Python Data Analysis
3h 44mIntermediate2025-01-09
Authors

Michele Vallisneri
Theoretical Astrophysicist at NASA Jet Propulsion Laboratory
Course details
Data science has transformed the way that government and industry leaders look at both specific problems and the world at large. Curious about how data analysis works in practice? In this course, instructor Michele Vallisneri explains what it takes to get started with data science using Python.
Michele demonstrates how to set up your analysis environment and provides a refresher on the basics of working with data structures in Python. Then, he jumps into the big stuff: the power of arrays, indexing, and tables in NumPy and pandas. He also guides you through two sample big-data projects: using NumPy to identify and visualize weather patterns and using pandas to analyze the popularity of baby names over the last century. Challenges issued along the way help you practice what you've learned. Plus, learn about the skills in the basic tasks of data analysis: importing and wrangling, summarizing and visualizing, modeling, and reasoning.
Michele demonstrates how to set up your analysis environment and provides a refresher on the basics of working with data structures in Python. Then, he jumps into the big stuff: the power of arrays, indexing, and tables in NumPy and pandas. He also guides you through two sample big-data projects: using NumPy to identify and visualize weather patterns and using pandas to analyze the popularity of baby names over the last century. Challenges issued along the way help you practice what you've learned. Plus, learn about the skills in the basic tasks of data analysis: importing and wrangling, summarizing and visualizing, modeling, and reasoning.
Skills covered
PythonData AnalysisProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceSoftware DevelopmentOne-Off
Concepts
Introduction
- From data to insight with Python
- What you need to know
- What is new in this update
- Set up - Using Codespaces
- CoderPad challenges
Python Data Structures
- Warmup with Python loops
- Tuples, lists, and the slicing syntax
- Dictionaries and sets
- Comprehensions
- Data classes
Project - Finding Anagrams
- Overview - Finding anagrams
- Loading dictionaries from text files
- Finding anagrams
- Solution - Find palindromes
NumPy
- NumPy overview
- Creating NumPy arrays
- Indexing NumPy arrays
- Doing math with NumPy arrays
- Special arrays - Records and dates
Project - Weather Data
- Overview - Analyzing weather
- Loading station and temperature data
- Cleaning weather data
- Smoothing and plotting time series
- Weather charts
- Solution - Temperature anomaly
pandas
- pandas overview
- pandas DataFrames and Series
- Indexing in pandas
- Math and plotting in pandas
- Database operations in pandas
Project - Baby Names
- Overview - Analyzing baby names
- Loading name datasets
- Comparing name popularity
- Compiling top tens
- Solution - Unisex names
Importing and Wrangling Data with pandas
- Overview - The structure of data
- Importing data with pandas
- Cleaning data
- Filtering, reshaping, and tidying data
- Simulating data
- Solution - Country rankings
Summarizing and Visualizing Data
- Overview - Exploring data
- Summarizing quantitative data
- Visualizing distributions
- Comparing quantitative variables
- Summarizing and visualizing categorical data
Introduction to Data Modeling
- Overview - Understanding data
- Fitting models to data
- Model evaluation and selection
- Testing hypotheses with Monte Carlo
- A taste of machine learning
- Solution - Gapminder model fit
Project - COVID-19 Data
- Overview - COVID-19 data
- Summarizing COVID-19 data
- Visualizing COVID-19 data
- Modeling COVID-19 data
Conclusion
- Extending your Python data analysis skills