Strata Scratch Problem Sets

Problem sets, exercises, and educational guides for SQL and python. These exercises are specifically tailored for business and marketing analytics students and novices.

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How to Create Visualizations

Raw data is difficult to understand in its natural form. Data visualization allows you to gain more insights and see patterns rather than just looking directly at the stats, turning a massive amount of data into something meaningful. Luckily, Strata Scratch provides visualization solution that’s easy to use yet powerful enough to help you create beautiful and meaningful plots. This guide will lead you to the steps to start creating your first chart.

Opening Your Dataset in SQL Editor

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Creating the Visualization Chart

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In our example below, let’s choose the distribution - bar chart for our display, and select the following parameters as shown on the image below. Then click Visualize.

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The is_dimension attribute allows you to include variables you want to plot versus the time or date.

The is_date attribute considers the date to plot versus the chosen variables.

The agg_func allows you to perform computations on multiple rows, such as computing the average, sum, count, maximum and minimum values over a set of rows.

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Editing the Chart Filter Options

Strata scratch provides filter options so you can manipulate how you want to visualize your dataset. The left side of the page contains the settings where you can change the chart type and parameters to display.

Naming Your Chart

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Datasource and Chart Type

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Time

Next to the Datasource & Chart Type configuration is the Time menu. Here, you can configure the time related to the attributes included in the chart.

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Query

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You should be able to see the graph as shown below:

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Chart Options

The chart options allow you to configure how you want your plot to be rendered.

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SQL

If you want to add more control to your query, you may add the WHERE and HAVING clauses under the SQL configuration. The WHERE clause is used to filter the rows of data you want to be considered on the plot, while the HAVING clause is used to manipulate groups through a condition.

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Filter

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Saving Your Chart

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