Pandas & NumPy for ML

Pandas and NumPy provide the foundation for data manipulation and numerical computing in Machine Learning workflows.

NumPy Array Basics

Creating and reshaping arrays

import numpy as np

a = np.array([1, 2, 3])
matrix = np.arange(12).reshape(3, 4)

print(matrix.shape)   # (3, 4)
print(matrix.mean(axis=0))

Loading and inspecting data

import pandas as pd

df = pd.read_csv("data.csv")

print(df.head())
print(df.info())
print(df.describe())

grouped = df.groupby("category")["sales"].agg(["mean", "sum", "count"])
print(grouped)

merged = df_customers.merge(df_orders, on="customer_id", how="inner")