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Bar Plots

Main Guide

Vertical Bar Plot

Simply use the bar() function:

  • the marker, color, and fill properties of the bar plot could be changed using their respective parameters: markers and colors are described in their linked sections.
  • the orientation (vertical by default) and relative bar width (4/5 by default) could also be changed using their respective parameters.

Here is an example:

import plotext as plt

pizzas = ["Sausage", "Pepperoni", "Mushrooms", "Cheese", "Chicken", "Beef"]
percentages = [14, 36, 11, 8, 7, 4]

plt.bar(pizzas, percentages)
plt.title("Most Favored Pizzas in the World")
plt.show()

or directly on terminal:

python3 -c "import plotext as plt; pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']; percentages = [14, 36, 11, 8, 7, 4]; plt.bar(pizzas, percentages); plt.title('Most Favored Pizzas in the World'); plt.show()"

vertical-bar

More documentation can be accessed with doc.bar().

Main Guide, Bar Plots

Horizontal Bar Plot

Simply set orientation = "horizontal" in the bar() function. Here is an example:

import plotext as plt

pizzas = ["Sausage", "Pepperoni", "Mushrooms", "Cheese", "Chicken", "Beef"]
percentages = [14, 36, 11, 8, 7, 4]

plt.bar(pizzas, percentages, orientation = "horizontal", width = 3 / 5) # or in short orientation = 'h'
plt.title("Most Favoured Pizzas in the World")
plt.show()

or directly on terminal:

python3 -c "import plotext as plt; pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']; percentages = [14, 36, 11, 8, 7, 4]; plt.bar(pizzas, percentages, orientation = 'h', width = 3 / 5); plt.title('Most Favored Pizzas in the World'); plt.show()"

horizontal-bar

More documentation can be accessed with doc.bar().

To create a simpler and sketchier version of the same bar plot, use the function simple_bar() instead:

  • the advantage of this bar plot is that it produces a very predictable output in terms of bar width (a single character),
  • the disadvantages are that its only orientation is horizontal, it cannot be used inside a matrix of subplots and any setting method which follows will not have any effect (like xlabel(), plotsize() and so on),

Here is an example:The default value for quintuples is False

import plotext as plt

pizzas = ["Sausage", "Pepperoni", "Mushrooms", "Cheese", "Chicken", "Beef"]
percentages = [14, 36, 11, 8, 7, 4]

plt.simple_bar(pizzas, percentages, width = 100, title = 'Most Favored Pizzas in the World')
plt.show()

or directly on terminal:

python3 -c "import plotext as plt; pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']; percentages = [14, 36, 11, 8, 7, 4]; plt.simple_bar(pizzas, percentages, width = 100, title = 'Most Favored Pizzas in the World'); plt.show()"

simple-bar

More documentation can be accessed with doc.simple_bar().

Main Guide, Bar Plots

Multiple Bar Plot

To plot multiple offsetted bars, each group with the same label, use the function plt.multiple_bar(), as in this example:

import plotext as plt

pizzas = ["Sausage", "Pepperoni", "Mushrooms", "Cheese", "Chicken", "Beef"]
male_percentages = [14, 36, 11, 8, 7, 4]
female_percentages = [12, 20, 35, 15, 2, 1]

plt.multiple_bar(pizzas, [male_percentages, female_percentages], labels = ["men", "women"])
plt.title("Most Favored Pizzas in the World by Gender")
plt.show()

or directly on terminal:

python3 -c "import plotext as plt; pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']; male_percentages = [14, 36, 11, 8, 7, 4]; female_percentages = [12, 20, 35, 15, 2, 1]; plt.multiple_bar(pizzas, [male_percentages, female_percentages], labels = ['men', 'women']); plt.title('Most Favored Pizzas in the World by Gender'); plt.show()"

multiple-bar

More documentation can be accessed with doc.multiple_bar().

To produce a simpler and sketchier version of the same bar plot, use the function simple_multiple_bar() instead, as in this example:

import plotext as plt
pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']
male_percentages = [14, 36, 11, 8, 7, 4]
female_percentages = [12, 20, 35, 15, 2, 1]
plt.simple_multiple_bar(pizzas, [male_percentages, female_percentages], width = 100, labels = ['men', 'women'], title = 'Most Favored Pizzas in the World by Gender')
plt.show()

or directly on terminal:

python3 -c "import plotext as plt; pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']; male_percentages = [14, 36, 11, 8, 7, 4]; female_percentages = [12, 20, 35, 15, 2, 1]; plt.simple_multiple_bar(pizzas, [male_percentages, female_percentages], width = 100, labels = ['men', 'women'], title = 'Most Favored Pizzas in the World by Gender'); plt.show()"

simple-multiple-bar

Note that this kind of plot has the same disadvantages as simple_bar(), as discussed in this section. More documentation can be accessed with doc.simple_multiple_bar().

Main Guide, Bar Plots

Stacked Bar Plot

To plot multiple bars on top of each other, each group with the same label, use the function plt.stacked_bar() as in this example:

import plotext as plt

pizzas = ["Sausage", "Pepperoni", "Mushrooms", "Cheese", "Chicken", "Beef"]
male_percentages = [14, 36, 11, 8, 7, 4]
female_percentages = [12, 20, 35, 15, 2, 1]

plt.stacked_bar(pizzas, [male_percentages, female_percentages], labels = ["men", "women"])
plt.title("Most Favored Pizzas in the World by Gender")
plt.show()

or directly on terminal:

python3 -c "import plotext as plt; pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']; male_percentages = [14, 36, 11, 8, 7, 4]; female_percentages = [12, 20, 35, 15, 2, 1]; plt.stacked_bar(pizzas, [male_percentages, female_percentages], labels = ['men', 'women']); plt.title('Most Favored Pizzas in the World by Gender'); plt.show()"

stacked-bar

The full documentation of the stacked_bar() function can be accessed with doc.stacked_bar().

To produce a simpler and sketchier version of the same bar plot, use the function simple_stacked_bar() instead, as in this example:

import plotext as plt
pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']
male_percentages = [14, 36, 11, 8, 7, 4]
female_percentages = [12, 20, 35, 15, 2, 1]
plt.simple_stacked_bar(pizzas, [male_percentages, female_percentages], width = 100, labels = ['men', 'women'], title = 'Most Favored Pizzas in the World by Gender')
plt.show()

or directly on terminal:

python3 -c "import plotext as plt; pizzas = ['Sausage', 'Pepperoni', 'Mushrooms', 'Cheese', 'Chicken', 'Beef']; male_percentages = [14, 36, 11, 8, 7, 4]; female_percentages = [12, 20, 35, 15, 2, 1]; plt.simple_stacked_bar(pizzas, [male_percentages, female_percentages], width = 100, labels = ['men', 'women'], title = 'Most Favored Pizzas in the World by Gender'); plt.show()"

simple-bar

Note that this kind of plot has the same disadvantages as simple_bar(), as discussed in this section. More documentation can be accessed with doc.simple_stacked_bar().

Main Guide, Bar Plots

Box Plot

Box plot is common and useful in statistics plot. plot.box function supports two types of input data. The first form involves providing the raw data to calculate the distribution(quintuples=False, default). Alternatively, one can directly provide the pre-calculated metrics, namely the minimum, first quartile, median, third quartile, and maximum(quintuples=True).

the first form:

import plotext as plt

labels = ["apple", "orange", "pear", "banana"]
data = [
    [1,2,3,5,10,8],
    [4,9,6,12,20,13],
    [1,2,3,4,5,6],
    [3,9,12,16,9,8,3,7,2]]

plt.box(labels, data, width=0.3)
plt.title("The weight of the fruit")
plt.show()

or directly on terminal:

python3 -c 'import plotext as plt;labels = ["apple", "orange", "pear", "banana"];data = [[1,2,3,5,10,8],[4,9,6,12,20,13],[1,2,3,4,5,6],[3,9,12,16,9,8,3,7,2]];plt.box(labels, data, width=0.3);plt.title("The weight of the fruit");plt.show()'

box-plot-1

the second form:

import plotext as plt

labels = ["apple", "orange", "pear", "banana"]
data = [
    # max, q75, q50, q25, min
    [10, 7, 5, 3, 1.5],
    [19, 12.3, 9, 7, 4],
    [15, 14, 11, 9, 8],
    [13, 12, 11, 10, 6]]

plt.box(labels, data, width=0.3, quintuples=True)
plt.title("The weight of the fruit")
plt.show()

or directly on terminal:

python3 -c 'import plotext as plt;labels = ["apple", "orange", "pear", "banana"];data = [[10, 7, 5, 3, 1.5],[19, 12.3, 9, 7, 4],[15, 14, 11, 9, 8],[13, 12, 11, 10, 6]];plt.box(labels, data, width=0.3, quintuples=True);plt.title("The weight of the fruit");plt.show()'

box-plot-2 This feature may require further development. Main Guide, Bar Plots

Histogram Plot

For a histogram plot use the function plt.hist(). Here is an example:

import plotext as plt
import random

l = 7 * 10 ** 4
data1 = [random.gauss(0, 1) for el in range(10 * l)]
data2 = [random.gauss(3, 1) for el in range(6 * l)]
data3 = [random.gauss(6, 1) for el in range(4 * l)]

bins = 60
plt.hist(data1, bins, label = "mean 0")
plt.hist(data2, bins, label = "mean 3")
plt.hist(data3, bins, label = "mean 6")

plt.title("Histogram Plot")
plt.show()

or directly on terminal:

python3 -c "import plotext as plt; import random; l = 7 * 10 ** 4; data1 = [random.gauss(0, 1) for el in range(10 * l)]; data2 = [random.gauss(3, 1) for el in range(6 * l)];  data3 = [random.gauss(6, 1) for el in range(4 * l)]; bins = 60; plt.hist(data1, bins, label = 'mean 0'); plt.hist(data2, bins, label = 'mean 3'); plt.hist(data3, bins, label = 'mean 6'); plt.title('Histogram Plot'); plt.show()"

hist

More documentation can be accessed with doc.hist().

Main Guide, Bar Plots