2: Visualize Data, Bar Charts, Histograms, Boxplots, Scatterplots, Line Graphs, Overplotting, Customize

geom_bar()

a function in ggplot2 used to create bar charts

y-axis in geom_bar()

you should not supply a y aesthetic when you use a geom_bar(). ggplot will count how many times x value appears in the data, then display the counts on the y axis

count()

a function in ggplot2 that counts the number of occurrences of each value in a vector or variable

geom_col()

a function in ggplot2 used to create bar charts where the heights of the bars represent values in the data, rather than counts

Aesthetics

the visual properties of a plot in ggplot2, such as color, size, shape, and transparency, that can be mapped to data variables and used to enhance data visualization

color =

assigns color to the outline of a plot element

fill =

assigns color to the interior of a plot element

width =

assigns the thickness of a plot element's outline such as lines or bars

Position Adjustments

manipulates the placement of data points or bars in a plot to improve clarity and avoid overlap

fill = clarity

assigns transparency to the interior of a plot element, improving visual distinction

position = “dodge”

a position adjustment that separates overlapping bars in a bar chart to make them visually distinct

clarity(stacked)

a method that stacks plot elements while adjusting their transparency to enhance visibility and distinguish between categories

position = “stack”

a position adjustment that stacks overlapping elements on top of each other in a plot, allowing for combined visual representation of categories

position = “fill”

a position adjustment that scales overlapping elements in a bar chart to fill the same height, allowing for proportionate comparison of categories

position = “identity”

a bad position adjustment that retains the original data values of overlapping elements in a plot without stacking or scaling, allowing for a straightforward representation of each category

why is it position = “identity” bad?

it does not provide a clear visual comparison of overlapping elements, as the original data values remain unchanged and can lead to misleading interpretations

Facets

a way to create multiple subplots based on a factor or variable, allowing for comparison across different groups or categories within a single visualization

facet_grid()

a function in the ggplot2 package in R that creates a grid of plots based on two categorical variables, allowing for easy comparison of distributions and patterns across different combinations of those variables

facet_wrap()

a function in the ggplot2 package in R that creates a series of plots wrapped into a specified number of rows and columns based on a single categorical variable, making it easier to visualize multiple groups in a tidy format

scales argument

an argument used in ggplot2 functions to manage the scaling of axes, allowing for customization of the scale type, labels, and limits for better visualization

scale = “free”

allows each facet to have its own scales, enabling better visualization of varying ranges across different subplots

scales = “free_x”

allows the x-axis to vary independently for each facet, enhancing clarity when comparing different groups with unequal distributions

scales = “free_y”

allows the y-axis to vary independently for each facet, improving the visualization of varying data ranges across different subplots

geom_historgram()

is a function in ggplot2 used to create histograms by specifying the values and bins for data distribution visualization

binwidth

specifies the width of each bin in a histogram

bins

refers to the number of intervals into which the data is divided in a histogram

boundary

is the outer limits that define the range of bins in a histogram

geom_freqpoly()

is a function in ggplot2 that creates a frequency polygon, which uses a line to display the same information as a histogram

geom_density()

is a function in ggplot2 that estimates and visualizes the probability density function of a continuous variable, creating a smooth curve that represents the distribution of the data

geom_dotplot()

is a function in ggplot2 that creates a dot plot, displays 1-dimensional distributions. it represents each observation with a dot and then stacks dots within lines to create the semblance of a histogram

Density curves

are smooth lines that represent the distribution of a continuous variable

Facets

are a method in ggplot2 for creating multiple subplots based on the values of a categorical variable

Boxplots

are a graphical representation of the distribution of a dataset through its quartiles, highlighting the median, upper and lower quartiles, and potential outliers. they display the relationship between a continuous variable and a categorical variable

Countplots

display the relationship between 2 categorical variables

geom_boxplot()

is a ggplot2 function used to create boxplots in R. It visually summarizes the distribution of a continuous variable while allowing for grouping by a categorical variable

geom_boxplot() expectations

the y-axis to be continuous and x-axis to be categorical

outlier.color parameter

specifies the color of the outliers in a boxplot created using ggplot2

outlier.fill parameter

specifies the fill color of the outliers in a boxplot created using ggplot2

outlier.shape parameter

specifies the shape of the outliers in a boxplot created using ggplot2

outlier.size parameter

specifies the size of the outliers in a boxplot created using ggplot2

outlier.stroke parameter

specifies the stroke color of the outliers in a boxplot created using ggplot2

outlier.alpha parameter

specifies the transparency level of the outliers in a boxplot created using ggplot2

cut_interval()

is a function in ggplot2 that divides continuous data into intervals of equal length

cut_number()

is a function in ggplot2 that divides continuous data into a specified number of intervals, ensuring that each interval contains approximately the same number of observations

cut_width()

is a function in ggplot2 that divides continuous data into intervals of specified width

coord_flip()

is a function in ggplot2 that switches the x and y axes of a plot, allowing for horizontal displays of bar charts and other visualizations

geom_dotplot()

is a function in ggplot2 that creates a dot plot, visualizing the distribution of a continuous variable by stacking dots for each value in a specified bin

geom_violin()

is a function in ggplot2 that creates a violin plot, which combines a box plot and a density plot to visualize the distribution of a continuous variable across different categories.

draw_quantities =

is a function in ggplot2 that draws reference lines for specified quantiles on a plot

geom_count()

is a function in ggplot2 that creates a count plot, visualizing the number of occurrences of each combination of two categorical variables by representing them with points

Heat maps

are graphical representations of data where individual values are represented as colors

geom_tile()

is a function in ggplot2 that creates heat maps, displaying values in a matrix format with colored tiles.

Scatterplots

display the relationship between 2 continuous variables

geom_point()

is a function in ggplot2 used to create scatterplots by plotting points for two continuous variables

geom_text()

is a function in ggplot2 that adds text labels to a plot

geom_label()

is a function in ggplot2 that adds text labels with a background rectangle to a plot

geom_smooth()

is a function in ggplot2 that adds a smoothed line to a plot, often used to visualize trends in data. provides a summarized version of a scatterplot

“method” parameters

specify the method used for smoothing in geom_smooth(), such as "glm" or "lm".

geom_label_repel()

is a function in the ggplot2 library that adds text labels to plots while preventing overlapping by automatically adjusting their positions

Global mapping

refers to applying a transformation to all data points in a plot, affecting the entire dataset

Local mapping

applies transformations to specific subsets or areas, allowing for more detailed and focused analysis of specific data segments

last_plot()

is a function in ggplot2 that retrieves the last plot created. It allows users to modify or re-use the last generated plot without re-running the original plotting command

geom_rug()

adds another type of summary to the plot. displays the one dimensional marginal distributions of each variable in the scatterplot. they appear as tik marks along the x and y axes

geom_jitter()

plots a scatterplot and then adds a small amount of random noise to each point in the plot. provides a simple way to inspect patterns that occur in heavily gridded or overlapping data

coord_cartesian()

is a function in ggplot2 that adjusts the displayed coordinate system of a plot without altering the actual data