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31. Python Programs Using Data Handling

31. Python Programs Using Data Handling

The chapter focuses on writing Python programs for basic data processing and visualization tasks using libraries such as NumPy, Pandas, Matplotlib, and OpenCV. Key topics include performing list operations, calculating statistical measures, plotting data, reading CSV files, and handling image data. These foundational skills are pivotal for understanding artificial intelligence and machine learning workflows.

Sections

Python Programs Using Data Handling and Visualization Libraries

This section provides an introduction to writing Python programs for data handling and visualization, utilizing libraries like NumPy, Pandas, Matplotlib, and OpenCV.

31 Section Overview

Start current section content and materials

31.1 Add Elements of Two Lists

This section covers how to create a Python program that adds corresponding elements from two lists using the zip function.

31.2 Calculate Mean, Median and Mode Using NumPy

This section focuses on calculating statistical values such as mean, median, and mode using the NumPy and SciPy libraries in Python.

31.3 Display a Line Chart from (2,5) to (9,10)

This section introduces how to display a line chart using the Matplotlib library in Python.

31.4 Display a Scatter Chart for Given Points

This section teaches how to create a scatter plot using Python's Matplotlib library to visualize data points.

31.5 Read a CSV File and Display 10 Rows

In this section, students learn how to read a CSV file using Pandas and display the first 10 rows.

31.6 Read a CSV File and Display Its Information

This section covers how to read a CSV file using Pandas and display fundamental information about the dataset.

31.7 Read and Display an Image Using Python

This section teaches how to read and display an image in Python using the OpenCV library.

31.8 Identify the Shape of an Image Using Python

This section teaches how to read an image using Python and identify its dimensions.

Learning Objectives

  • Perform list operations.

  • Calculate statistics like mean, median, and mode.

  • Plot data using line and scatter charts.

  • Read and explore CSV files using Pandas.

  • Handle and analyze images using OpenCV.

Key Concepts

NumPy

A Python library for numerical computing that provides functions for working with arrays and matrices.

Pandas

A data manipulation and analysis library for Python that offers data structures like DataFrames.

Matplotlib

A plotting library for the Python programming language and its numerical mathematics extension NumPy.

OpenCV

An open-source computer vision and machine learning software library that enables image processing capabilities.