Librería Portfolio

If you're like many of Excel's 750 million users, you want to do more with your data-like repeating similar analyses over hundreds of files, or combining data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale the processing and analysis of data in different formats-by using Python.

After author Clinton Brownley takes you through Python basics, you'll be able to write simple scripts for processing data in spreadsheets as well as databases. You'll also learn how to use several Python modules for parsing files, grouping data, and producing statistics. No programming experience is necessary.

Create and run your own Python scripts by learning basic syntax
Use Python's csv module to read and parse CSV files
Read multiple Excel worksheets and workbooks with the xlrd module
Perform database operations in MySQL or with the mysqlclient module
Create Python applications to find specific records, group data, and parse text files
Build statistical graphs and plots with matplotlib, pandas, ggplot, and seaborn
Produce summary statistics, and estimate regression and classification models
Schedule your scripts to run automatically in both Windows and Mac environments



Chapter 1Python Basics
How to Create a Python Script
How to Run a Python Script
Useful Tips for Interacting with the Command Line
Python's Basic Building Blocks
Reading a Text File
Reading Multiple Text Files with glob
Writing to a Text File
print Statements
Chapter Exercises
Chapter 2Comma-Separated Values (CSV) Files
Base Python Versus pandas
Filter for Specific Rows
Select Specific Columns
Select Contiguous Rows
Add a Header Row
Reading Multiple CSV Files
Concatenate Data from Multiple Files
Sum and Average a Set of Values per File
Chapter Exercises
Chapter 3Excel Files
Introspecting an Excel Workbook
Processing a Single Worksheet
Reading All Worksheets in a Workbook
Reading a Set of Worksheets in an Excel Workbook
Processing Multiple Workbooks
Chapter Exercises
Chapter 4Databases
Python's Built-in sqlite3 Module
MySQL Database
Chapter Exercises
Chapter 5Applications
Find a Set of Items in a Large Collection of Files
Calculate a Statistic for Any Number of Categories from Data in a CSV File
Calculate Statistics for Any Number of Categories from Data in a Text File
Chapter Exercises
Chapter 6Figures and Plots
matplotlib
pandas
ggplot
seaborn
Chapter 7Descriptive Statistics and Modeling
Datasets
Wine Quality
Customer Churn
Chapter 8Scheduling Scripts to Run Automatically
Task Scheduler (Windows)
The cron Utility (macOS and Unix)
Chapter 9Where to Go from Here
Additional Standard Library Modules and Built-in Functions
Python Package Index (PyPI): Additional Add-in Modules
Additional Data Structures
Where to Go from Here
Appendix Download Instructions
Download Python 3
Download the xlrd Package
Download the MySQL Database Server
Download mysqlclient (Python 3.x)/MySQL-python (Python 2.x)
Appendix Answers to Exercises
Chapter 1