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提取码：52n7

As an engineer, I work with data all the time. I parse log files, analyze data, estimate values, 

and compare the results with theory. Things don’t always add up. So I double-check my analy￾sis, perform more calculations, or run simulations to better understand the results. I refer to 

previous work because the ideas are similar or sometimes because they’re dissimilar. I look at 

the graphs and realize I’m missing some crucial information. So I add the missing data, but it’s 

noisy and needs filtering. Eventually, I realize my implementation of the algorithm is poor or 

that there is a better algorithm with better results, and so back to square one. It’s an iterative 

process: tweak, test, tweak again until I’m satisfied with the results.

Those are the tasks surrounding research and development (R&D) work. And to be honest, 

there’s no systematic method. Most of the time, research is organized chaos. The emphasis, 

however, should be on organized, not chaos. Data should be analyzed and presented in a 

clear and coherent manner. Sources for graphs well understood and verified to be accurate. 

Algorithms tested and proven to be working as intended. The system should be flexible. Intro￾ducing new ideas and challenging previous methods should be easy and testing new ideas on 

current data fast and efficient.

In this book I will attempt to address all the topics associated with data processing and 

visualization: managing files and directories, reading files of varying formats, performing 

signal processing and numerical analysis in a high-level programming language similar to 

MATLAB and GNU-Octave, and teaching you Python, a rich and powerful programming lan￾guage, along the way.

In a nutshell, Beginning Python Visualization deals with the processing, analysis, manipu￾lation, and visualization of data using the Python programming language. The book covers the 

following:

1

2 CHAPTER 1 N￾ NAVIGATING THE WORLD OF DATA VISUALIZATION

￾ s￾ &UNDAMENTALS￾OF￾THE￾0YTHON￾PROGRAMMING￾LANGUAGE￾REQUIRED￾FOR￾DATA￾ANALYSIS￾AND￾

visualization

￾ s￾ $ATA￾FILES￾FORMAT￾AND￾ORGANIZATION￾AS￾WELL￾AS￾METHODS￾AND￾GUIDELINES￾FOR￾SELECTING￾FILE￾

formats and storing and organizing data to enable fast, efficient data processing

￾ s￾ 2EADILY￾AVAILABLE￾0YTHON￾PACKAGES￾FOR￾NUMERICAL￾ANALYSIS￾SIGNAL￾AND￾IMAGE￾PROCESSING￾

graphing and plotting, and more

Gathering Data

We spend a considerable time recording and analyzing data. Data is stored in various formats 

depending on the tools used to collect it, the nature of the data (e.g., pictures vs. sampled 

analog data), the application that will later process the data, and personal preferences. Data 

files are of varying sizes; some are very large, others are smaller but in larger quantities. Data 

ORGANIZATION￾ADDS￾ANOTHER￾LEVEL￾OF￾COMPLEXITY￾&ILES￾CAN￾BE￾STORED￾IN￾DIRECTORIES￾ACCORDING￾TO￾

date, grouped together in one big directory or in a database, or adhere to a different scheme 

altogether. Typically, the number of data files or the amount of data per file is too large to 

allow skimming or browsing with an editor or viewer. Methods and tools are required to find 

the data and analyze it to produce meaningful results.

Case Study: GPS Data

You just got a USB GPS receiver for your birthday! You’d like to analyze GPS data and find out 

how often you exceed the speed limit and how much time you spend in traffic. You’d like to 

track data over a year, or even longer.

Some hardware background: most USB GPS receivers behave as serial ports (this is also 

true for Bluetooth GPS devices). What this means is that once a GPS is connected, and assum￾ing it’s installed properly, reading GPS data is as simple as opening the COM port associated 

with the GPS and reading the values. GPS values are typically clear text values: numbers and 

text. Of course, if you’re planning on recording data from your car, it would make a lot of sense 

to hook it up to a laptop rather than a desktop.

7E￾WOULD￾LIKE￾TO￾RECORD￾ANALYZE￾AND￾VISUALIZE￾THE￾'03￾DATA￾IN￾0YTHON￾&IRST￾THINGS￾FIRST￾

recording GPS data.

NNote If you wish to follow along with the remainder of the chapter by means of issuing the commands 

yourself and viewing the results, you might first want to refer to Chapter 2 and set up Python on your system. 

That being said, it’s not necessary, and you can follow along to get an understanding of the book and its 

purpose. In fact, I encourage you to come back to this chapter and read it again after you’ve had more expe￾rience with Python.

Python is an interpreted programming language. What this means is each command 

is first read and then executed, in contrast to compiled programming languages, where the 

entire program is evaluated (compiled) and then executed. One of the important features of 

CHAPTER 1 N