Personnalisation

Python intermédiaire

Hugo Bowne-Anderson

Data Scientist at DataCamp

Visualisation des données

De nombreuses options
- Différents types de graphiques
- De nombreuses personnalisations
Le choix dépend de
- Données
- Histoire que vous souhaitez partager

Graphique de base

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

Étiquettes des axes

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

Étiquettes des axes

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

Titre

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

Titre

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

Coches

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

Coches

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

Coches (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

Coches (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

Ajouter des données historiques

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

Ajouter des données historiques

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

Avant et après

ch1_3_slides.031.png

Passons à la pratique !

Python intermédiaire