Overview

By the end of this chapter, you will be able to use Python to read and write to files; use defensive programming techniques, such as assertions, to debug your code; use exceptions, assertions, and tests with a defensive mindset; and plot, draw, and create graphs as outputs.

You will also learn about the basic input/output (I/O) operations for Python and how to use the matplotlib and seaborn libraries to create visualizations.

Introduction

In Chapter 3, Executing Python – Programs, Algorithms, and Functions, you covered the basics of Python programs and learned how to write algorithms, functions, and programs. Now, you will learn how to make your programs more relevant and usable in the IT world.

In this chapter, you are going to look at file operations. File operations are essential for scripting as a Python developer, especially when you need to process and analyze a large number of files, such as in data science. In companies that deal with data science, you often do not have direct access to a database. Rather, they receive files in text format. These include CSV files for column data and TXT files for unstructured data (such as patient logs, news articles, user comments, and so on).

In this chapter, we will cover the following topics:

• Reading files
• Writing files
• Preparing for debugging (defensive code)
• Plotting techniques
• The don’ts of plotting graphs

...

Technical requirements

You can find the code files for this chapter on GitHub at https://github.com/PacktPublishing/The-Python-Workshop-Second-Edition/tree/main/Chapter04.

Reading files

While databases such as MySQL and Postgres are popular and widely used in many web applications, a large amount of data is still stored and exchanged using text file formats. Popular formats such as comma-separated values (CSV), JavaScript Object Notation (JSON), and plain text are used to store information such as weather data, traffic data, and sensor readings. In the following exercise, you will learn how to read text from a file using Python.

Exercise 59 – reading a text file using Python

In this exercise, you will be downloading a sample data file from the internet and reading data as the output. Follow these steps:

1. Open a new Jupyter notebook.
2. Now, copy the entire text from https://packt.live/2MIHzhO, save it to a local folder as pg37431.txt, and remember where it is located.
3. Upload the file to your Jupyter notebook by clicking on the Upload button in the top-right corner. Select the pg37431.txt file from your local folder, and then...

Writing files

Now that you have learned how to read the content of a file, you are going to learn how to write content to a file. Writing content to a file is the easiest way for us to store content in our database storage, save our data by writing it to a particular file, and save data on our hard disk. This way, the output will still be available for us after we have closed the terminal or terminated the notebook that contains our program output. This will allow us to reuse the content later with the read() method, which we covered in the previous section, Reading files.

You will still be using the open() method to write to a file, except for when it requires an extra argument to indicate how you want to access and write to the file.

For instance, consider the following:

f = open("log.txt","w+", encoding="utf-8")

The preceding code snippet allows us to open a file in w+, a mode that supports both reading and writing – that is, to update...

Preparing for debugging (defensive code)

In the programming world, a bug refers to defects or problems that prevent code or programs from running normally or as expected. Debugging is the process of finding and resolving those defects. Debugging methods include interactive debugging, unit testing, integration testing, and other types of monitoring and profiling practices.

Defensive programming is a form of debugging approach that ensures the continuing function of a piece of a program under unforeseen circumstances. Defensive programming is particularly useful when we require our programs to have high reliability. In general, we practice defensive programming to improve the quality of software and source code, and to write code that is both readable and understandable.

We can use exceptions to handle unexpected inputs or user actions that can potentially reduce the risk of crashing our programs and make our software behave predictably.

Writing assertions

The first thing...

Plotting techniques

Unlike machines, humans are terrible at understanding data without graphics. Various visualization techniques have been invented to make humans understand different datasets. There are various types of graphs that you can plot, each with its strengths and weaknesses.

Each type of chart is only suitable for a certain scenario, and they shouldn’t be mixed up. Presenting dropped-out customer details for marketing scatter plots is a good example of this. A scatter plot is suitable for visualizing a categorical dataset with numeric values; you will be exploring this further in the following exercise.

To present your data in the best way possible, you should choose the right graph for the right data. In the following exercises, you will be introduced to various graph types and their suitability for different scenarios. You will also learn how to avoid plotting misleading charts.

You will plot each of these graphs in the following exercises and observe...

The don’ts of plotting graphs

In newspapers, blogs, or social media, there are a lot of misleading graphs that make people misunderstand the actual data. We will look at some examples of this in this section and learn how to avoid them.

Manipulating the axis

Imagine that you have three students with three different scores from an exam. Now, you have to plot their scores on a bar chart. There are two ways to do this – the misleading way and the right way:

Figure 4.23 – Chart A (starts from 80) and Chart B (starts from 0)

Looking at Chart A, it will be interpreted that the score of student A is about 10 times higher than students B and C. However, that is not the case. The scores for the students are 96, 81, and 80, respectively. Chart A is misleading because the Y-axis ranges from 80 to 100. The correct Y-axis should range from 0 to 100, as in Chart B. This is simply because the minimum score a student can get is 0, and the maximum...

Summary

In this chapter, you learned how to read and write to a text file using Python, followed by using assertions in defensive programming, which is a way of debugging your code. Finally, you explored different types of graphs and charts to plot data. We discussed the suitability of each plot for different scenarios and datasets while providing suitable examples along the way. We also discussed how to avoid plotting charts that could be misleading.

In the next chapter, you will learn how to use Python to write Object-Oriented Programming (OOP) code. This includes creating classes and instances, using write subclasses that inherit the property of the parent class, and extending functionalities using methods and properties.