mutate()

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!

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?

Yes, if you just want to rename a variable (of any type), rename() is your best bet.

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.

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!

Hi, Valli! All of your questions can be solved using the case_when function inside mutate. You can watch this video from week 7 which has an example of case_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:

mutate(proficiency_level = case_when(
    proficiency_level == "number_level_4" ~ "4",
    proficiency_level == "number_level_3" ~ "3",
    proficiency_level == "number_level_2" ~ "2",
    proficiency_level == "number_level_1" ~ "1"
  )) 

See my other response about case_when, but you can use it to create a categorical variable based on conditional statements, such as

mutate(income_category = case_when(income < 50000 ~ 'Under $50K', 
                                                                  income >= 50000 ~ '$50K +'))

I actually discussed this in R in 3 Months. Here's a video clip from that. Let me know if this helps!

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 run penguins <- penguins |> mutate(observation_station="palmer"), your new dataset will be stored in the penguins object, and you'll see the result it in the data viewer panel. Let me know if this was helpful!

Can you please share the full code you're using all the way from data import to the mutate() code?

hi, thanks for your response! its as follows:

library(tidyverse)

read_csv("penguins_data.csv")
penguins_data
penguins <- read_csv("penguins_data.csv")

penguins |> 
  mutate(height_on_weight_ratio = bill_length_mm / bill_depth_mm)

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?

hi, i did as instructed and it says that the video is posted, thanks!

OK now the second one is working: penguins |> mutate(both_flippers = (flipper_length_mm * 2)) (Not sure why, I didn't change anything, just ran it again.) But I'm still getting the same error for the first

Hi Greg! I've seen this happen before when there were extra pipes in the script. It might be that you ran a code block with an extra pipe somewhere and R kept waiting for the rest of the code, then even if you run just those lines that you copied here - which contain no extra pipes -, R will complain to you. 😅

Hi Queeneth! There are a few options to do that. The first one is to create a new object with your updated dataset with the new variable and view it on the data panel. Another option is to pipe your mutate operation into a print(width=Inf) to show all the columns in the console. Alternatively, if you want to see only that column, you can use select() at the end of your mutate operation. Let us know if this answers your question!

Hi Heather! There are a few options to do that. The first one is to create a new object with your updated dataset with the new variable and view it on the data panel. Another option is to pipe your mutate operation into a print(width=Inf) to show all the columns in the console. Let us know if this answers your question!

Hi Gene! We might need to see your code to debug that. Can you copy it here for us?

There might something before that that's causing the error. When you inspect your dataset, is bill_length_mm numeric? Do you see numbers aligned to the right side in this column?

That's very odd... Could you please share your whole code?