Learn Pandas for Machine Learning in 10 minutes

Get up and running with Pandas for Machine Learning in just 10 minutes! This beginner-friendly guide will help you master the basics of Pandas, a powerful data analysis and data manipulation library, and apply it to your Machine Learning projects with ease.

Set up

First we’ll import the NumPy and Pandas libraries and set seeds for reproducibility. We’ll also download the dataset we’ll be working with to disk.

import numpy as np
import pandas as pd

# Set seed for reproducibility
np.random.seed(seed=1234)

Load data

We will analyze the Titanic dataset, which contains information on passengers and their survival status. We’ll load the data into a Pandas dataframe, using “header=0” to specify the first row as the header with column names.

# Read from CSV to Pandas DataFrame
url = "https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv"
df = pd.read_csv(url, header=0)
# First 5 rows
df.head()

Output

| PassengerId | Survived | Pclass | Name                                            | Sex    | Age | SibSp | Parch | Ticket         | Fare  | Cabin | Embarked |…