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friendly take over of PR6488 #7317

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9c666a0
correction for doc string and PEP8
aneda May 27, 2016
1f9176d
Cleanup : doc string and pep8
aneda May 27, 2016
f2e3153
Added initial description
aneda May 27, 2016
2bb93ec
Merge branch 'master' of https://github.com/aneda/matplotlib into ane…
fariza Oct 4, 2016
d0f6b82
update docstring
fariza Oct 4, 2016
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8 changes: 8 additions & 0 deletions examples/showcase/bachelors_degrees_by_gender.py
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@@ -1,3 +1,11 @@
"""
A graph of multiple time series which demonstrates extensive custom
styling of plot frame, tick lines and labels, and line graph properties.

Also demonstrates the custom placement of text labels along the right edge
as an alternative to a conventional legend.
"""

import matplotlib.pyplot as plt
from matplotlib.mlab import csv2rec
from matplotlib.cbook import get_sample_data
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6 changes: 3 additions & 3 deletions examples/statistics/boxplot_color_demo.py
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# Box plots with custom fill colors
"""Box plots with custom fill colors."""

import matplotlib.pyplot as plt
import numpy as np
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# adding horizontal grid lines
for ax in axes:
ax.yaxis.grid(True)
ax.set_xticks([y+1 for y in range(len(all_data))], )
ax.set_xticks([y + 1 for y in range(len(all_data))], )
ax.set_xlabel('xlabel')
ax.set_ylabel('ylabel')

# add x-tick labels
plt.setp(axes, xticks=[y+1 for y in range(len(all_data))],
plt.setp(axes, xticks=[y + 1 for y in range(len(all_data))],
xticklabels=['x1', 'x2', 'x3', 'x4'])

plt.show()
24 changes: 13 additions & 11 deletions examples/statistics/boxplot_vs_violin_demo.py
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@@ -1,13 +1,15 @@
# Box plot - violin plot comparison
#
# Note that although violin plots are closely related to Tukey's (1977) box plots,
# they add useful information such as the distribution of the sample data (density trace).
#
# By default, box plots show data points outside 1.5 x the inter-quartile range as outliers
# above or below the whiskers wheras violin plots show the whole range of the data.
#
# Violin plots require matplotlib >= 1.4.
"""Box plot - violin plot comparison.

Note that although violin plots are closely related to Tukey's (1977) box
plots, they add useful information such as the distribution of the sample
data (density trace).

By default, box plots show data points outside 1.5 x the inter-quartile range
as outliers above or below the whiskers wheras violin plots show the whole
range of the data.

Violin plots require matplotlib >= 1.4.
"""
import matplotlib.pyplot as plt
import numpy as np

Expand All @@ -29,11 +31,11 @@
# adding horizontal grid lines
for ax in axes:
ax.yaxis.grid(True)
ax.set_xticks([y+1 for y in range(len(all_data))])
ax.set_xticks([y + 1 for y in range(len(all_data))])
ax.set_xlabel('xlabel')
ax.set_ylabel('ylabel')

# add x-tick labels
plt.setp(axes, xticks=[y+1 for y in range(len(all_data))],
plt.setp(axes, xticks=[y + 1 for y in range(len(all_data))],
xticklabels=['x1', 'x2', 'x3', 'x4'])
plt.show()