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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
- Sales Rank: #684918 in Books
- Brand: imusti
- Published on: 2016-09-04
- Original language: English
- Number of items: 1
- Dimensions: 9.17" h x .74" w x 7.01" l, .0 pounds
- Binding: Paperback
- 352 pages
- O Reilly Media
About the Author
Clinton Brownley, Ph.D., is a data scientist at Facebook, where he is responsible for a wide variety of data pipelining, statistical modeling, and data visualization projects that inform data-driven decisions about large-scale infrastructure. Clinton is a Past-President of the San Francisco Bay Area Chapter of the American Statistical Association and a Council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Like many other people
By Sonny Torres
Finally a book that focuses on working with spreadsheets with Python. Like many other people, I am a heavy excel user and needed a guide to working with excel that went beyond your normal introductory load file and spit out some superficial row/column slices.
GREAT book with plenty of useful examples and exercises on working with Python (examples are in base python, pandas and base python with regular expresssions) for excel and csv files. The author is great at explaining the concepts and walking through each line of code to help you understand what each piece is doing.
0 of 0 people found the following review helpful.
Excellent introductory guide
By Amazon Customer
Excellent introductory guide, the font size in some of the code window examples is too small, which makes it hard to read.
0 of 9 people found the following review helpful.
Analytics with Python
By amajerzyzon
Just browsed. To early to tell.
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