16.7 Matplotlib Bars

Duration: 3 min

This video lesson is available to enrolled students.

Return to /learn/MPPSC-ASSISTANT-PROFESSOR-COMPUTER-SCIENCE-PAPER-2/python/file-handling-data-analysis/data-visualization/asset-167-matplotlib-bars after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. About Course: About the Course
  2. Paper 1 | General Studies: State Wise GK
  3. Paper 1 | Information and Communication Technology: Role of Internet and Web Services, Security in Mobile and Wireless Computing
  4. Paper 1 | Current Affairs: GK- Current Affairs
  5. Paper 2 | Discrete Mathematical Structure: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic, Probability
  6. Paper 2 | Digital Computer Organization And Architecture: Number System, Number Representation, Sequential Circuits, Combinational Circuit, Basics of COA, Floating Point Rep, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Register Transfer and Microoperations, Control Unit Design, Programming the Basic Computer
  7. Paper 2 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  8. Paper 2 | Programming Languages & Object-Oriented Programming Concepts: Java, OOPS with C++, Java Fundamentals, Array, String, IO & References
  9. Paper 2 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis
  10. Paper 2 | Data Structure And Algorithms: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Minimum Spanning Trees, Advanced Algorithms
  11. Paper 2 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Unix OS
  12. Paper 2 | Theory Of Computation: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines, Complexity Theory
  13. Paper 2 | Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment
  14. Paper 2 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, Relational Algebra, SQL, Transaction Management, Concurrency Control, Database Recovery, Database Security & Authorization, Enhanced Data Models
  15. Paper 2 | Computer Network And Information Security: Introduction to CN, Data Communication, Application Layer, Hardware basics, Cyber Threats and Malware Attacks, Network Security, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP
  16. Paper 2 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  17. Paper 2 | Current Trends & Technologies: Emerging Tech Trends, Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Planning, Multi Agent Systems, Fuzzy Sets, Natural Language Processing, Artificial Neural Networks, Genetic Algorithms, Artificial Intelligence, Data Warehousing & Mining, Electronic Data Interchange and E-Commerce, Terms & Abbreviations
  18. Paper 2 | Full Length Mock Tests:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This video is a Python programming tutorial focused on creating bar charts using the Matplotlib library. The instructor begins by introducing the `plt.bar()` function, demonstrating its basic syntax with a simple example that plots categories A, B, C, and D with corresponding values 13, 8, 12, and 7. The lesson progresses to show how to create horizontal bar charts by using the `plt.barh()` function, which swaps the x and y axes. The tutorial then covers customization options, including setting the color of the bars using the `color` parameter and adjusting the width of the bars with the `width` parameter. Finally, the instructor explains how to control the height of the bars using the `height` parameter, which is particularly relevant for horizontal bars. The entire lesson is presented on a digital whiteboard with code snippets and a live graph, providing a clear, step-by-step guide for beginners.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video starts with a title slide for a Python tutorial on 'Matplotlib Bars'. The instructor introduces the topic and then transitions to a slide titled 'Creating Bars'. On this slide, the instructor explains that the `plt.bar()` function is used to draw bar graphs. The code example shown includes importing `matplotlib.pyplot` as `plt` and `numpy` as `np`. The example defines two arrays: `x` for the categories (['A', 'B', 'C', 'D']) and `y` for the values ([13, 8, 12, 7]). The instructor then demonstrates how to create the bar chart with `plt.bar(x, y)` and display it with `plt.show()`. The resulting vertical bar chart is visible on the right, with the x-axis labeled A, B, C, D and the y-axis showing the values. The instructor points to the code and the chart, explaining the process.

  2. 2:00 – 2:41 02:00-02:41

    The instructor moves to a new slide titled 'Horizontal Bars'. The code on the screen is updated to use the `plt.barh()` function, which creates horizontal bars. The instructor explains that this function is used to draw horizontal bar graphs, and the x and y axes are swapped. The same data arrays `x` and `y` are used, but the chart now displays the bars horizontally. The instructor then transitions to a slide titled 'Bar Color', where the `color` parameter is introduced. The code is modified to `plt.bar(x, y, color='red')`, and the instructor points to the code, explaining that this will color the bars red. Next, the 'Bar Width' slide is shown, where the `width` parameter is introduced. The code is updated to `plt.bar(x, y, width=0.1)`, and the instructor draws a diagram to illustrate how the width of the bars is reduced. Finally, the 'Bar Height' slide is presented, where the `height` parameter is explained for horizontal bars. The code is updated to `plt.bar(x, y, height=0.1)`, and the instructor explains that this parameter controls the height of the bars, which is the vertical dimension in a horizontal bar chart.

The video provides a comprehensive, step-by-step tutorial on creating and customizing bar charts in Python using Matplotlib. It begins with the fundamental concept of the `plt.bar()` function for vertical bars, then logically progresses to the `plt.barh()` function for horizontal bars. The lesson effectively demonstrates key customization parameters, including `color`, `width`, and `height`, showing how each one modifies the appearance of the chart. The clear progression from basic to more advanced features, supported by live code and visual examples, makes it an effective learning resource for understanding data visualization with Matplotlib.

Loading lesson…