mutate()
This lesson is called mutate(), part of the Fundamentals of R course. This lesson is called mutate(), part of the Fundamentals of R course.
Transcript
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View code shown in video
# Load Packages -----------------------------------------------------------
library(tidyverse)
# Import Data -------------------------------------------------------------
penguins <- read_csv("penguins.csv")
# mutate() ----------------------------------------------------------------
# We use mutate() we make new variables or change existing ones.
# We can use mutate() in three ways.
# 1. Create a new variable with a specific value:
penguins |>
mutate(continent = "Antarctica")
# 2. Create a new variable based on other variables:
penguins |>
mutate(body_mass_lbs = body_mass_g / 453.6)
# 3. Change an existing variable
penguins |>
mutate(bill_length_mm = bill_length_mm + 1)
Your Turn
# Load Packages -----------------------------------------------------------
# Load the tidyverse package
library(tidyverse)
# Import Data -------------------------------------------------------------
# Download data from https://rfor.us/penguins
# Copy the data into the RStudio project
# Create a new R script file and add code to import your data
penguins <- read_csv("penguins.csv")
# mutate() ----------------------------------------------------------------
# Use mutate() to create a variable called observation_station and set its value to "Palmer"
# YOUR CODE HERE
# 2. Create a new variable based on other variables:
# YOUR CODE HERE
# 3. Change an existing variable
# YOUR CODE HERE
Learn More
To learn more about the mutate()
function, check out Chapter 3 of R for Data Science.
Have any questions? Put them below and we will help you out!
Course Content
34 Lessons
1
The Grammar of Graphics
04:39
2
Scatterplots
03:46
3
Histograms
05:47
4
Bar Charts
06:37
5
Setting color and fill Aesthetic Properties
02:39
6
Setting color and fill Scales
05:40
7
Setting x and y Scales
03:09
8
Adding Text to Plots
07:32
9
Plot Labels
03:57
10
Themes
02:19
11
Facets
03:12
12
Save Plots
02:57
13
Bring it All Together (Data Visualization)
06:42
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Rob Schoen • October 13, 2023
There are some things I'd like to do for part 3 of the assignment (change an existing variable) that I don't know how to do. For example, I'd like to change the "sex" variable to be called "female" and then change the values from female-> 1, male -> 0, and NA -> NA. How can I find the functions that will enable me to do that?
Libby Heeren Coach • October 14, 2023
Hey, Rob! The case_when() function will allow you to change values from female-> 1, male -> 0, and NA -> NA and the rename() function will allow you to rename a column. You'll get to these functions in time throughout the course once you get to the advanced data wrangling sections, but if you'd like to check out an older video clip (videos are in the process of being replaced) you can see one about case_when here.
If you'd like to try out the rename() function, try adding a line to your dplyr code like this: penguins |> mutate(continent = "Antarctica") |> rename(sex_numeric = sex_v2)
The syntax works like this here: rename(new_column_name = old_column_name)
Please feel free to message me on Discord with any questions!
Gabby Bachhuber • March 19, 2024
Is it not possible to mutate categorical variable names? I tried to mutate "species", but perhaps that isn't possible (it generated an error). I think I need to use rename() instead, as noted below?
David Keyes Founder • March 19, 2024
Yes, if you just want to rename a variable (of any type),
rename()
is your best bet.Charles Obiorah • March 25, 2024
Hi David, My progress has been slowed down by how my video plays and stops. It is no longer flowing seamlessly and I wonder where I have to touch the settings. i tried another network provider and it seems to persist. Next, I tried the assignment of creating a new variable and changing an existing one. While I could see the new variable in a new column Antarctica, I could not see the new column body_mass_lbs as it is in your video. Note that I saw this on the Console:
David Keyes Founder • March 26, 2024
Sorry about the website issues. We're working to resolve these ASAP.
To answer your question, I'd need to see your code. Please paste it in the comment.
Valliappan Muthu • April 24, 2024
Hello, I have a question
Say I have a variable “plant” and which can be either “tree” or “shrub “. Coded the data in excel or spss as 1 and 0 for tree and shrub
If I want to analyse data of only “1” that is only “trees”
What should I do?
I have day where the information is coded as 1 and 0
If I want to filter these observations containing “1”
Valliappan Muthu • April 24, 2024
Hello Sorry there was an error in my code and question number 2 was resolved when I used the code Filter (plant == “1”)
I still want to know about the first question
Thanks!
Libby Heeren Coach • April 25, 2024
Hi, Valli! All of your questions can be solved using the
case_when
function insidemutate
. You can watch this video from week 7 which has an example ofcase_when
and also lists resources below the video with further examples of how to use it in different ways.An example of it in David's code during Week 7 is this:
Valliappan Muthu • April 24, 2024
Sorry I have been coming with questions from old lessons After I started cleaning the data which I work on
Kindly suggest the ways to categorise continued variable E.g say I have income of 100 individuals as a continuous variable Now I want to analyse my parameters of interest between income more than 1000$ and less than 1000$
Can I use mutate to create categories from pre existing continuous variable?
Libby Heeren Coach • April 25, 2024
See my other response about
case_when
, but you can use it to create a categorical variable based on conditional statements, such asDenny Lu • July 10, 2024
Why does the code sometimes need quotations and other times not?
David Keyes Founder • July 11, 2024
I actually discussed this in R in 3 Months. Here's a video clip from that. Let me know if this helps!
Imelda Akurut • September 25, 2024
Hi David , i need some help , i posted the code .....penguins |> mutate(observation_station="palmer")..... for mutate and it doesn't show in the data , i get this instead
Gracielle Higino Coach • September 26, 2024
Hi Imelda! I might need a bit more of information to give you a more definitive answer, but I suspect that you're not seeing changes in the dataset because you're not assigning the operation to an object. If you just run
penguins |> mutate(observation_station="palmer")
, you'll get a sample of your dataset in the console panel, with the text you've mentioned below it. However, if you runpenguins <- penguins |> mutate(observation_station="palmer")
, your new dataset will be stored in thepenguins
object, and you'll see the result it in the data viewer panel. Let me know if this was helpful!Samreen Chhabra • November 6, 2024
i keep running into the same error as the one few have mentioned before, and do not see the mutated rows at all!
this is the code i am using:
would love some help here!
David Keyes Founder • November 7, 2024
Can you please share the full code you're using all the way from data import to the
mutate()
code?Samreen Chhabra • November 7, 2024
hi, thanks for your response! its as follows:
David Keyes Founder • November 7, 2024
Ok, I'm not seeing anything off there. I'm guessing, though, by the message you're getting, that the
height_on_weight_ratio
variable is there, just not showing up. Could you record a quick video showing yourself running your code and let me know when it's posted?Samreen Chhabra • November 11, 2024
hi, i did as instructed and it says that the video is posted, thanks!