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Naina Chaturvedi

Welcome to this 1 hour long guided project on Data Visualization using Plotly. Plotly is a python graphing library which is used to make interactive, publication-quality graphs. It allows users to import, copy and paste, or stream data to be analyzed and visualized.

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Welcome to this 1 hour long guided project on Data Visualization using Plotly. Plotly is a python graphing library which is used to make interactive, publication-quality graphs. It allows users to import, copy and paste, or stream data to be analyzed and visualized.

In this project you will learn how to create beautiful visualizations using Plotly constructs. This guided project is for anyone who wants to learn data visualization or already in the data science field.

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What's inside

Syllabus

Project Overview
Welcome to this 1.5 hours long guided project on Data Visualization using Plotly. Plotly is a python graphing library which is used to make interactive, publication-quality graphs. It allows users to import, copy and paste, or stream data to be analyzed and visualized.In this project you will learn how to create beautiful visualizations using Plotly constructs. This guided project is for anyone who wants to learn data visualization or already in the data science field.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Introduces learners to data visualization, which is used by professionals in industry
Taught by Naina Chaturvedi, an expert in data visualization
Emphasizes hands-on learning through interactive visualizations in Plotly
Suitable for both beginners and experienced data science professionals
Covers essential concepts and techniques in data visualization

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Visualization using Plotly with these activities:
Tutorial: Create Interactive Graphs with Plotly
This tutorial will teach you how to create interactive graphs with Plotly, showcasing the power of this library for data presentation.
Show steps
  • Import the necessary Plotly libraries.
  • Load your data into a DataFrame.
  • Create a Plotly figure and add your data.
  • Customize the appearance of your graph.
  • Publish your graph online or save it to your computer.
Practice: Bar Charts with Plotly
Practice creating bar charts using Plotly, reinforcing your understanding of data visualization with this fundamental chart type.
Browse courses on Bar Charts
Show steps
  • Create a Pandas DataFrame with data.
  • Import Plotly and create a bar chart.
  • Set titles, labels, and axis values.
  • Customize the appearance of your chart.
Practice: Scatter Plots with Plotly
Create scatter plots with Plotly to visualize relationships between variables and strengthen your understanding of data visualization.
Browse courses on Scatter Plots
Show steps
  • Import the necessary Plotly libraries.
  • Load your data into a DataFrame.
  • Plotly scatter plot your data.
  • Customize your chart title, labels and legends.
  • Save or display your visualization.
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice: Line Plots with Plotly
Practice creating line plots with Plotly, reinforcing your ability to visualize trends and patterns over time.
Browse courses on Line Plots
Show steps
  • Create a Pandas DataFrame with data.
  • Import Plotly and create a line plot.
  • Set titles, labels, and axis values.
  • Customize colors, markers and line styles.
  • Publish or save your interactive line plot.
Create: Customizing Plotly Charts
Expand your understanding of Plotly by customizing and enhancing its charts, gaining control over the visual presentation and refining your visualizations.
Browse courses on Data Visualization
Show steps
  • Create a scatter plot with Plotly.
  • Customize marker colors, sizes and shapes.
  • Add a title, labels and a legend.
  • Change the chart layout, background and margins.
  • Save or publish your customized chart.
Create: Animated Plotly Charts
Challenge yourself by creating animated Plotly charts, enhancing your ability to visualize dynamic data and bring your insights to life.
Show steps
  • Create a Pandas DataFrame with time-series data.
  • Plotly scatter plot with animated markers.
  • Customize animation speed, colors and shapes.
  • Add a title, labels and a legend.
  • Save or publish your animated visualization.

Career center

Learners who complete Data Visualization using Plotly will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. They use data visualization tools to create interactive dashboards and reports that communicate insights to stakeholders. The course on Data Visualization using Plotly can help Data Analysts develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders.
Data Scientist
Data Scientists use data visualization tools to communicate insights to stakeholders, identify patterns and trends in data, and develop predictive models. The course on Data Visualization using Plotly can help Data Scientists develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Business Intelligence Analyst
Business Intelligence Analysts use data visualization tools to create interactive dashboards and reports that communicate insights to stakeholders. They use data to identify trends and patterns, and to develop recommendations for improving business performance. The course on Data Visualization using Plotly can help Business Intelligence Analysts develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Data Visualization Specialist
Data Visualization Specialists are responsible for designing and developing data visualizations that communicate insights to stakeholders. They use data visualization tools to create interactive dashboards, reports, and presentations. The course on Data Visualization using Plotly can help Data Visualization Specialists develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders.
Data Engineer
Data Engineers are responsible for designing and building data pipelines that collect, clean, and transform data. They use data visualization tools to monitor data quality and to identify trends and patterns. The course on Data Visualization using Plotly can help Data Engineers develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Machine Learning Engineer
Machine Learning Engineers use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate machine learning models. The course on Data Visualization using Plotly can help Machine Learning Engineers develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Software Engineer
Software Engineers use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate software applications. The course on Data Visualization using Plotly can help Software Engineers develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Product Manager
Product Managers use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate product roadmaps. The course on Data Visualization using Plotly can help Product Managers develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Marketing Analyst
Marketing Analysts use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate marketing campaigns. The course on Data Visualization using Plotly can help Marketing Analysts develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Financial Analyst
Financial Analysts use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate financial models. The course on Data Visualization using Plotly can help Financial Analysts develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Operations Research Analyst
Operations Research Analysts use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate operations research models. The course on Data Visualization using Plotly can help Operations Research Analysts develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Market Research Analyst
Market Research Analysts use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate market research studies. The course on Data Visualization using Plotly can help Market Research Analysts develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
User Experience Designer
User Experience Designers use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate user experience designs. The course on Data Visualization using Plotly can help User Experience Designers develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Data Journalist
Data Journalists use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate data-driven stories. The course on Data Visualization using Plotly can help Data Journalists develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.
Statistician
Statisticians use data visualization tools to visualize data, identify patterns and trends, and to develop and evaluate statistical models. The course on Data Visualization using Plotly can help Statisticians develop the skills needed to create visually appealing and informative data visualizations that can effectively communicate insights to stakeholders and support data-driven decision-making.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Visualization using Plotly.
Provides a comprehensive overview of the techniques and tools for creating interactive data visualizations for the web. It covers topics such as data preparation, chart types, and interactivity, and it provides numerous examples of how to use Plotly to create beautiful and informative visualizations.
Provides a comprehensive overview of the principles of data visualization. It covers topics such as data types, visual perception, and chart design, and it provides numerous examples of how to use visualization to communicate data effectively.
Provides a comprehensive overview of the principles of visualization design. It covers topics such as data types, visual perception, and interaction design, and it provides numerous examples of how to use visualization to communicate data effectively.
Provides a practical guide to data visualization. It covers topics such as data exploration, chart types, and visual storytelling, and it provides numerous examples of how to use visualization to communicate data effectively.
Provides a simple and easy-to-understand introduction to data visualization. It covers topics such as data types, chart types, and visual design, and it provides numerous examples of how to use visualization to communicate data effectively.
This classic book provides a comprehensive overview of the principles of data visualization. It covers topics such as data types, visual perception, and chart design, and it provides numerous examples of how to use visualization to communicate data effectively.
Provides a collection of essays from experts in data visualization. It covers topics such as data storytelling, visual design, and the use of visualization in different fields.
Provides a collection of weekly data visualization challenges. It great way to practice your data visualization skills and get feedback from other data visualization enthusiasts.
Provides a comprehensive overview of the ggplot2 package for data visualization in R. It covers topics such as data preparation, chart types, and interactivity, and it provides numerous examples of how to use ggplot2 to create beautiful and informative visualizations.
Provides a collection of recipes for creating different types of visualizations in R. It covers topics such as data preparation, chart types, and interactivity, and it provides numerous examples of how to use R to create beautiful and informative visualizations.
Provides a broad overview of the field of data science. It covers topics such as data collection, data analysis, and data visualization, and it provides numerous examples of how data science is used in different fields.
Provides a comprehensive overview of the field of data science. It covers topics such as data collection, data analysis, and data visualization, and it provides numerous examples of how data science is used in different fields.

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