Bar Plotting

Bar Plotting

In [1]:
import numpy as np
import matplotlib.pyplot as plt
In [2]:
ages = np.array([5, 25, 45, 20, 15])
names = np.array(['John', 'Maria', 'Priyanka', 'Martha', 'Matts'])
In [3]:
plt.bar(names, ages)
plt.show()
In [4]:
plt.bar(names, ages, color = "red")
plt.show()
In [5]:
color = np.array(["red", "purple", "green", "yellow", "blue"])
In [6]:
plt.bar(names, ages, color = color)
plt.show()

Bar graph title and x & y label

In [7]:
plt.bar(names, ages, color = color)

plt.title("Name and Age Bar Graph")
plt.xlabel("Names")
plt.ylabel("Ages")

plt.show()
In [8]:
plt.bar(names, ages, color = color)

plt.title("Name and Age Bar Graph", fontsize = 20)
plt.xlabel("Names", fontsize = 15)
plt.ylabel("Ages", fontsize = 15)

plt.show()

Plot ages and names change the x and y value

In [9]:
plt.bar(ages, names)
plt.show()

Horizental Bar

In [10]:
ages = np.array([5, 25, 45, 20, 15])
names = np.array(['John', 'Maria', 'Priyanka', 'Martha', 'Matts'])

plt.barh(names, ages)
plt.show()

Generate x any y with numpy arange()

In [11]:
x = np.arange(4)
y = np.random.rand(4)
print(x)
print(y)

[0 1 2 3]
[0.74977035 0.46075216 0.20877558 0.83256212]
In [12]:
plt.bar(x, y)
plt.show()

Combined bar graph

In [13]:
x = np.arange(5)
y = np.random.rand(4, 5)
In [14]:
print(x)
print(y)

[0 1 2 3 4]
[[0.7045655  0.71276931 0.42875423 0.32457147 0.10620684]
 [0.39211275 0.97822557 0.19020476 0.45456743 0.87602839]
 [0.6056702  0.92448795 0.97788145 0.93067779 0.44006445]
 [0.15374324 0.74571794 0.478721   0.63886297 0.36412861]]
In [15]:
plt.bar(x + 0.00, y[0], color = 'b', width = 0.25)
plt.bar(x + 0.25, y[1], color = 'g', width = 0.25)
plt.bar(x + 0.50, y[2], color = 'r', width = 0.25)
plt.show()

Plot grade and score

In [16]:
grade = ["III", "IV", "V", "VI", "VII"] 
score = [60, 40, 50, 78, 90]

position_of_grade = np.arange(len(grade))
plt.bar(position_of_grade, score)

plt.show()
In [17]:
grade = ["III", "IV", "V", "VI", "VII"] 
score = [60, 40, 50, 78, 90]

position_of_grade = np.arange(len(grade))
plt.bar(position_of_grade, score)

plt.xticks(position_of_grade, grade)
plt.title('Barchart - Score by Grade',fontsize=20)
plt.xlabel('Grade', fontsize=15)
plt.ylabel('Score in %', fontsize=15)

plt.show()
In [18]:
grade = ["III", "IV", "V", "VI", "VII"] 
score = [60, 40, 50, 78, 90]
color = ["red", "purple", "green", "yellow", "blue"]

position_of_grade = np.arange(len(grade))
plt.bar(position_of_grade, score, color = color, edgecolor = 'red')

plt.xticks(position_of_grade, grade)
plt.title('Barchart - Score by Grade',fontsize = 20)
plt.xlabel('Grade', fontsize = 15)
plt.ylabel('Score in %', fontsize = 15)

plt.show()

Linestyle, linewidth and alpha

linestyle description

'-' or 'solid' solid line '--' or 'dashed' dashed line '-.' or 'dashdot' dash-dotted line ':' or 'dotted' dotted line

In [19]:
grade = ["III", "IV", "V", "VI", "VII"] 
score = [60, 40, 50, 78, 90]
color = ["red", "purple", "green", "yellow", "blue"]

position_of_grade = np.arange(len(grade))
plt.bar(position_of_grade, score, color = color, edgecolor = 'red', linestyle = '--')

plt.xticks(position_of_grade, grade)
plt.title('Barchart - Score by Grade',fontsize = 20)
plt.xlabel('Grade', fontsize = 15)
plt.ylabel('Score in %', fontsize = 15)

plt.show()
In [20]:
grade = ["III", "IV", "V", "VI", "VII"] 
score = [60, 40, 50, 78, 90]
color = ["red", "purple", "green", "yellow", "blue"]

position_of_grade = np.arange(len(grade))
plt.bar(position_of_grade, score, color = color, edgecolor = 'red', linestyle = '--', alpha = 0.4, linewidth = 2)

plt.xticks(position_of_grade, grade)
plt.title('Barchart - Score by Grade',fontsize = 20)
plt.xlabel('Grade', fontsize = 15)
plt.ylabel('Score in %', fontsize = 15)

plt.show()

Stacked bar chart

In [21]:
grade = ["III", "IV", "V", "VI", "VII"] 
#score = [60, 40, 50, 78, 90]

score_male = [40, 60, 30, 65, 85]
score_female = [50, 70, 80, 55, 75]

position_of_grade = np.arange(len(grade))
plt.bar(position_of_grade, score_male, color = "#00bfff", edgecolor = 'red')
plt.bar(position_of_grade, score_female, color = "#bf00ff", edgecolor = 'red', bottom = score_male)

plt.xticks(position_of_grade, grade)
plt.title('Barchart - Score by Grade',fontsize = 20)
plt.xlabel('Grade', fontsize = 15)
plt.ylabel('Score in %', fontsize = 15)

plt.show()

Legend

Location String Location Code

'best' 0 'upper right' 1 'upper left' 2 'lower left' 3 'lower right' 4 'right' 5 'center left' 6 'center right' 7 'lower center' 8 'upper center' 9 'center' 10

In [22]:
grade = ["III", "IV", "V", "VI", "VII"] 
#score = [60, 40, 50, 78, 90]

Gender=['Male','Female']

score_male = [40, 60, 30, 65, 85]
score_female = [50, 70, 80, 55, 75]

position_of_grade = np.arange(len(grade))
plt.bar(position_of_grade, score_male, color = "#00bfff", edgecolor = 'red')
plt.bar(position_of_grade, score_female, color = "#bf00ff", edgecolor = 'red', bottom = score_male)

plt.xticks(position_of_grade, grade)
plt.title('Barchart - Score by Grade',fontsize = 20)
plt.xlabel('Grade', fontsize = 15)
plt.ylabel('Score in %', fontsize = 15)

plt.legend(Gender,loc=2)

plt.show()

Questions

A survey of 100 people asked them "Which is the nicest fruit?":

Fruit:      Apple   Orange  Banana  Mango   Watermelon  Grapes
People:     30      10      10      20      5           25
In [23]:
fruits = ["Apple", "Orange", "Banana", "Mango", "Watermelon", "Grapes"]
fruits
Out[23]:
['Apple', 'Orange', 'Banana', 'Mango', 'Watermelon', 'Grapes']
In [24]:
no_of_people = [30, 10, 10, 20, 5, 25]
no_of_people
Out[24]:
[30, 10, 10, 20, 5, 25]
In [25]:
color = ["#33f6ff", "#a5ff33", "#ee42d4", "#e7f121", "#f83a10", "#3f41f1"]
In [26]:
plt.bar(fruits, no_of_people, color = color)

plt.xticks(fruits)
plt.title('Barchart - Which is the nicest fruit?',fontsize=20)
plt.xlabel('Fruits', fontsize=15)
plt.ylabel('Number of People', fontsize=15)
plt.show()

Plot Literacy Rate in India

Top Performing States in 2018 No State Literacy Rate in Percentage 1 Kerala 96.2% 2 Delhi 88.7% 3 Uttarakhand 87.6% 4 Himachal Pradesh 86.6% 5 Assam 85.9% 6 Maharashtra 84.8%

In [27]:
states = ["Kerala", "Delhi", "Uttarakhand", "Himachal Pradesh", "Assam", "Maharashtra"]
states
Out[27]:
['Kerala', 'Delhi', 'Uttarakhand', 'Himachal Pradesh', 'Assam', 'Maharashtra']
In [28]:
literacy_rate = [96.2, 88.7, 87.6, 86.6, 85.9, 84.8]
literacy_rate
Out[28]:
[96.2, 88.7, 87.6, 86.6, 85.9, 84.8]
In [29]:
color = ["#33f6ff", "#a5ff33", "#ee42d4", "#e7f121", "#f83a10", "#3f41f1"]
In [30]:
plt.figure(figsize=(10, 6))
plt.bar(states, literacy_rate, color = color)

plt.xticks(states)
plt.title('Top Performing States in 2018',fontsize=20)
plt.xlabel('State', fontsize=15)
plt.ylabel('Literacy Rate in Percentage', fontsize=15)
plt.show()

Plot comparative literacy statistics on country

UNESCO list of countries by literacy rate (2015)

The adult and youth literacy rates for India and some neighboring countries in 2015. Adult literacy rate is based on the 15+ years age group, while the youth literacy rate is for the 15–24 years age group.

UNESCO list of countries by literacy rate (2015) Country Adult literacy rate Youth literacy rate ages 15–24 China 96.4% 99.7% Sri Lanka 92.6% 98.8% Myanmar 93.7% 96.3% World average 86.3% 91.2% India 81% 91.66% Nepal 64.7% 86.9% Bangladesh 61.5% 83.2% Pakistan 58% 80.3%

This data is taken from wikipedia https://en.wikipedia.org/wiki/Literacy_in_India.

In [31]:
countries = ["China", "Sri Lanka", "Myanmar", "World average", "India", "Nepal", "Bangladesh", "Pakistan"]
In [32]:
adult_literacy_rate = [96.4, 92.6, 93.7, 86.3, 81, 64.7, 61.5, 58]
In [33]:
color = ["#33f6ff", "#a5ff33", "#ee42d4", "#e7f121", "#f83a10", "#3f41f1", "#ef24d4", "#e3f124"]
In [34]:
plt.figure(figsize=(10, 6))
plt.bar(countries, adult_literacy_rate, color = color)

plt.xticks(countries)
plt.title('UNESCO list of countries by literacy rate (2015) ',fontsize=20)
plt.xlabel('Countries', fontsize=15)
plt.ylabel('Adult Literacy Rate in Percentage', fontsize=15)
plt.show()

Plot countries and adult youth literacy rate

In [35]:
adult_literacy_rate_ages_15_to_24 = [99.7, 98.8, 96.3, 91.2, 91.66, 86.9, 83.2, 80.3]
In [36]:
import seaborn as sns

colors= sns.color_palette("husl", 8)
colors
Out[36]:
In [37]:
plt.figure(figsize=(10, 6))
plt.bar(countries, adult_literacy_rate_ages_15_to_24, color = colors)

plt.xticks(countries)
plt.title('UNESCO List of Countries by Literacy Rate Ages 15–24 (2015) ',fontsize=18)
plt.xlabel('Countries', fontsize=12)
plt.ylabel('Youth Literacy Rate Ages 15–24 in Percentage', fontsize=12)
plt.show()

Subplots

In [38]:
fig, (ax1, ax2) = plt.subplots(1, 2)
fig.set_figwidth(20)

ax1.bar(countries, adult_literacy_rate, color = color)
ax1.set_title("Adult Literacy Rate")

ax2.bar(countries, adult_literacy_rate_ages_15_to_24, color = color)
ax2.set_title("Youth Literacy Rate")

fig.suptitle('UNESCO List of Countries by Literacy Rate Ages 15+ and 15–24 (2015)', fontsize = 20)

plt.show()

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