Data Science Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface Data Science Introducing R R Constructs R Tasks R Strings R Read, Write, and Create Data Template Data Exploration Data Wrangling Data Visualisation Statistics ML Template ML Scenarios ML Activities ML Applications ML Algorithms Cluster Analysis Decision Trees Computer Vision Graph Data Privacy Literate Data Science Coding with Style Resources Bibliography Index

CLICK HERE TO VISIT THE UPDATED SURVIVAL GUIDE

RStudio Review

REVIEW Figure 2.3 shows the editor as it appears after we have typed the above commands into the R Script file in the top left pane. We have sent the commands to the R Console to have it run by R. We have done this by ensuring the cursor within the R Script editor is on the same line as the command to be run and then clicking the Run button. We will notice that the command is sent to the R Console in the bottom left pane and the cursor advances to the next line within the R Script editor. After each command is run any text output by the command is displayed in the R Console whilst graphic output is displayed in the Plots tab of the bottom right pane. This is now our first program in R. We can now provide our first observations of the data. It is not too hard to see from the plot that there appears to be quite a strong relationship between the minimum temperature and the maximum temperature: with higher values of the minimum temperature recorded on any particular day we see higher values of the maximum temperature. There is also a clear lower boundary that might suggest, as logic would dictate, that the maximum temperature can not be less than the minimum temperature. If we were to observe data points below this line then we would begin to explore issues with the quality of the data. As data scientists we have begun our observation and understanding of the data, taking our first steps toward immersing ourselves in and thereby beginning to understand the data.

Figure: Running R commands in . The R programming code is written into a file using the editor in the top left pane. With the cursor on the line containing the code we click the Run button to pass the code on to the R Console to have it run by the R Interpreter to produce the plot we see in the bottom right pane.