#!/usr/bin/env python
# coding: utf-8

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from lets_plot import *
import lets_plot.mapping as pm


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LetsPlot.setup_html()


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df = {
    'x': [0, 5, 10, 15],
    'y': [0, 5, 10, 15],
    'a': [1, 2, 3, 4],
    'b': [4, 5, 6, 7]
}


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# as_discrete, no scale
p = ggplot(df, aes(x='x', y='y')) + geom_point(aes(color=pm.as_discrete('a', label='custom name')), size=9)
p


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# as_discrete, scale
p = ggplot(df, aes(x='x', y='y')) \
    + geom_point(aes(color='a', fill=pm.as_discrete('b')), shape=21, size=9, stroke=5) \
    + scale_color_discrete()
p


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# data in mappings, scale_color_discrete
p = ggplot() + geom_point(aes(x=[0, 5, 10], y=[0, 5, 10], color=[1, 2, 4]), size=9) + scale_color_discrete()
p


# ## Issue 1
# 
# `as_discrete` is not working when used in "ggplot()" mapping.

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p3 = ggplot(df, aes(x='x', y='y', color=pm.as_discrete('a'))) + geom_point(size=9)
p3


# ## Issue 2
# `as_discrete` doesn't create groups the way discrete variable does.

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df = {
    'x': [0, 5, 10, 15],
    'y': [0, 5, 10, 15],
    'a': [0, 0, 1, 1],
    'c': ['a', 'a', 'b', 'b']
}


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p4 = ggplot(df, aes(x='x', y='y')) + geom_line(aes(color=pm.as_discrete('a')), size=3)
p4


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# expected: 2 lines ('c' is a discrete variable)
p5 = ggplot(df, aes(x='x', y='y')) + geom_line(aes(color='c'), size=3)
p5


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# expected: 2 lines (`group` is defined manually)
p6 = ggplot(df, aes(x='x', y='y')) + geom_line(aes(color='a', group='a'), size=3)
p6


# ## Issue 2a
# Also about groups but with `stat` this time

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import pandas as pd
mpg_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv')
mpg_plot = ggplot(mpg_df, aes(x='displ', y='hwy'))


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cyl_factor = pm.as_discrete('cyl')
mpg_plot + geom_point(aes(color=cyl_factor)) \
+ geom_smooth(aes(color=cyl_factor), method='lm', size=1, se=False)


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# expected: seperate regression line for each group
mpg_plot + geom_point(aes(color=cyl_factor)) \
+ geom_smooth(aes(color='cyl', group='cyl'), method='lm', size=1, se=False)


# ## Issue 3
# "Not an aesthetic 'group'" error when used with `as_discrete`

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mpg_plot + geom_point(aes(color=cyl_factor)) \
+ geom_smooth(aes(color=cyl_factor, group='cyl'), method='lm', size=1, se=False)


# ## Issue 4
# Nice to have parameter `ordered`. Owerwise have to use `scale_discrete(breaks=[...])` to order groups by number of cylinders:

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mpg_plot + geom_point(aes(color=cyl_factor)) \
+ scale_color_discrete(breaks=[4, 5, 6, 8])


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mpg_plot + geom_point(aes(color=pm.as_discrete('cyl', label='cyl')))