Python for Data Science with Pandas, NumPy and Matplotlib

Overview

This two-day course provides an overview of how Python can be used in Data Science to manipulate, process, clean, and crunch data. It is an introduction to scientific computing in Python focusing data-intensive applications. Specifically, the class will review the essential Python libraries: NumPy, pandas, matplotlib, IPython, and SciPy.

Audience

Students wanting use Python in data analytics applications.

Prerequisites

Students should have taken an introductory Python course or have six months of Python programming experience.

Course Outline

CHAPTER I BUILDING BLOCKS

WORKING WITH PYTHON

NUMPY NDARRAYS

SLICING AND INDEXING

SCALAR OPERATIONS

SHAPE SHIFTING

DESCRIPTIVE STATISTICS

ARRAY OPERATIONS

MULTIPLE DIMENSIONS

ARRAY CREATION OPTIONS

DATA TYPES

GETTING NUMPY-SPECIFIC HELP

OVERVIEW OF DATA VISUALIZATION / PRESENTATION TOOLS

CHAPTER II OVERVIEW OF PANDAS

WORKING WITH PANDAS IN AN IDE

ENHANCEMENTS FROM NDARRAY OBJECTS

SERIES OBJECTS

PANDAS IN 2-D

PANDAS IN 3-D

CHAPTER III DATA ACQUISITION

DEALING WITH MISSING DATA AND OUTLIERS

SLICING, DICING AND RE-INDEXING

DATA DESCRIPTION / ANALYSIS TOOLS

CHAPTER IV DATA VISUALIZATION

CHAPTER V DATETIME-LIKE OBJECTS

BASIC TIME SERIES OPERATIONS

INTROSPECTING TIME SERIES

TOOLS FOR HOLIDAYS, BUSINESS DAYS, ETC.

COMPARING AND COMBINING DATA FROM DIFFERENT SERIES

TIME SHIFTING AND TIME "WINDOW" OPERATIONS

CHAPTER VI PANDAS DATABASE OPS

COMPARISON OF SQL OPERATIONS AND PANDAS METHODS

CREATING PIVOT TABLES AND CROSS-TABULATIONS

AGGREGATING DATA ACROSS DIFFERENT TABLES

CREATING COMPLEX QUERIES WITH INTERMEDIATE DATA FRAME OBJECTS

CHAPTER VII PANDAS + MACHINE LEARNING TOOLS

WHAT IS LDA?

GETTING TO KNOW THE DATA

EXPLORING DATA INTEGRITY

APPLYING THE LDA MODEL

DO YOU WANT A DOGGIE BAG?

QUICK RECAP OF THE ANALYSIS

APPENDIX A TEXT-ONLY DEBUGGING

THE PDB DEBUG LIBRARY

OTHER TEXT-BASED TOOLS

INTEGRATING LOGGING WITH DEBUGGING

APPENDIX B INTRODUCTION TO BAYESIAN ANALYSIS

A SIMPLE REAL-LIFE EXAMPLE

THE BAYESIAN APPROACH

REALITY CHECKING