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Python for Data Visualization: The Complete Masterclass

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Python for Data Visualization: The Complete Masterclass, available at $29.99, has an average rating of 4.51, with 51 lectures, based on 115 reviews, and has 39900 subscribers.

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You will learn about Understanding the importance of data visualization, its role in data analysis, and the principles of effective visualization design. Exploring popular Python libraries such as Matplotlib, and Seaborn, and learning how to leverage their functionalities to create a variety of visualizations. Understanding how to customize and enhance visualizations by adjusting colors, labels, titles, legends, and other visual elements. Understanding the principles of effective data storytelling and best practices for designing clear, impactful, and informative data visualizations. This course is ideal for individuals who are Individuals who are new to data visualization and have little or no prior experience with Python or programming. or Professionals working with data who want to enhance their data visualization skills to effectively communicate insights and findings. or Individuals with programming experience who wish to expand their knowledge and incorporate data visualization into their skill set. or Business Professionals: Managers, executives, and professionals from non-technical backgrounds who want to gain a practical understanding of data visualization to make informed decisions and effectively communicate data-driven insights. or Students and Researchers: Those studying data science, computer science, statistics, or related fields who want to strengthen their proficiency in visualizing and presenting data using Python. or Anyone Interested in Data Visualization: Enthusiasts, hobbyists, or curious learners who have an interest in data visualization and want to explore the capabilities of Python for creating impactful visualizations. It is particularly useful for Individuals who are new to data visualization and have little or no prior experience with Python or programming. or Professionals working with data who want to enhance their data visualization skills to effectively communicate insights and findings. or Individuals with programming experience who wish to expand their knowledge and incorporate data visualization into their skill set. or Business Professionals: Managers, executives, and professionals from non-technical backgrounds who want to gain a practical understanding of data visualization to make informed decisions and effectively communicate data-driven insights. or Students and Researchers: Those studying data science, computer science, statistics, or related fields who want to strengthen their proficiency in visualizing and presenting data using Python. or Anyone Interested in Data Visualization: Enthusiasts, hobbyists, or curious learners who have an interest in data visualization and want to explore the capabilities of Python for creating impactful visualizations.

Enroll now: Python for Data Visualization: The Complete Masterclass

Summary

Title: Python for Data Visualization: The Complete Masterclass

Price: $29.99

Average Rating: 4.51

Number of Lectures: 51

Number of Published Lectures: 51

Number of Curriculum Items: 51

Number of Published Curriculum Objects: 51

Original Price: $79.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understanding the importance of data visualization, its role in data analysis, and the principles of effective visualization design.
  • Exploring popular Python libraries such as Matplotlib, and Seaborn, and learning how to leverage their functionalities to create a variety of visualizations.
  • Understanding how to customize and enhance visualizations by adjusting colors, labels, titles, legends, and other visual elements.
  • Understanding the principles of effective data storytelling and best practices for designing clear, impactful, and informative data visualizations.

Who Should Attend

  • Individuals who are new to data visualization and have little or no prior experience with Python or programming.
  • Professionals working with data who want to enhance their data visualization skills to effectively communicate insights and findings.
  • Individuals with programming experience who wish to expand their knowledge and incorporate data visualization into their skill set.
  • Business Professionals: Managers, executives, and professionals from non-technical backgrounds who want to gain a practical understanding of data visualization to make informed decisions and effectively communicate data-driven insights.
  • Students and Researchers: Those studying data science, computer science, statistics, or related fields who want to strengthen their proficiency in visualizing and presenting data using Python.
  • Anyone Interested in Data Visualization: Enthusiasts, hobbyists, or curious learners who have an interest in data visualization and want to explore the capabilities of Python for creating impactful visualizations.

Target Audiences

  • Individuals who are new to data visualization and have little or no prior experience with Python or programming.
  • Professionals working with data who want to enhance their data visualization skills to effectively communicate insights and findings.
  • Individuals with programming experience who wish to expand their knowledge and incorporate data visualization into their skill set.
  • Business Professionals: Managers, executives, and professionals from non-technical backgrounds who want to gain a practical understanding of data visualization to make informed decisions and effectively communicate data-driven insights.
  • Students and Researchers: Those studying data science, computer science, statistics, or related fields who want to strengthen their proficiency in visualizing and presenting data using Python.
  • Anyone Interested in Data Visualization: Enthusiasts, hobbyists, or curious learners who have an interest in data visualization and want to explore the capabilities of Python for creating impactful visualizations.

Use Python to build spectacular data visualisations and fascinate your audience. Join our transformative masterclass to master Python for data visualisation.

Visual storytelling is crucial in a data-driven environment. This comprehensive Python course will teach you how to turn raw data into stunning visualisations.

You’ll learn how to maximise Matplotlib, Seaborn, and Plotly via immersive hands-on activities and real-world examples. Python opens us a universe of data visualisation possibilities, from simple charts to heatmaps, time series visualisation, and geospatial mapping.

As you master every component of your visualisations, you may customise them to create stunning masterpieces that fascinate and engage your audience. Interactive dashboards will let people explore data and discover hidden insights.

This masterclass will teach data analysts, corporate leaders, researchers, and aspiring data enthusiasts how to use the most popular data visualisation programming language to have a lasting effect. Practical projects, real-world case studies, and industry experts will give you the confidence and skills to tackle any Python data visualisation challenge.

Avoid boring presentations that don’t tell your data’s story. Join us to use Python to visualise difficult data in beautiful, persuasive ways. Become a Python data visualisation expert and boost your career. Enrol today and unleash your creativity with Python.

Course Curriculum

Chapter 1: Setup & Installation

Lecture 1: Installing the Anaconda Navigator

Lecture 2: Installing Matplotlib, seaborn & cufflinks

Lecture 3: Reading data from a csv file with pandas

Lecture 4: Explaining Matplotlib libraries

Lecture 5: Course Materials

Chapter 2: Plotting Line Plots with matplotlib

Lecture 1: Changing the axis scales

Lecture 2: Label Styling

Lecture 3: Adding a legend

Lecture 4: Changing colors, linestyles, linewidth and markers

Lecture 5: Adding a grid to the chart

Lecture 6: Filling only a specific area

Lecture 7: Filling area on line plots and filling only specific area

Lecture 8: Changing fill color of different areas (negative vs positive for example)

Chapter 3: Plotting Histograms & Bar Charts with matplotlib

Lecture 1: Changing edge color and adding shadow on the edge

Lecture 2: Adding legends, titles, location and rotating pie chart

Lecture 3: Histograms vs Bar charts (Part 1)

Lecture 4: Histograms vs Bar charts (Part 2)

Lecture 5: Changing edge color of the histogram

Lecture 6: Changing the axis scale to log scale

Lecture 7: Adding median to histogram

Lecture 8: Advanced Histograms and Patches (Part 1)

Lecture 9: Advanced Histograms and Patches (Part 2)

Lecture 10: Overlaying bar plots on top of each other (Part 1)

Lecture 11: Overlaying bar plots on top of each other (Part 2)

Lecture 12: Creating Box and Whisker Plots

Chapter 4: Plotting Stack Plots & Stem Plots

Lecture 1: Plotting a basic stack plot

Lecture 2: Plotting a stem plot

Lecture 3: Plotting a stack plot od data with constant total

Chapter 5: Plotting Scatter Plots with matplotlib

Lecture 1: Plotting a basic scatter plot

Lecture 2: Changing the size of the dots

Lecture 3: Changing colors of markers

Lecture 4: Adding edges to dots

Chapter 6: Time Series Data Visualization with matplotlib

Lecture 1: Using the Python datetime module

Lecture 2: Connecting data points by line

Lecture 3: Converting string dates using the .to_datetime() pandas method

Lecture 4: Plotting live data using FuncAnimation in matplotlib

Chapter 7: Creating multiple subplots

Lecture 1: Setting up the number of rows and columns

Lecture 2: Plotting multiple plots in one figure

Lecture 3: Getting separate figures

Lecture 4: Saving figures to your computer

Chapter 8: Plotting charts using seaborn

Lecture 1: Introduction to seaborn

Lecture 2: Working on hue, style and size in seaborn

Lecture 3: Subplots using seaborn

Lecture 4: Line plots

Lecture 5: Cat plots

Lecture 6: Jointplot, pair plot and regression plot

Lecture 7: Controlling Plotted Figure Aesthetics

Chapter 9: Plotly and Cufflinks

Lecture 1: Installation and Setup

Lecture 2: Line, Scatter, Bar, box and area plot

Lecture 3: 3D plots, spread plot and hist plot, bubble plot, and heatmap

Chapter 10: BONUS Section – Don't Miss Out

Lecture 1: BONUS Section – Don't Miss Out

Instructors

  • Meta Brains
    Meta Brains
    Let's code & build the metaverse together!

Rating Distribution

  • 1 stars: 2 votes
  • 2 stars: 3 votes
  • 3 stars: 14 votes
  • 4 stars: 33 votes
  • 5 stars: 63 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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