--- title: Download NYC Taxi demo data and scripts for embedded R and Python (SQL Server Machine Learning) | Microsoft Docs description: Instructions for downloading New York City taxi sample data and creating a database. Data is used in SQL Server tutorials showing how to embed R and Python in SQL Server stored procedures and T-SQL functions. ms.prod: sql ms.technology: machine-learning ms.date: 10/02/2018 ms.topic: tutorial author: HeidiSteen ms.author: heidist manager: cgronlun --- # NYC Taxi demo data for SQL Server [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md-winonly](../../includes/appliesto-ss-xxxx-xxxx-xxx-md-winonly.md)] This article explains how to obtain sample data for R and Python tutorials for in-database analytics in SQL Server. Data originates from the [NYC Taxi and Limousine Commission](http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml) public data set. We took a snapshot of the dataset and captured one percent of the available data for our demo database. On your system, the database backup file is slightly over 90 MB, providing 1.7 million rows in the primary data table. When you are finished with the steps in this article, the **NYCTaxi_Sample** database is available on your local instance, providing demo data for hands-on learning. The database name must be **NYCTaxi_Sample** if you want to run the demo scripts with no modification. ## Prerequisites You need an internet connection, local administrative rights on the computer, and a database engine instance. To complete this exercise, you should have [SQL Server Management Studio](https://docs.microsoft.com/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-2017) or another tool that can restore database back up files and run T-SQL queries. ## Download demo database The sample database is a backup file hosted by Microsoft. File download begins immediately when you click the link. File size is approximately 90 MB. 1. Click [NYCTaxi_Sample.bak](https://sqlmldoccontent.blob.core.windows.net/sqlml/NYCTaxi_Sample.bak) to download the database backup file. 2. Copy the file to C:\Program files\Microsoft SQL Server\MSSQL-instance-name\MSSQL\Backup folder. 3. In Management Studio, right-click **Databases** and select **Restore Files and File Groups**. 4. Enter *NYCTaxi_Sample* as the database name. 5. Click **From device** and then open the file selection page to select the backup file. Click **Add** to select NYCTaxi_Sample.bak. 6. Select the **Restore** checkbox and click **OK** to restore the database. ## Review database objects Confirm the database objects exist on the [!INCLUDE[ssNoVersion](../../includes/ssnoversion-md.md)] instance using [!INCLUDE[ssManStudioFull](../../includes/ssmanstudiofull-md.md)]. You should see the database, tables, functions, and stored procedures. ![rsql_devtut_BrowseTables](media/rsql-devtut-browsetables.png "rsql_devtut_BrowseTables") ### Objects in NYCTaxi_Sample database The following table summarizes the objects created in the NYC Taxi demo database. |**Object name**|**Object type**|**Description**| |----------|------------------------|---------------| |**NYCTaxi_Sample** | database |Created by the create-db-tb-upload-data.sql script. Creates a database and two tables:

dbo.nyctaxi_sample table: Contains the main NYC Taxi dataset. A clustered columnstore index is added to the table to improve storage and query performance. The 1% sample of the NYC Taxi dataset is inserted into this table.

dbo.nyc_taxi_models table: Used to persist the trained advanced analytics model.| |**fnCalculateDistance** |scalar-valued function | Created by the fnCalculateDistance.sql script. Calculates the direct distance between pickup and dropoff locations. This function is used in [Create data features](sqldev-create-data-features-using-t-sql.md), [Train and save a model](sqldev-train-and-save-a-model-using-t-sql.md) and [Operationalize the R model](sqldev-operationalize-the-model.md).| |**fnEngineerFeatures** |table-valued function | Created by the fnEngineerFeatures.sql script. Creates new data features for model training. This function is used in [Create data features](sqldev-create-data-features-using-t-sql.md) and [Operationalize the R model](sqldev-operationalize-the-model.md).| |**PlotHistogram** |stored procedure | Created by the PlotHistogram.sql script. Calls an R function to plot the histogram of a variable and then returns the plot as a binary object. This stored procedure is used in [Explore and visualize data](sqldev-explore-and-visualize-the-data.md).| |**PlotInOutputFiles** |stored procedure| Created by the PlotInOutputFiles.sql script. Creates a graphic using an R function and then saves the output as a local PDF file. This stored procedure is used in [Explore and visualize data](sqldev-explore-and-visualize-the-data.md).| |**PersistModel** |stored procedure | Created by the PersistModel.sql script. Takes a model that has been serialized in a varbinary data type, and writes it to the specified table. | |**PredictTip** |stored procedure |Created by the PredictTip.sql script. Calls the trained model to create predictions using the model. The stored procedure accepts a query as its input parameter and returns a column of numeric values containing the scores for the input rows. This stored procedure is used in [Operationalize the R model](sqldev-operationalize-the-model.md).| |**PredictTipSingleMode** |stored procedure| Created by the PredictTipSingleMode.sql script. Calls the trained model to create predictions using the model. This stored procedure accepts a new observation as input, with individual feature values passed as in-line parameters, and returns a value that predicts the outcome for the new observation. This stored procedure is used in [Operationalize the R model](sqldev-operationalize-the-model.md).| |**TrainTipPredictionModel** |stored procedure|Created by the TrainTipPredictionModel.sql script. Trains a logistic regression model by calling an R package. The model predicts the value of the tipped column, and is trained using a randomly selected 70% of the data. The output of the stored procedure is the trained model, which is saved in the table nyc_taxi_models. This stored procedure is used in [Train and save a model](sqldev-train-and-save-a-model-using-t-sql.md).| ## Query data for verification As a validation step, run a query to confirm the data was uploaded. 1. In Object Explorer, under Databases, right-click the **NYCTaxi_Sample** database, and start a new query. 2. Run **`select * from dbo.nyctaxi_sample`** to return all 1.7 million rows. ## Next steps NYC Taxi sample data is now available for hands-on learning. + [Learn in-database analytics using R in SQL Server](sqldev-in-database-r-for-sql-developers.md)