🐍 Bibliotheques populaires

NumPy - Calcul scientifique

import numpy as np

# Creer un tableau
arr = np.array([1, 2, 3, 4, 5])

# Operations mathematiques
print(arr.mean())  # Moyenne
print(arr.sum())   # Somme
print(arr * 2)     # Multiplication par 2

# Tableau 2D
matrice = np.array([[1, 2], [3, 4]])

Pandas - Analyse de donnees

import pandas as pd

# Creer un DataFrame
data = {"nom": ["Alice", "Bob", "Charlie"],
        "age": [25, 30, 35]}
df = pd.DataFrame(data)

print(df.head())  # Premieres lignes
print(df["nom"])  # Selectionner une colonne
print(df[df["age"] > 28])  # Filtre

Matplotlib - Visualisation

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [10, 20, 25, 30, 40]

plt.plot(x, y)
plt.xlabel("X")
plt.ylabel("Y")
plt.title("Mon graphique")
plt.show()

Requests - Requetes HTTP

import requests

# Requete GET
response = requests.get("")
print(response.status_code)
print(response.json())

# Requete POST
data = {"nom": "Alice", "age": 25}
response = requests.post("", json=data)