Data Visualization With Ggplot2 — Part 1 MCQs with Explanations

geom_point() is the correct answer to “In ggplot2, what function is used to create a scatter plot”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

color = "red" is the correct answer to “How do you change the color of all points in a ggplot2 scatter plot to red”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Adds aesthetic mappings to the plot is the correct answer to “In ggplot2, what is the purpose of the aes() function”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Sets the title of the entire plot is the correct answer to “What is the purpose of the ggtitle() function in ggplot2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_bar(aes(x = category, y = count)) is the correct answer to “How do you create a bar plot in ggplot2 for a categorical variable named category and its counts”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_line() is the correct answer to “In ggplot2, what function is used to create a line plot”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_errorbar() is the correct answer to “How do you add error bars to a ggplot2 bar plot”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Divides the plot into multiple facets is the correct answer to “What is the role of the facet_wrap() function in ggplot2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Adjusts the overall theme of the plot is the correct answer to “In ggplot2, what is the purpose of the theme() function”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_boxplot(mapping = aes(x = group, y = value)) is the correct answer to “How do you create a boxplot in ggplot2 for a numerical variable named value grouped by a factor variable group”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Customizes the labels and captions of the plot is the correct answer to “What is the purpose of the labs() function in ggplot2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_hist(mapping = aes(x = variable)) is the correct answer to “How do you create a histogram in ggplot2 for a numeric variable named variable”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_smooth() is the correct answer to “In ggplot2, how do you add a smooth line to a scatter plot”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

scale_color_manual(values = color_var) is the correct answer to “How do you customize the color of data points based on a categorical variable color_var in a ggplot2 scatter plot”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

scale_x_discrete(labels = category) is the correct answer to “In ggplot2, how do you customize the x-axis labels for a categorical variable category”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

scale_color_gradient(low = "blue", high = "red") is the correct answer to “In ggplot2, how do you add a color gradient to a scatter plot based on a numeric variable color_var”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Plots the counts directly without statistical transformation is the correct answer to “What is the purpose of the geom_bar(stat = "identity") syntax in ggplot2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_violin(aes(x = group, y = values)) is the correct answer to “How do you create a violin plot in ggplot2 for a numerical variable named values grouped by a factor variable group”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Converts a scatter plot to a polar coordinate system is the correct answer to “In ggplot2, what is the role of the coord_polar() function”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_bar(aes(x = category1, fill = category2), position = "stack") is the correct answer to “How do you create a stacked bar plot in ggplot2 for two categorical variables category1 and category2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Sets the plot theme with minimal elements is the correct answer to “What does the theme_minimal() function do in ggplot2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

labs(legend.title = "New Title") is the correct answer to “In ggplot2, how do you customize the appearance of the legend title”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

aes(alpha = 0.5) is the correct answer to “How do you customize the transparency of points in a ggplot2 scatter plot”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Adds text labels to the plot is the correct answer to “In ggplot2, what does the geom_text() function do”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

facet_wrap(~facet1 + facet2) is the correct answer to “How do you create a faceted scatter plot in ggplot2 for two categorical variables facet1 and facet2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_bar(position = "horizontal") is the correct answer to “In ggplot2, how do you create a bar plot with horizontal bars”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

Sets the y-axis to a logarithmic scale is the correct answer to “What is the purpose of the scale_y_log10() function in ggplot2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

theme_dark() is the correct answer to “How do you create a theme with a dark background in ggplot2”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

theme(axis.ticks = element_line(color = "red")) is the correct answer to “In ggplot2, how do you customize the appearance of axis ticks”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

geom_density(mapping = aes(x = values)) is the correct answer to “How do you create a density plot in ggplot2 for a numeric variable named values”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

z <- rbinom(n,size,prob) is the correct answer to “Which of the following code create n samples of size "size" with probability prob from the binomial”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

x1 <- c(rnorm(n)) is the correct answer to “Which of the following code create a n item vector of random normal deviates”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

read.table(filename,header=TRUE,sep=',') is the correct answer to “Which of the following statement can read csv files”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

read.table(filename,header=TRUE) is the correct answer to “Which of the following statement read a tab or space delimited file”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

subset(dataset,logical) is the correct answer to “which of the following statement chose those objects meeting a logical criterion”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

data.df[data.df=logical] is the correct answer to “Which of the following statement is another way to get a subset”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

x[rev(order(x$B)),] is the correct answer to “Which of the following sort a dataframe by the order of the elements in B”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

browse.workspace is the correct answer to “Which of the following is Mac menu command”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

ls() is the correct answer to “. . . . . . . . list the variables in the workspace.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

rm(list=ls()) is the correct answer to “. . . . . . . . remove all the variables from the workspace.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.