Package 'ggtaichi'

Taichi

Description

The taichi geom turns each cell of a heatmap-like grid into a taichi (yin-yang) diagram. The two interlocking "fish" of the diagram use luminance to show the values from two data sources on the same plot, so four dimensions of data can be expressed at once: the x and y position of every taichi symbol plus the yin and yang values that fill its two halves.

Usage

geom_taichi(
  yin,
  yin_name = NULL,
  yin_colors = c("gray100", "gray85", "gray50", "gray35", "gray0"),
  yang,
  yang_name = NULL,
  yang_colors = c("#FED7D8", "#FE8C91", "#F5636B", "#E72D3F", "#C20824"),
  ...
)

Arguments

yin	The column name for the yin (dark) fish of the taichi symbol.
yin_name	The label name (in quotes) for the legend of the yin rendering. Default is NULL.
yin_colors	A color vector, usually as hex codes.
yang	The column name for the yang (light) fish of the taichi symbol.
yang_name	The label name (in quotes) for the legend of the yang rendering. Default is NULL.
yang_colors	A color vector, usually as hex codes.
...	... accepts any arguments scale_fill_gradientn() has .

Value

A taichi diagram comparing two data sources.

Examples

# taichi with categorical variables only

library(ggplot2)

data <- data.frame(x = rep(c("a", "b", "c"), 3),
                   y = rep(c("d", "e", "f"), 3),
                   yin_values = rep(c(1,5,7),3),
                   yang_values = rep(c(2,3,4),3))

ggplot(data, aes(x,y)) +
geom_taichi(yin = yin_values,
            yang = yang_values)


# taichi with numeric variables only

data <- data.frame(x = rep(c(1, 2, 3), 3),
                   y = rep(c(1, 2, 3), 3),
                   yin_values = rep(c(1,5,7),3),
                   yang_values = rep(c(2,3,4),3))

ggplot(data, aes(x,y)) +
geom_taichi(yin = yin_values,
            yang = yang_values)


# taichi with a mixture of numeric and categorical variables

data <- data.frame(x = rep(c("a", "b", "c"), 3),
                   y = rep(c(1, 2, 3), 3),
                   yin_values = rep(c(1,5,7),3),
                   yang_values = rep(c(2,3,4),3))

ggplot(data, aes(x,y)) +
geom_taichi(yin = yin_values,
            yang = yang_values)

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Popular Emojis

Description

The most popular Emoji of a given week in a given category from the Meltwater Tweet sample. They can be rendered by using "richtext" with annotate().

Usage

pitts_emojis

Format

An object of class character of length 270.

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Pittsburgh COVID-related Google & Twitter incidence rates

Description

A data set containing the 30-week incidence rates of COVID related categories from week 1 starting from June 1, 2020 to week 30 that ended in the last Sunday of the year in Pittsburgh Metropolitan Statistical Area (MSA). The data columns are introduced below. One quick note about the columns of the data set: week_start as a column is present in the data set for illustration purposes, reminding users what week column is. In other words, it does not participate any visualization.

Usage

pitts_tg

Format

A data frame with 270 rows and 6 columns:

msa

Metropolitan statistical area (Pittsburgh only).

week

week 1 to week 30.

week_start

The Monday date of the week started.

category

9 Covid-related categories in total.

Twitter

weekly tweets percentage (%) in the MSA falling into each category.

Google

weekly Google search percentage (%) in the MSA falling into each category.

Source

Just like states_tg, Google is processed from Google Health API, and Twitter from Meltwater, a Twitter vendor. Both data sources are processed by the author of the package.

---

Remove ggplot2 default padding

Description

The default ggplot2 plots give certain amount of padding for both continuous and discrete variables. Due to this padding, it makes the plots generated from ‘geom_taichi()' look like there is something missing. Depends on users’ preference, they can remove the "empty space" by using this function. The only thing users need to figure out is whether the 'x' and 'y' scales are continuous or discrete.

Usage

remove_padding(x = "c", y = "d", ...)

Arguments

x	x-axis scale, if it is continuous scale, input "c"; discrete, "d".
y	y-axis scale, if it is continuous scale, input "c"; discrete, "d".
...	...

Value

remove_padding

---

States' COVID-related Google & Twitter incidence rates

Description

A data set containing the 30-week incidence rates of COVID related categories from week 1 starting from June 1, 2020 to week 30 that ended in the last Sunday of the year in 4 states (Florida, Missouri, New York, and Texas). The data columns are introduced below. One quick note about the columns of the data set: week_start as a column is present in the data set for illustration purposes, reminding users what week column is. In other words, it does not participate any visualization.

Usage

states_tg

Format

A data frame with 1116 rows and 6 columns:

state

state

week

week 1 to week 30.

week_start

The Monday date of the week started.

category

9 Covid-related categories in total.

Twitter

weekly tweets percentage (%) in state falling into each category.

Google

weekly Google search percentage (%) in state falling into each category.

Source

Just like pitts_tg, Google is processed from Google Health API, and Twitter from Meltwater, a Twitter vendor. Both data sources are processed by the author of the package.

---

Plot Themes

Description

A light theme tuned for the taichi grid: it bottoms the legends, drops the panel grid and axis ticks, and gives the canvas a soft off-white background reminiscent of rice paper.

Usage

theme_taichi(
  base_size = 11,
  base_family = "",
  base_line_size = base_size/22,
  base_rect_size = base_size/22
)

Arguments

base_size	base font size
base_family	base font family
base_line_size	base size for line elements
base_rect_size	base size for rect elements

Value

Adding a taichi theme to all plots generated by using the ggtaichi package.

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