Update completed computations files

Author: cwickham

docs/get-started/computations/_positron/python/computations-complete.qmd

@@ -1,11 +1,8 @@
 ---
 title: "Quarto Computations"
-format: 
-  html:
-    code-fold: true
-    code-tools: true
-fig-height: 3
-fig-width: 10
+echo: false
+fig-height: 3.5
+fig-width: 6
 ---
 
 This dataset contains a subset of the fuel economy data from the EPA.
@@ -17,42 +14,23 @@ from plotnine import *
 from plotnine.data import mpg
 ```
 
-The plots in @fig-scatterplot show the relationship between city and highway mileage for 38 popular models of cars.
-In @fig-scatterplot-1 the points are colored by the number of cylinders while in @fig-scatterplot the points are colored by engine displacement.
+@fig-scatterplot shows a positive, strong, and linear relationship between the city and highway mileage of these cars.
+Additionally, mileage is higher for cars with fewer cylinders.
 
 ```{python}
 #| label: fig-scatterplot
+#| echo: true
+#| code-fold: true
+#| code-line-numbers: true 
 #| fig-cap: "City and highway mileage for 38 popular models of cars."
-#| fig-subcap:
-#|   - "Color by number of cylinders"
-#|   - "Color by engine displacement, in liters"
-#| layout-ncol: 2
-#| column: page
+#| fig-alt: "Scatterplot of city vs. highway mileage for cars, where points are colored by the number of cylinders. The plot displays a positive, linear, and strong relationship between city and highway mileage, and mileage increases as the number of cylinders decreases."
 
-cyl_plot = (
+(
     ggplot(mpg, aes(x="hwy", y="cty", color="cyl"))
     + geom_point(alpha=0.5, size=2)
     + scale_color_continuous()
     + theme_bw()
 )
-
-cty_plot = (
-    ggplot(mpg, aes(x="hwy", y="cty", color="displ"))
-    + geom_point(alpha=0.5, size=2)
-    + scale_color_continuous(cmap_name="cividis")
-    + theme_bw()
-)
-
-cyl_plot.show()
-cty_plot.show() 
 ```
 
 There are `{python} len(mpg)` observations in our data.
-
-```{python}
-#| echo: false
-mean_cty = round(mpg['cty'].mean(), 2)
-mean_hwy = round(mpg['hwy'].mean(), 2)
-```
-
-The average city mileage of the cars in our data is `{python} f"{mean_cty:.2f}"` and the average highway mileage is `{python} f"{mean_hwy:.2f}"`. 

docs/get-started/computations/_positron/r/computations-complete.qmd

@@ -1,9 +1,6 @@
 ---
 title: "Quarto Computations"
-format: 
-  html:
-    code-fold: true
-    code-tools: true
+echo: false
 fig-height: 3.5
 fig-width: 6
 ---
@@ -16,27 +13,22 @@ This dataset contains a subset of the fuel economy data from the EPA.
 library(ggplot2)
 ```
 
-The plots in @fig-scatterplot show the relationship between city and highway mileage for 38 popular models of cars.
-In @fig-scatterplot-1 the points are colored by the number of cylinders while in @fig-scatterplot the points are colored by engine displacement.
+@fig-scatterplot shows a positive, strong, and linear relationship between the city and highway mileage of these cars.
+Additionally, mileage is higher for cars with fewer cylinders.
 
 ```{r}
 #| label: fig-scatterplot
+#| echo: true
+#| code-fold: true
+#| code-line-numbers: true 
 #| fig-cap: "City and highway mileage for 38 popular models of cars."
-#| fig-subcap:
-#|   - "Color by number of cylinders"
-#|   - "Color by engine displacement, in liters"
 #| fig-alt: "Scatterplot of city vs. highway mileage for cars, where points are colored by the number of cylinders. The plot displays a positive, linear, and strong relationship between city and highway mileage, and mileage increases as the number of cylinders decreases."
-#| layout-ncol: 2
-#| column: page
 
 ggplot(mpg, aes(x = hwy, y = cty, color = cyl)) +
   geom_point(alpha = 0.5, size = 2) +
   scale_color_viridis_c() +
   theme_minimal()
-
-ggplot(mpg, aes(x = hwy, y = cty, color = displ)) +
-  geom_point(alpha = 0.5, size = 2) +
-  scale_color_viridis_c(option = "E") +
-  theme_minimal()
 ```
 
+
+There are `{r} nrow(mpg)` observations in our data.

docs/get-started/computations/positron.qmd

@@ -215,6 +215,7 @@ For example, an alternative to showing or hiding code is to use [code folding](/
 
 ``` r
 #| label: scatterplot
+#| echo: true
 #| code-fold: true
 
 ggplot(mpg, aes(x = hwy, y = cty, color = cyl)) +
@@ -227,6 +228,7 @@ ggplot(mpg, aes(x = hwy, y = cty, color = cyl)) +
 
 ``` python
 #| label: scatterplot
+#| echo: true
 #| code-fold: true
 
 (
@@ -250,7 +252,9 @@ As another example, you can add line numbers to your code cells with the `code-l
 
 ``` r
 #| label: scatterplot
-#| code-line-numbers: true
+#| echo: true
+#| code-fold: true
+#| code-line-numbers: true 
 
 ggplot(mpg, aes(x = hwy, y = cty, color = cyl)) +
   geom_point(alpha = 0.5, size = 2) +
@@ -262,7 +266,9 @@ ggplot(mpg, aes(x = hwy, y = cty, color = cyl)) +
 
 ``` python
 #| label: scatterplot
-#| code-line-numbers: true
+#| echo: true
+#| code-fold: true
+#| code-line-numbers: true 
 
 (
     ggplot(mpg, aes(x="hwy", y="cty", color="cyl"))
@@ -303,6 +309,7 @@ format:
 
 To understand which options can be set in the document header, look at the [Reference](/docs/reference) for the format you are using.
 For instance, `code-fold` can be set in the document header because it is listed as an [HTML format option](/docs/reference/formats/html.qmd).
+You'll learn more about when to set document header options nested under a format versus at the top level in the next tutorial: [Authoring](/docs/get-started/authoring/positron.qmd).
 
 You can see examples of other options that control code appearance in the HTML format in the Guide page [HTML Code Blocks](/docs/output-formats/html-code.qmd).
 
@@ -349,6 +356,7 @@ You can control the size of all the figures in the document by setting `fig-widt
 ``` yaml
 ---
 title: "Quarto Computations"
+echo: false
 fig-height: 3.5
 fig-width: 6
 ---
@@ -386,8 +394,7 @@ To override the figure size for individual images, specify the plot size in your
 
 :::
 
-Quarto provides lots of additional flexibility for figures. 
-
+Quarto provides additional flexibility for figures. 
 You can:
 
 *  Produce figure panels with multiple figures, each with its subcaption. 
@@ -460,6 +467,7 @@ len(mpg)
 :::
 
 Preview the document again to see the output of your code cell. 
+
 This isn't a very pretty way to display the number of observations.
 An alternative is to use inline code, which we'll cover next.