Python Data Analytics Essentials
Explore the fundamentals of data analytics in Python, emphasizing Python libraries and practical skills for manipulating and analyzing data. Essential Python packages, including NumPy, pandas, matplotlib, SciPy, scikit-learn, and statsmodels, are covered. Get ready to dive into the world of data science with real-world datasets and hands-on exercises.
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Presentation Transcript
Data Analytics in Python COMP 2800 COMP 2800 David J Stucki David J Stucki Otterbein University Otterbein University
Course Info Syllabus Course Web Site Python Environment Python 3.12.1 is most current stable release. Please make sure you are using at least 3.10. Jupyter/IPython VS Code (Visual Studio Code) Questions?
What Do We Have In Common? Major/Minor: Business Analytics, Data Science, Computer Science... COMP 1800: when? Spring '21, Spring '22, Spring '23, Fall '23 Other Python experience? Statistics? ASCI 2000 (Data Science in R)? Exposure to large data sets? Databases?
What Is Data Analytics? Ideas? "... concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data." Wes McKinney What does that mean? Emphasis in this course is Python and Python libraries and how to use them We will touch on data science methods, statistics, analytical models, etc., but it is not the purpose of this course for those to be the main topics of study We will also be using a variety of large data sets from various sources, and learning how to represent, model, and interact with those.
Essential Python Packages for Data Analyics NumPy: pandas: matplotlib: SciPy: scikit-learn: statsmodels: n-dimensional arrays, fast, numerical computation on arrays, linear algebra tabular data (as in spreadsheets/relational databases); slice, dice, subset, aggregate, etc. plots and data visualizations scientific computing tools (numerical calculus, linear algebra, optimization, probability distributions, etc.) machine-learning toolkit (classification, regression, clustering, etc.) extensive statistical analysis tools
Begin a review of Python (read chapter 2 before class) Next Time...
