Home Artificial Intelligence Using Slope Charts to Simplify Your Data Visualization When You Could Use a Slope Chart Example: The Tourist Arrivals Scenario

Using Slope Charts to Simplify Your Data Visualization When You Could Use a Slope Chart Example: The Tourist Arrivals Scenario

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Using Slope Charts to Simplify Your Data Visualization
When You Could Use a Slope Chart
Example: The Tourist Arrivals Scenario

Data Visualization, Data Storytelling

Simplify your overwhelmed charts through the use of slope charts: a tutorial in Python Altair

Towards Data Science
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We may plot charts to incorporate as many concepts as possible in our visualization. In consequence, our chart could possibly be difficult to read and distracting. Because of this, before plotting anything, sit in your chair and plan what you would like to communicate. Then, have a look at your data and choose what’s effectively essential to plot. Leave the remainder out of your visualization.

On this tutorial, we’ll see the best way to use slope charts to simplify an awesome trendline. For those who are a knowledge analyst, you would possibly jump out of your chair and get scared because, using a slope chart, you will note a significant loss of knowledge. But I assure you that, in some cases, it would really be price it.

Let’s see the cases where a slope chart could be used.

A slope chart is a kind of line chart showing only the primary and last points, as shown in the next figure.

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A slope chart is especially useful when you would like to know only the slope of your data trend. Thus, slope charts are useful to simplify trendlines. For instance, you possibly can use a slope chart to see if product sales increase or decrease over a period. Imagine that you’ve many trend lines to represent in the identical chart, and you have an interest only in each trend line’s first and last values. You possibly can simplify the chart through the use of a slope chart.

Let’s implement a practical example to see the best way to implement a slope chart in Python Altair, a Python library for data visualization.

Consider the arrivals at tourist accommodation establishments dataset, released as open data by Eurostat. Imagine you would like to compare the tourist arrivals in Portugal with those in the opposite five countries: Germany, France, Italy, the…

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