up @@ -964,7 +969,8 @@ def _construct_source(self,
stack_column=None,
normalize=False,
categorical_order_by=None,
categorical_order_ascending=False):
categorical_order_ascending=False,
color_column=None):
"""Constructs ColumnDataSource
Returns:
Expand Down Expand Up @@ -1003,8 +1009,18 @@ def _construct_source(self,
columns=stack_column,
index=categorical_columns,
values=numeric_column,
aggfunc='sum').fillna(0) # NA columns break the stacks
aggfunc='sum')
)
# NA columns break the stacks
# Might want to make this conditional in the future for parallel plots.
source = source.fillna(0)

if color_column:
# Merge color column
color_df = data_frame.astype(type_map)
color_df['color_column'] = color_df[color_column].astype(str)
color_df = color_df.set_index(categorical_columns)['color_column']
source = source.join(color_df)

# Normalize values at the grouped levels.
# Only relevant for stacked objects
Expand Down Expand Up @@ -1152,14 +1168,15 @@ def text(self,
numeric_column,
categorical_order_by=categorical_order_by,
categorical_order_ascending=categorical_order_ascending)
sliced_data = (sliced_data.set_index(categorical_columns)
sliced_data = (sliced_data.astype(str)
.set_index(categorical_columns)
.reindex(source.data['factors']).reset_index())
# Text column isn't in the source so it needs to be added.
if text_column != numeric_column:
source.add(sliced_data[text_column], name=text_column)
sliced_data['text_column'] = sliced_data[text_column]
source.add(sliced_data['text_column'], name='text_column')

self._chart.figure.text(
text=text_column,
text='text_column',
x=x_value,
y=y_value,
text_font_size=font_size,
Expand Down Expand Up @@ -1285,7 +1302,7 @@ def text_stacked(self,
.reindex(index=factors).reset_index())

text_values = np.where(sliced_data[text_column].isna(), '',
sliced_data[text_column])
sliced_data[text_column].astype(str))

if cumulative_numeric_value is not None:
cumulative_numeric_value = (
Expand Down Expand Up @@ -1363,17 +1380,25 @@ def bar(self,
categorical_columns,
numeric_column,
categorical_order_by=categorical_order_by,
categorical_order_ascending=categorical_order_ascending)
categorical_order_ascending=categorical_order_ascending,
color_column=color_column)

colors, color_values = self._get_color_and_order(
data_frame, color_column, color_order, categorical_columns)

colors, _ = self._get_color_and_order(data_frame, color_column,
color_order, categorical_columns)
if color_column is None:
colors = colors[0]

self._set_categorical_axis_default_factors(vertical, factors)
self._set_categorical_axis_default_range(vertical, data_frame,
numeric_column)
bar_width = self._get_bar_width(factors)

if color_column:
legend = bokeh.core.properties.field('color_column')
else:
legend = None

if vertical:
self._chart.figure.vbar(
x='factors',
Expand All @@ -1382,7 +1407,8 @@ def bar(self,
bottom=0,
line_color='white',
source=source,
fill_color=colors)
fill_color=colors,
legend=legend)
else:
self._chart.figure.hbar(
y='factors',
Expand All @@ -1391,7 +1417,11 @@ def bar(self,
left=0,
line_color='white',
source=source,
fill_color=colors)
fill_color=colors,
legend=legend)
# Set legend defaults if there are multiple series.
if color_column is not None:
self._chart.style._apply_settings('legend')
return self._chart

def interval(self,
Expand Down Expand Up @@ -1708,17 +1738,23 @@ def lollipop(self,
categorical_columns,
numeric_column,
categorical_order_by=categorical_order_by,
categorical_order_ascending=categorical_order_ascending)
categorical_order_ascending=categorical_order_ascending,
color_column=color_column)

colors, _ = self._get_color_and_order(data_frame, color_column,
color_order, categorical_columns)
colors, color_values = self._get_color_and_order(
data_frame, color_column, color_order, categorical_columns)
if color_column is None:
colors = colors[0]

self._set_categorical_axis_default_factors(vertical, factors)
self._set_categorical_axis_default_range(vertical, data_frame,
numeric_column)

if color_column:
legend = bokeh.core.properties.field('color_column')
else:
legend = None

if vertical:
self._chart.figure.segment(
'factors',
Expand All @@ -1735,7 +1771,8 @@ def lollipop(self,
fill_color=colors,
line_color=colors,
line_width=3,
source=source)
source=source,
legend=legend)
else:
self._chart.figure.segment(
0,
Expand All @@ -1752,7 +1789,13 @@ def lollipop(self,
fill_color=colors,
line_color=colors,
line_width=3,
source=source)
source=source,
legend=legend)

# Set legend defaults if there are multiple series.
if color_column is not None:
self._chart.style._apply_settings('legend')

return self._chart

def parallel(self,
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25 changes: 25 additions & 0 deletions tests/test_plots.py
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Expand Up @@ -220,6 +220,20 @@ def test_single_datetime_text(self):
chart_data(ch, '')['text'], ['a', 'b', 'a', 'b']))


class CategoricalTextTest:
def test_float_labels(self):
label_test = pd.DataFrame(
{'value': [.20, .40, .05, .6, .2, .8],
'bucket': [1, 2, 3, 1, 2, 3],
'platform': ['android', 'android', 'android', 'ios', 'ios', 'ios'],
'value2': [1.0, 2.0, 3, 6., 8., 10.]})
ch = chartify.Chart(x_axis_type='categorical')
ch.plot.text(label_test, ['bucket', 'platform'], 'value', 'value')
assert (np.array_equal(
ch.data[0]['text_column'].values,
['0.8', '0.05', '0.6', '0.2', '0.4', '0.2']))


class TestAreaPlot:
"""Area plot tests.
Expand Down Expand Up @@ -341,6 +355,7 @@ def setup(self):
self.data = pd.DataFrame({
'category1': ['a', 'b', 'a', 'b', 'a'],
'category2': [1, 1, 2, 2, 3],
'color': ['c', 'd', 'e', 'f', 'g'],
'number': [5, 4, 10, -3, 0],
})
self.plot_methods = ['bar', 'lollipop', 'parallel']
Expand Down Expand Up @@ -453,6 +468,16 @@ def test_bar_parallel_color_column(self):
assert (np.array_equal(chart_data(ch, '')['2'], [10, -3]))
assert (np.array_equal(chart_data(ch, '')['3'], [0, 0]))

def test_bar_color(self):
ch = chartify.Chart(blank_labels=True, x_axis_type='categorical')
ch.plot.bar(
data_frame=self.data,
categorical_columns=['category1', 'category2'],
numeric_column='number',
color_column='color')
assert np.array_equal(
ch.data[0]['color_column'], ['e', 'c', 'g', 'd', 'f'])


class TestBarNumericSort:
def setup(self):
Expand Down

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