Python Hands-on Crash Course For Data Science Guide

But sitting down to learn Python for data science often feels different than learning Python for web development. You don’t need to build a video game or a social media platform. You need to clean messy spreadsheets, run statistical tests, and build machine learning models.

Open your terminal. Type jupyter notebook . Write import pandas as pd . Touch the data. Python Hands-On Crash Course For Data Science

The crash course starts now.

Download the Titanic passenger list from Kaggle. Use Pandas to load the CSV. Use df.isnull().sum() to find missing ages. Use Matplotlib to plot a histogram of passenger fares. Fix the missing ages using the median. Phase 3: The Wrangle (90% of the Real Job) Data is never clean. It arrives with null values, duplicates, inconsistent capitalization ("New York" vs "new york"), and impossible outliers (Age = 999). But sitting down to learn Python for data