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As part of the process, it set the password for the PostgreSQL database superuserpostgres` to the valueДЇor simplicity, we are using a weak password at this point and itвЂ™s shown hereДЄnd in the code in plain text. *CHECK for sqlpetr update! Thesp_make_simple_pg function we called above created a container from thepostgres:11 library image downloaded from Docker Hub.

H.4 Documentation for Docker and PostgreSQL.

E.3.5 Disconnect and remove the container.

E.2 Password authentication on the PostgreSQL Docker image.

E Appendix C - PostgreSQL Authentication.

From the adventureworks2012 database. windows#

D Appendix B - Additional technical details for Windows users.

C.1.3 Restore the adventureworks database using pgAdmin.

C.1.2 Restore the dvdrental database at the command line.

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C.1.1 Download the adventureworks database.

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C Appendix E - Install adventureworks on your own machine.A.8.5 Using SQLite to simulate an enterprise DBMS.A.8.4 Connecting the R and DBMS environments.A.8.3 PostgreSQL and connection parameters.A.8.2 Data mapping between R vs SQL data types.A.7.4 Transaction Control Language (TCL).A.5.5 Hosting Docker on Windows machines.A.2 Your computer and its operating system.A.1 The big picture: R and the Docker / PostgreSQL playground on your machine.12.4 Characterizing how things are named.12.3.2 What data types are found in the database?.12.3.1 What is the difference between a VIEW and a BASE TABLE?.12.3 What columns do those tables contain?.12.2.3 What tables are in the database?.12.2.2 Contents of the information_schema.12.1.1 Explore the vsalelsperson and vsalespersonsalesbyfiscalyearsdata views.12.1 Views trick parked here for the time being.12 Getting metadata about and from PostgreSQL.11.5 Revise the view to summarize by quarter not fiscal year.11.4 Compare the official view and the dplyr output.11.3.4 Selecting relevant tables and columns.11.3.1 Use a view just like any other table.11.3 Unpacking the elements of a view in the Tidyverse.11.2.2 Rely on вЂ“ and be critical of вЂ“ views.11.1 Setup our standard working environment.10.2 Disconnect from the database and stop Docker.10.1.4 Many handy R functions canвЂ™t be translated to SQL.10.1.2 Time-based, execution environment issues.10 Lazy Evaluation and Execution Environment.9.3.1 Create a black box query for experimentation.9.2 R is lazy and comes with guardrails.8.10 Disconnect from the database and stop Docker.8.9.4 Monthly Sales by Order Type with corrected dates вЂ“ relative to a trend line.8.9.2 Define and store a PostgreSQL function to correct the date.8.9.1 Define a date correction function in R.8.9 Correcting the order date for Sales Reps.8.8 Detect and diagnose the day of the month problem.8.7.3 Compare monthly lagged data by Sales Channel.8.7.2 Monthly variation compared to a trend line.8.7.1 Retrieve monthly sales with the onlineorderflag.8.7 Impact of order type on monthly sales.8.6.4 Comparing average order size: Sales Reps to Online orders.8.6.1 Add onlineorderflag to our annual sales query.8.5.2 Comparing dollars and orders to a base year.8.4.1 Annual summary of sales, number of transactions and average sale.8.3 The overall AdventureWorks sales picture.8.1 Setup our standard working environment.8 Asking Business Questions From a Single Table.7.6 Disconnect from the database and stop Docker.

7.5.5 The skim function in the skimr package.

7.5.4 The glimpse function in the tibble package.

7.5.2 Always look at your data with head, View, or kable.

7.3 Translating dplyr code to SQL queries.

7.2.4 Retrieving random rows from the DBMS.

7.2.3 Controlling the number of rows returned with collect().

7.2.2 Create a pointer to a table that can be reused.

7.2 Methods for downloading a single table.

6.5 Disconnect from the database and stop Docker.

6.4 Anatomy of a dplyr connection object.

6.3 Set schema search path and list its contents.

6.1 Verify that Docker is up and running, and start the database.

6 Connecting to the database with R code.

5.3 Disconnect from the database and stop Docker.

5.2.1 Connect with Postgres using the Sys.getenv function.

5.1 Set up the adventureworks Docker container.

5 Securing and using your dbms log-in credentials.

4.10 Using the adventureworks container in the rest of the book.

4.9 Cleaning up: diconnect from the database and stop Docker.

4.8 Investigate the database using Rstudio.

4.5 Run the adventureworks Docker Image.

4.4 Build the adventureworks Docker image.

4.2 Verify that Docker is up, running, and clean up if necessary.

4 Create and connect to the adventureworks database in PostgreSQL.

3.1.3 Problems that we address in the book.

3.1.1 The Challenge: Investigating a question using an organizationвЂ™s database.

3.1 The BookвЂ™s Challenge: goals, context and expectations.

1.1 Using R to query a DBMS in your organization.