14.9 Types of Plot in Matplotlib

Duration: 4 min

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Inside: a video lesson and guided study material.

Module outline

  1. HPSC Interview Preparation: Interview Preparation
  2. Python Language: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis, DSA using Python
  3. Data Structure & Algorithms: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Algorithm Analysis, Sorting Algorithms, Minimum Spanning Trees, Time Complexity Analysis, Graph Theory, Shortest Path Algos
  4. Computer Networks: Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security
  5. Computer System & Organisation: Basics of COA, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design, Programming the Basic Computer
  6. Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, SQL, File Organization & Indexing, Transaction Management, Concurrency Control
  7. Operating Systems: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling
  8. Digital Logic & Circuits: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  9. Theory Of Computation: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Pushdown Automata & CFG, Turing Machines, Moore & Mealy Machines
  10. 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
  11. Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management, Data Warehousing & Mining
  12. Introduction to Emerging Trends: Emerging Tech Trends
  13. Digital Society & Cyber Law: Society, Law & Ethics
  14. HPSC PGT Previous Year Paper:
  15. HPSC Assistant Professor Previous Year Paper:
  16. Live Sessions: HPSC Live Sessions, EMRS TGT/PGT Live Class
  17. Full Mock Test:
  18. HPSC PGT - MOCK Test Series:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video provides a tutorial on creating four different types of plots using the Matplotlib library in Python. The instructor begins by introducing the topic with a title slide, then systematically demonstrates how to create a line plot, a bar chart, a scatter plot, and a pie chart. For each plot type, the video displays the corresponding Python code, including the necessary library import (plt), data definition, and plotting function (e.g., plt.plot(), plt.bar(), plt.scatter(), plt.pie()). The instructor also shows how to add labels and titles to the plots. Throughout the demonstration, the instructor uses a digital whiteboard to draw the resulting graphs, illustrating the visual output of the code. The video concludes with a 'Thank You' slide.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video starts with a title slide that reads 'Types of Plots in Matplotlib'. The instructor then introduces the first type of plot, the Line Plot. The on-screen code shows the necessary imports and the function call `plt.plot(x, y)`. The instructor explains that this function is used to create a line plot, and he draws a simple line graph on the digital whiteboard to illustrate the concept. The code snippet includes `plt.show()` to display the plot.

  2. 2:00 – 4:12 02:00-04:12

    The instructor transitions to the second plot type, the Bar Chart. The on-screen code defines two lists, `names = ["A", "B", "C"]` and `marks = [80, 90, 85]`, and uses `plt.bar(names, marks)` to create a bar chart. The instructor draws the corresponding bar chart on the whiteboard, labeling the x-axis with 'A', 'B', 'C' and the y-axis with 'Marks'. He then moves to the third type, the Scatter Plot, showing the code `plt.scatter(x, y)` and drawing a scatter plot with several data points. Finally, he demonstrates the Pie Chart, with code `plt.pie(sizes, labels=labels, autopct='%1.1f%%')` where `sizes = [40, 30, 20, 10]` and `labels = ["Python", "Java", "C", "Others"]`. He draws a pie chart with four slices and labels it 'Programming Language Usage'. The video ends with a 'Thank You' slide.

The video provides a clear, step-by-step guide to creating four fundamental types of data visualizations in Python using Matplotlib. It follows a consistent structure for each plot: presenting the code, explaining the function, and drawing the resulting graph. This methodical approach effectively teaches the syntax and visual outcome of each plot type, making it a useful resource for beginners learning data visualization.

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