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In this step, you explore the sample data and generate some plots. Later, you learn how to serialize graphics objects in Python, and then deserialize those objects and make plots. First, take a minute to browse the data schema, as we've made some changes to make it easier to use the NYC Taxi data. Each fare record includes payment information such as the payment type, total amount of payment, and the tip amount. The last three columns can be used for various machine learning tasks.
Developing a data science solution usually includes intensive data exploration and data visualization. Because visualization is such a powerful tool for understanding the distribution of the data and outliers, Python provides many packages for visualizing data. The matplotlib module is one of the more popular libraries for visualization, and includes many functions for creating histograms, scatter plots, box plots, and other data exploration graphs.
In this section, you learn how to work with plots using stored procedures. Rather than open the image on the server, you store the Python object plot as varbinary data, and then write that to a file that can be shared or viewed elsewhere. The stored procedure returns a serialized Python figure object as a stream of varbinary data. You cannot view the binary data directly, but you can use Python code on the client to deserialize and view the figures, and then save the image file on a client computer.
Create the stored procedure SerializePlots , if the PowerShell script did not already do so. Now run the stored procedure with no arguments to generate a plot from the data hard-coded as the input query. From a Python client, you can now connect to the SQL Server instance that generated the binary plot objects, and view the plots.
To do this, run the following Python code, replacing the server name, database name, and credentials as appropriate. Make sure the Python version is the same on the client and the server. Also make sure that the Python libraries on your client such as matplotlib are the same or higher version relative to the libraries installed on the server. The output file is created in the Python working directory.
To view the plot, locate the Python working directory, and open the file. The following image shows a plot saved on the client computer. Create data features using T-SQL. The feedback system for this content will be changing soon. Old comments will not be carried over. If content within a comment thread is important to you, please save a copy.
For more information on the upcoming change, we invite you to read our blog post. Review the data First, take a minute to browse the data schema, as we've made some changes to make it easier to use the NYC Taxi data The original dataset used separate files for the taxi identifiers and trip records. The original dataset spanned many files and was quite large.
The current data table has 1,, rows and 23 columns. Trip and fare records Each trip record includes the pickup and drop-off location and time, and the trip distance. The Python script is fairly simple: The Python graphics object is serialized to a pandas DataFrame for output. Using SQL Server authentication: The plots are saved in directory: Next step Step 4: