Merge pull request #35 from JosephBARBIERDARNAL/mortgage-rate

new article on using vertical lines instead of default axis

x-axis-with-vertical-lines/x-axis-with-vertical-lines.md

@@ -0,0 +1,282 @@
+# Use vertical lines instead of axis lines for cleaner charts
+David Keyes
+2024-09-16
+
+I recently came across a data viz in the *New York Times* that used a
+unique approach to adding axis lines. In [this chart about the number of
+days that members of the United States House of Representatives served
+as speaker](https://arc.net/l/quote/xcvmjwrj), rather than use
+traditional axis lines, they used white lines that show up on bars but
+are hidden otherwise.
+
+![](days-as-house-speaker.png)
+
+How can we create a bar chart in `ggplot2` without using vertical white
+lines instead? This guide will walk you through the steps to create a
+polished bar plot using gross domestic product data (GDP) from the
+`gapminder` package.
+
+## Load the Necessary Packages
+
+First, we need to load the `tidyverse` package, which includes `ggplot2`
+for plotting and `dplyr` for data manipulation. We’ll also be using the
+`gapminder` dataset that comes preloaded with the `gapminder` package.
+It contains data about life expectancy, GDP per capita, and population
+for different countries over time.
+
+``` r
+library(tidyverse)
+library(gapminder)
+```
+
+## Import Data
+
+We’ll focus on the most recent data in the dataset, which is from 2007,
+and select the top 10 countries by GDP per capita. We’ll also make the
+`country` variable into a factor, reordering it by the `gdpPercap`
+variable so that our bar chart will be ordered by GDP per capita.
+
+``` r
+gdp_data <-
+  gapminder |>
+  filter(year == 2007) |>
+  select(
+    country,
+    gdpPercap
+  ) |>
+  mutate(country = fct_reorder(
+    country,
+    gdpPercap
+  )) |>
+  arrange(desc(gdpPercap)) |>
+  slice(1:15)
+```
+
+Now, let’s take a look at our filtered dataset:
+
+``` r
+gdp_data
+#> # A tibble: 15 × 2
+#>    country          gdpPercap
+#>    <fct>                <dbl>
+#>  1 Norway              49357.
+#>  2 Kuwait              47307.
+#>  3 Singapore           47143.
+#>  4 United States       42952.
+#>  5 Ireland             40676.
+#>  6 Hong Kong, China    39725.
+#>  7 Switzerland         37506.
+#>  8 Netherlands         36798.
+#>  9 Canada              36319.
+#> 10 Iceland             36181.
+#> 11 Austria             36126.
+#> 12 Denmark             35278.
+#> 13 Australia           34435.
+#> 14 Sweden              33860.
+#> 15 Belgium             33693.
+```
+
+## Create a Basic Horizontal Bar Plot
+
+With our data in place, we will now create a basic bar chart to
+visualize the GDP per capita for each country.
+
+``` r
+ggplot(
+  gdp_data,
+  aes(
+    x = gdpPercap,
+    y = country
+  )
+) +
+  geom_col()
+```
+
+![](x-axis-with-vertical-lines_files/figure-commonmark/unnamed-chunk-4-1.svg)
+
+This creates a basic bar chart, but it’s still missing the customization
+we want, like removing the x-axis and adding vertical white lines.
+
+## Remove Default Axis Lines
+
+Next, we’ll remove the x-axis (since the bars are horizontal, this
+refers to the axis along the bottom). We’ll do this by using `theme()`
+and setting `panel.grid.major` and `panel.grid.minor` to
+`element_blank()`.
+
+``` r
+ggplot(
+  gdp_data,
+  aes(
+    x = gdpPercap,
+    y = country
+  )
+) +
+  geom_col() +
+  theme_minimal() +
+  theme(
+    panel.grid.major = element_blank(),
+    panel.grid.minor = element_blank()
+  )
+```
+
+![](x-axis-with-vertical-lines_files/figure-commonmark/unnamed-chunk-5-1.svg)
+
+## Add Custom Axis Lines
+
+To add vertical white lines in place of the x-axis, we’ll use
+`geom_vline()`. This function allows us to add vertical lines at
+specified positions. We’ll place the lines at intervals across the
+y-axis values to help the viewer estimate the GDP per capita using the
+`seq()` function to add lines from 10,000 to 50,000 at increments of
+10,000.
+
+``` r
+ggplot(
+  gdp_data,
+  aes(
+    x = gdpPercap,
+    y = country
+  )
+) +
+  geom_col() +
+  geom_vline(
+    xintercept = seq(
+      from = 10000,
+      to = 50000,
+      by = 10000
+    ),
+    color = "white"
+  ) +
+  theme_minimal() +
+  theme(
+    panel.grid.major = element_blank(),
+    panel.grid.minor = element_blank()
+  )
+```
+
+![](x-axis-with-vertical-lines_files/figure-commonmark/unnamed-chunk-6-1.svg)
+
+### Improve Overall Style
+
+Now that we’ve created the plot with our white vertical lines instead of
+axis lines, we can customize it further to make it look just a bit more
+polished.
+
+First, let’s add a nicer color to our bars (you might recognize it as
+the R for the Rest of Us blue):
+
+``` r
+geom_col(fill = "#6cabdd")
+```
+
+To do this, we make some tweaks with the `scale_x_continuous()` function
+to reduce the horizontal spacing around the bars and make the y-axis
+labels to show values in thousands (e.g., \$20k instead of 20000) with
+the `dollar_format()` function from the `scales` package.
+
+``` r
+scale_x_continuous(
+  expand = expansion(add = 500),
+  labels = scales::dollar_format(scale = 1 / 1000, suffix = "k")
+)
+```
+
+We also added a title and caption and removed the x and y axis labels
+(since they are now obvious from the title).
+
+``` r
+labs(
+  x = NULL,
+  y = NULL,
+  title = "GDP Per Capita (2007)",
+  caption = "Source: Gapminder"
+)
+```
+
+Next, we made a few additional tweaks to the theme. Adding
+`base_family = "Roboto"` makes the entire plot use that font and
+`base_size = 14` makes the size of all text elements larger in order to
+make them more readable.
+
+``` r
+theme_minimal(
+  base_family = "Roboto",
+  base_size = 14
+)
+```
+
+Finally, we added some additional tweaks in the `theme()` function to
+style the title and caption:
+
+``` r
+theme(
+  panel.grid.major = element_blank(),
+  panel.grid.minor = element_blank(),
+  plot.title = element_text(face = "bold"),
+  plot.caption = element_text(
+    size = 10,
+    color = "#7f8c8d",
+    hjust = 0,
+    margin = margin(t = 15)
+  )
+)
+```
+
+All of these elements combined given us our final code:
+
+``` r
+ggplot(
+  gdp_data,
+  aes(
+    x = gdpPercap,
+    y = country
+  )
+) +
+  geom_col(fill = "#6cabdd") +
+  geom_vline(
+    xintercept = seq(
+      from = 10000,
+      to = 50000,
+      by = 10000
+    ),
+    color = "white"
+  ) +
+  scale_x_continuous(
+    expand = expansion(add = 500),
+    labels = scales::dollar_format(scale = 1 / 1000, suffix = "k")
+  ) +
+  labs(
+    x = NULL,
+    y = NULL,
+    title = "GDP Per Capita (2007)",
+    caption = "Source: Gapminder"
+  ) +
+  theme_minimal(
+    base_family = "Roboto",
+    base_size = 14
+  ) +
+  theme(
+    panel.grid.major = element_blank(),
+    panel.grid.minor = element_blank(),
+    plot.title = element_text(face = "bold"),
+    plot.caption = element_text(
+      size = 10,
+      color = "#7f8c8d",
+      hjust = 0,
+      margin = margin(t = 15)
+    )
+  )
+```
+
+And the result looks great!
+
+![](x-axis-with-vertical-lines_files/figure-commonmark/unnamed-chunk-13-1.svg)
+
+By following these steps, you now have a clean, polished horizontal bar
+plot that uses vertical white lines as reference points for GDP per
+capita values. The x-axis has been removed for a cleaner look, but the
+vertical lines give viewers a guide for interpreting the values. This
+chart is a useful visualization tool for comparing GDP per capita across
+countries without the clutter of an x-axis, making the data easy to
+interpret at a glance.