Customization

Intermediate Python

Hugo Bowne-Anderson

Data Scientist at DataCamp

Data visualization

Many options
- Different plot types
- Many customizations
Choice depends on
- Data
- Story you want to tell

Basic plot

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100]
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)

plt.show()

ch1_3_slides.012.png

Axis labels

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')


plt.show()

ch1_3_slides.012.png

Axis labels

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')


plt.show()

ch1_3_slides.014.png

Title

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')

plt.title('World Population Projections')


plt.show()

ch1_3_slides.015.png

Title

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')

plt.title('World Population Projections')


plt.show()

ch1_3_slides.017.png

Ticks

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')

plt.title('World Population Projections')

plt.yticks([0, 2, 4, 6, 8, 10])


plt.show()

ch1_3_slides.019.png

Ticks

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')

plt.title('World Population Projections')

plt.yticks([0, 2, 4, 6, 8, 10])


plt.show()

ch1_3_slides.020.png

Ticks (2)

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')

plt.title('World Population Projections')

plt.yticks([0, 2, 4, 6, 8, 10],

           ['0', '2B', '4B', '6B', '8B', '10B'])


plt.show()

ch1_3_slides.021.png

Ticks (2)

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]

plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')

plt.title('World Population Projections')

plt.yticks([0, 2, 4, 6, 8, 10],

           ['0', '2B', '4B', '6B', '8B', '10B'])


plt.show()

ch1_3_slides.027.png

Add historical data

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]


# Add more data
year = [1800, 1850, 1900] + year
pop = [1.0, 1.262, 1.650] + pop


plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')

plt.title('World Population Projections')

plt.yticks([0, 2, 4, 6, 8, 10],

           ['0', '2B', '4B', '6B', '8B', '10B'])


plt.show()

ch1_3_slides.028.png

Add historical data

population.py

import matplotlib.pyplot as plt
year = [1950, 1951, 1952, ..., 2100] 
pop = [2.538, 2.57, 2.62, ..., 10.85]


# Add more data
year = [1800, 1850, 1900] + year
pop = [1.0, 1.262, 1.650] + pop


plt.plot(year, pop)


plt.xlabel('Year')
plt.ylabel('Population')

plt.title('World Population Projections')

plt.yticks([0, 2, 4, 6, 8, 10],

           ['0', '2B', '4B', '6B', '8B', '10B'])


plt.show()

ch1_3_slides.030.png

Before vs. after

ch1_3_slides.031.png

Let's practice!

Intermediate Python