Looks good! Now finish the job by adding in the data from the other datasets.

Instructions

• Append the remaining datasets in the order of the years they describe.
  • Select all non-header rows from Hud_2007.csv and append to combined_hud.csv.
  • Select all non-header rows from Hud_2013.csv and append to combined_hud.csv.
• Display the last 10 rows of combined_hud.csv and verify that they match the last 10 rows of Hud_2013.csv

~$ wc -l Hud_2007.csv

 ~$ tail -42729 Hud_2007.csv >> combined_hud.csv 

~$ wc -l Hud_2013.csv

~$ tail -64535 Hud_2013.csv >> combined_hud.csv

/home/dq$ wc -l Hud_2007.csv                                                    

42730 Hud_2007.csv                                                              

/home/dq$ tail -42729 Hud_2007.csv >> combined_hud.csv                          

/home/dq$ wc -l Hud_2013.csv                                                    

64536 Hud_2013.csv                                                              

/home/dq$ tail -64535 Hud_2013.csv >> combined_hud.csv                          

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5: Counting

Now that you have a consolidated dataset, you can start to answer basic questions on the entire dataset.

Instructions

• Count and display the number of lines in combined_hud.csvcontaining 1980-1989

/home/dq$ grep '1980-1989' combined_hud.csv |wc -l                              

13672  

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6: Next Steps

In this challenge, you learned about a few useful commands for exploring files and practiced data munging from the command line. Next in this course is a guided project where you'll explore how to create Python scripts from the command line for more robust and reusable logic