Day 8: Time to go to NYC 🗽

Hey 

Over the last 7 days, we've learned quite a bit ranging from installing R, packages, plotting data and using arithmetic functions.

Today, we'll be working on something important.

Something you'll be using often at work irrespective of the domain you are in.

I'm talking about data transformation.

But what does this mean?

You see...

The data we receive isn't (in most cases) ready to be analysed. It'll require some checks, format changes, rearrangements and so forth.

For this, we'll need:

  1. A dataset - nycflights13

  2. Tidyverse package (specifically dplyr)

  3. Learn new functions from the dplyr package

Here's a chunk of code you'll need to run for the above:

install.packages("nycflights13")
library(nycflights13)

view(flights)
flights

We won't go into the new functions today as it can be a little overwhelming but I recommend keeping the flights data set ready and familiarising yourself with the different attributes in it

It's a real data set based on flight information of all 336,776 flight departures from New York City in 2013

To read more you can run the code:

?flights

I'll see you tomorrow for the first function of the dplyr package 😁

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Day 9: Data Transformation - Power in disguise

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Day 7: Show that 1+1 = 3