differences for PR #908

04-data-structures-part1.md

@@ -237,30 +237,29 @@ No matter how
 complicated our analyses become, all data in R is interpreted as one of these
 basic data types. This strictness has some really important consequences.
 
-A user has added details of another cat. This information is in the file
-`data/feline-data_v2.csv`.
+A user has added details of another cat. We can add an additional row to our cats `data.frame` using `rbind`.
 
 
 ``` r
-file.show("data/feline-data_v2.csv")
+additional_cat <- data.frame(coat = "tabby", weight = "2.3 or 2.4", likes_catnip = 1)
+cats2 <- rbind(cats, additional_cat)
+cats2
 ```
 
-
-``` r
-coat,weight,likes_catnip
-calico,2.1,1
-black,5.0,0
-tabby,3.2,1
-tabby,2.3 or 2.4,1
+``` output
+    coat     weight likes_catnip
+1 calico        2.1            1
+2  black          5            0
+3  tabby        3.2            1
+4  tabby 2.3 or 2.4            1
 ```
 
-Load the new cats data like before, and check what type of data we find in the
-`weight` column:
+Let's check what type of data we find in the
+`weight` column of our new object:
 
 
 ``` r
-cats <- read.csv(file="data/feline-data_v2.csv")
-typeof(cats$weight)
+typeof(cats2$weight)
 ```
 
 ``` output
@@ -272,11 +271,11 @@ we did on them before, we run into trouble:
 
 
 ``` r
-cats$weight + 2
+cats2$weight + 2
 ```
 
 ``` error
-Error in cats$weight + 2: non-numeric argument to binary operator
+Error in cats2$weight + 2: non-numeric argument to binary operator
 ```
 
 What happened?
@@ -292,14 +291,14 @@ is written by the `str()` function:
 
 
 ``` r
-str(cats)
+str(cats2)
 ```
 
 ``` output
 'data.frame':	4 obs. of  3 variables:
  $ coat        : chr  "calico" "black" "tabby" "tabby"
  $ weight      : chr  "2.1" "5" "3.2" "2.3 or 2.4"
- $ likes_string: int  1 0 1 1
+ $ likes_catnip: num  1 0 1 1
 ```
 
 *Data frames* are composed of rows and columns, where each column has the
@@ -555,8 +554,7 @@ Create a new script in RStudio and copy and paste the following code. Then
 move on to the tasks below, which help you to fill in the gaps (\_\_\_\_\_\_).
 
 ```
-# Read data
-cats <- read.csv("data/feline-data_v2.csv")
+Using the object `cats2`:
 
 # 1. Print the data
 _____
@@ -568,15 +566,15 @@ _____(cats)
 #    The correct data type is: ____________.
 
 # 4. Correct the 4th weight data point with the mean of the two given values
-cats$weight[4] <- 2.35
+cats2$weight[4] <- 2.35
 #    print the data again to see the effect
 cats
 
 # 5. Convert the weight to the right data type
-cats$weight <- ______________(cats$weight)
+cats2$weight <- ______________(cats2$weight)
 
 #    Calculate the mean to test yourself
-mean(cats$weight)
+mean(cats2$weight)
 
 # If you see the correct mean value (and not NA), you did the exercise
 # correctly!
@@ -586,7 +584,7 @@ mean(cats$weight)
 
 #### 1\. Print the data
 
-Execute the first statement (`read.csv(...)`). Then print the data to the
+Print the data to the
 console
 
 :::::::::::::::  solution
@@ -601,8 +599,8 @@ Show the content of any variable by typing its name.
 Two correct solutions:
 
 ```
-cats
-print(cats)
+cats2
+print(cats2)
 ```
 
 :::::::::::::::::::::::::
@@ -611,7 +609,7 @@ print(cats)
 
 The data type of your data is as important as the data itself. Use a
 function we saw earlier to print out the data types of all columns of the
-`cats` table.
+`cats2` `data.frame`.
 
 :::::::::::::::  solution
 
@@ -628,15 +626,14 @@ here.
 > ### Solution to Challenge 1.2
 > 
 > ```
-> str(cats)
+> str(cats2)
 > ```
 
 #### 3\. Which data type do we need?
 
 The shown data type is not the right one for this data (weight of
 a cat). Which data type do we need?
 
-- Why did the `read.csv()` function not choose the correct data type?
 - Fill in the gap in the comment with the correct data type for cat weight!
 
 :::::::::::::::  solution
@@ -715,8 +712,8 @@ auto-complete function: Type "`as.`" and then press the TAB key.
 > There are two functions that are synonymous for historic reasons:
 > 
 > ```
-> cats$weight <- as.double(cats$weight)
-> cats$weight <- as.numeric(cats$weight)
+> cats2$weight <- as.double(cats2$weight)
+> cats2$weight <- as.numeric(cats2$weight)
 > ```
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::

data/feline-data.csv

@@ -1,4 +1,4 @@
-"coat","weight","likes_string"
+"coat","weight","likes_catnip"
 "calico",2.1,1
 "black",5,0
 "tabby",3.2,1

md5sum.txt

@@ -6,7 +6,7 @@
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 "episodes/02-project-intro.Rmd" "cd60cc3116d4f6be92f03f5cc51bcc3b" "site/built/02-project-intro.md" "2024-12-03"
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-"episodes/04-data-structures-part1.Rmd" "afc6c3ced3677ab088457152f8d84b54" "site/built/04-data-structures-part1.md" "2024-12-03"
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