Podcast
Questions and Answers
Which type of chart is NOT mentioned as part of customizing plots?
Which type of chart is NOT mentioned as part of customizing plots?
What is one of the advanced customization options mentioned for plots?
What is one of the advanced customization options mentioned for plots?
Which feature can help in enhancing the visualization process according to the content provided?
Which feature can help in enhancing the visualization process according to the content provided?
In the context of Matplotlib, which of the following is NOT a basic plotting type?
In the context of Matplotlib, which of the following is NOT a basic plotting type?
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What aspect of plots can be customized through setting ticks and labels?
What aspect of plots can be customized through setting ticks and labels?
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What is one of the main objectives of the Data Visualization using Python course?
What is one of the main objectives of the Data Visualization using Python course?
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Which Python packages are emphasized in the course for data visualization?
Which Python packages are emphasized in the course for data visualization?
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What content is covered regarding the importance of data visualization in business?
What content is covered regarding the importance of data visualization in business?
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What do students learn about data visualization techniques in the course?
What do students learn about data visualization techniques in the course?
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How are students introduced to Python libraries for data visualization?
How are students introduced to Python libraries for data visualization?
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Which visualization techniques are included in Seaborn plotting?
Which visualization techniques are included in Seaborn plotting?
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What is the primary purpose of using Plotly in visualization?
What is the primary purpose of using Plotly in visualization?
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Which of the following is NOT a plotting technique mentioned in the course outcomes?
Which of the following is NOT a plotting technique mentioned in the course outcomes?
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What is a key feature of Violin Plot in data visualization?
What is a key feature of Violin Plot in data visualization?
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Which technique would be suitable for plotting data on a geographical map?
Which technique would be suitable for plotting data on a geographical map?
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What is a distinguishing feature of 3D visualizations in data analysis?
What is a distinguishing feature of 3D visualizations in data analysis?
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When comparing different plotting techniques, what is an important consideration?
When comparing different plotting techniques, what is an important consideration?
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Which plot allows for the representation of distributions alongside summary statistics?
Which plot allows for the representation of distributions alongside summary statistics?
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Study Notes
Course Information
- Course: Computer Science
- Class: S.Y.B.Sc.C.S
- Semester: III
- Course Name: Data Visualization using Python
- Course Code: PUIDC308
- Subject Level: Medium
- Credit Points: 2
Course Objectives
- Expose students to visual representation methods and techniques to enhance understanding of complex data.
- Introduce Python packages for easy creation of readable and understandable graphs, charts, and data visualizations.
Unit 1: Introduction to Data Visualization and Python Libraries for Data Visualization
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Topic 1.1: Introduction: Data Visualization and Its Importance, Need of Data Visualization in Businesses, Future of Data Visualization, Use of Data Visualization in Business Decision Making
- Covers the introduction to data visualization, its importance, necessity in businesses, future trends, and its role in decision-making.
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Topic 1.2: Data Visualization Techniques: Loading libraries, Popular libraries for data visualization in python, introduction to plots in python, Types of Data required for plot, Installing python libraries.
- Details loading libraries, popular libraries for data visualization in Python, introduction to plots, types of data needed for plotting, and the installation of Python libraries.
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Topic 1.3: Defining plot types: bar, line and stacked charts, Drawing a simple sine and cosine plot, Defining axis lengths and limits, Defining plot line styles, properties and format strings
- Explains different plot types, draws simple sine and cosine plots, defines axis lengths, plot styles, properties, and format strings.
Unit 2: Drawing Plots & Customizing Them
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Topic 2.1: Customizing plots: Setting ticks, labels, and grids, Adding a legend and annotations, Moving spines to the center, Setting the transparency and size of axis labels.
- Discusses customizing plots, including setting ticks, labels, grids, legends, annotations, moving spines, and adjusting transparency and axis labels.
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Topic 2.2: Making bar charts with error bars, Making pie charts, Plotting with filled areas, Drawing scatter plots with colored markers.
- Covers creating bar charts with error bars, pie charts, filled areas, and scatter plots.
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Topic 2.3: Advanced Customization: Adding a shadow to the chart line, Adding a data table to the figure, Using subplots, Customizing grids, Creating contour plots, Timelines
- Discusses advanced customization techniques like adding shadows, data tables, subplots, customizing grids, creating contour plots, and timelines.
Unit 3: Matplotlib, Seaborn Plotting and Plotly Plotting
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Topic 3.1: Matplotlib: Line Plot, Bar Plot, Scatter plot, Histogram plot, Stack Plot, Pie chart
- Covers various chart types using Matplotlib.
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Topic 3.2: Seaborn Plotting: Strip plot, Box Plot, Swarm plot, Joint plot,relational plot, HeatMap, Violin Plot, Facet_grid
- Discusses using Seaborn for plotting different charts.
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Topic 3.3: Plotly Plotting: Gnatt Chart, Waterfall Chart, Funnel Chart
- Focus on using Plotly for specific chart types.
Unit 4: Making 3D Visualization and Animations, Plotting Charts with images and maps
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Topic 4.1: 3D Visualization and Animations: Creating 3D bars, Creating 3D histograms, Animating in matplotlib
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Topic 4.2: Plotting with images and maps: Plotting Data on a map using Basemap, Plotting data on a map using Google Map API, Generating Captchas
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Topic 4.3: Animations with Plotly: Bubble Chart, Bar Charts, Adding Control Buttons to Animations, Race Bar Chart
- Covers animations with Plotly and various chart types.
Practical Exercises
- Practical exercises for plotting histograms and bar plots with customization.
- Creating plots with various chart types and adding elements like ticks, labels, and annotations.
- Creating plots for relational, mapped data, and interactive plots/charts.
- Creating exploded and stacked plots, timelines, 3D plots, animations.
- Demonstrating matplotlib and Plotly animations with charts.
- Adding annotations to charts using images and text
- Creating plots on maps using libraries like GoogleMaps API
- Creating captcha generators.
Course Outcomes
- Understanding Data Visualization needs and the use of Python.
- Plotting data using graphs and charts (2D, 3D, animations).
- Analyzing data and using appropriate graphs.
- Customizing plot elements to make data more meaningful.
- Comparing different plotting techniques.
References
- Various articles, books, and online resources are referenced in the course material for plotting, data visualization techniques and Python libraries.
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Description
Test your knowledge on the fundamentals of data visualization and the Python libraries used for creating visual representations. This quiz covers the importance of data visualization in businesses and the techniques to effectively represent data visually. Challenge yourself to understand how data visualization can enhance decision-making processes.
