Changes Over Time: Line, Multiple Line & Area Charts

Charting data that changes over time is a fundamental skill for data analysts, researchers, and decision-makers in various fields. Understanding how to chart different kinds of data that change over time can help you to identify trends, patterns, and insights, and communicate your findings effectively to your audience. In this video, you'll learn ways how to chart different kinds of data that change over time.
One of the most common types of data that changes over time is numerical data. For example, you may have sales data that changes from month to month, stock prices that fluctuate throughout the day, or weather data that varies over the course of a year. Line charts are typically used to represent numerical data that changes over time, and they are effective in showing trends and patterns in the data.
Another type of data that changes over time is categorical data. Categorical data represents information that can be divided into distinct categories or groups, such as demographic data or survey responses. Bar charts and stacked bar charts are commonly used to represent categorical data that changes over time, and they can help you to compare different categories or groups over time.
Time series data is another type of data that changes over time, and it is often used in finance, economics, and other fields to analyze trends and forecast future values. Time series data can be represented using line charts, area charts, or scatter plots, depending on the nature of the data and the story you want to tell.
Finally, qualitative data that changes over time, such as social media sentiment or customer feedback, can be represented using word clouds, heat maps, or other visualization techniques that highlight changes in sentiment or usage over time.
By understanding how to chart different kinds of data that change over time, you can gain valuable insights into patterns and trends, identify opportunities for improvement or growth, and effectively communicate your findings to your audience. With the right tools and techniques, you can transform raw data into actionable insights that drive decision-making and success.
More resources to explore:
Page: How to choose the right chart for your data
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Blog: Data visualization best practices
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Blog: Chart do's and don'ts: The ultimate data visualization guide
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Blog: Data visualization tips
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Awesome! Thanks for bringing this project to life!