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pandas

Pandas tutorials covering DataFrames, data cleaning, and analysis in Python.

Pandas Project: Clean a Messy Real-World Dataset

This pandas project takes a genuinely messy dataset and turns it into numbers you can trust. You will audit the mess first, fix it in clear stages (types, dates, duplicates, categories, outliers), validate the result, then answer three real business questions with groupby and merge. By the end you have a notebook you can put on GitHub and point a hiring manager at. “Most of data science is janitor work. The model is the easy part, the cleaning is the ... Read More

Data Science: End-to-End Project, Raw Data to Insights

Build a complete Python data science project from start to finish. You load a real dataset, clean it, run exploratory analysis, engineer features, create visualizations, and present actionable business insights. “The goal is to turn data into information, and information into insight.” Carly Fiorina Last Updated: July 2026 | Tested on: Python 3.14.6, Pandas 2.3.3, NumPy 2.4.6, Seaborn 0.13.2, Matplotlib 3.11.0 | Difficulty: Advanced | Reading Time: 23 minutes This is where everything in Part 4 comes together. You have ... Read More

EDA: Exploratory Data Analysis Complete Workflow

Exploratory data analysis is the part everyone wants to skip and nobody should. Before you train a single model, you sit with the data and get to know it: load it, look at its shape, find the missing values, spot the outliers, and check which columns actually move together. This exploratory data analysis Python tutorial walks the full workflow on a realistic employee dataset, every number printed is real output from the code you see. “Fools ignore complexity. Pragmatists suffer ... Read More