2.1. Matplotlib Plots

2.1.1. Pie Chart

import matplotlib.pyplot as plt


slices = [20, 6, 3, 13]
status = ['todo', 'in progress', 'in test', 'done']
colors = ['#0052CC', '#F6C242ff', '#F6C242aa', '#008759']

plt.pie(
    x=slices,            # data
    labels=status,       # name of the slices
    colors=colors,       # colors
    startangle=90,       # angle at which start plotting
    shadow=False,         # drop shadow outline?
    explode=[0,1,0,0],   # which piece to explode out from the chart
    autopct='%1.2f%%',   # number formatting
    radius=2,            # size of the chart
)

plt.show()  # doctest: +SKIP

2.1.2. Donut Chart

import matplotlib.pyplot as plt
import numpy as np


fig, ax = plt.subplots()

size = 0.3
vals = np.array([[60., 32.],
                 [37., 40.],
                 [29., 10.]])

cmap = plt.get_cmap("tab20c")
outer_colors = cmap([0, 4, 8])
inner_colors = cmap([1, 2, 5, 6, 9, 10])

ax.pie(vals.sum(axis=1),
       radius=1,
       colors=outer_colors,
       wedgeprops={'width': size, 'edgecolor': 'white'})

ax.pie(vals.flatten(),
       radius=1-size,
       colors=inner_colors,
       wedgeprops={'width': size, 'edgecolor': 'white'})

plt.show()  # doctest: +SKIP

2.1.3. Stack Plot

import matplotlib.pyplot as plt


labels = ['To Do', 'In Progress', 'In Test', 'In Review', 'Done']
colors = ['#0052CC', '#F6C242ff', '#F6C242aa', '#F6C24266', '#008759']

day         = [1, 2, 3, 4, 5]
todo        = [10, 8, 6, 4, 2]
in_progress = [2, 3, 4, 3, 2]
in_test     = [7, 8, 7, 2, 2]
in_review   = [8, 5, 7, 8, 1]
done        = [0, 2, 4, 6, 12]

plt.stackplot(day, todo, in_progress, in_test, in_review, done, labels=labels, colors=colors)
plt.legend(loc='upper left')
plt.show()  # doctest: +SKIP

2.1.4. Box Plot

import matplotlib.pyplot as plt


age = [
    22, 55, 62, 45, 21, 22, 34,
    42, 42, 4, 99, 102, 110, 120,
    121, 122, 130, 111, 115, 112,
    80, 75, 65, 54, 44, 43, 42, 48
]

plt.boxplot(age)
plt.show()  # doctest: +SKIP

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(0)


x = np.random.normal(size=1000)

plt.boxplot(x)
plt.show()  # doctest: +SKIP

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(0)


a = np.random.normal(size=1000)
b = np.random.normal(size=1000)
c = np.random.normal(size=1000)
d = np.random.normal(size=1000)
data = [a, b, c, d]

plt.boxplot(data)
plt.show()  # doctest: +SKIP

import matplotlib.pyplot as plt


center = [5]
spread = [5.0, 6, 5.1, 5.2, 5.5, 5.0, 4.1]
flier_high = [7, 7.5]
flier_low = [3, 3.3]
data = spread + center + flier_high + flier_low

plt.boxplot(data)
plt.show()  # doctest: +SKIP

2.1.5. Error

import matplotlib.pyplot as plt
import numpy as np


x = [1, 2, 3, 4]
y = [1, 4, 9, 16]
e = [0.5, 1.0, 1.5, 0.7]

plt.errorbar(x, y, yerr=e, fmt='o')
plt.show()  # doctest: +SKIP

import matplotlib.pyplot as plt
import numpy as np

x = [1, 2, 3, 4]
y = [1, 4, 9, 16]
e = [0.5, 1.0, 1.5, 0.7]

plt.errorbar(x, y, yerr=e, fmt='o-')
plt.show()  # doctest: +SKIP