| Title: | A Comprehensive Set of Functions to Clean, Analyze, and Present Crime Data |
| Version: | 0.5.1 |
| Description: | A collection of functions that make it easier to understand crime (or other) data, and assist others in understanding it. The package helps you read data from various sources, clean it, fix column names, and graph the data. |
| Depends: | R (≥ 2.10) |
| Imports: | dplyr, stringr, ggplot2, readr, gridExtra, scales, magrittr, gt, grDevices, tidyr, stats, methods, rlang |
| License: | MIT + file LICENSE |
| URL: | https://github.com/jacobkap/crimeutils/ |
| BugReports: | https://github.com/jacobkap/crimeutils/issues/ |
| RoxygenNote: | 7.2.2 |
| Suggests: | spelling, testthat (≥ 2.1.0), covr |
| Language: | en-US |
| Encoding: | UTF-8 |
| NeedsCompilation: | no |
| Packaged: | 2022-12-07 05:04:32 UTC; jkkap |
| Author: | Jacob Kaplan 
[aut, cre] |
| Maintainer: | Jacob Kaplan <jkkaplan6@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2022-12-07 15:10:07 UTC |
Pipe operator
Description
See magrittr::%>% for details.
Usage
lhs %>% rhs
Capitalizes the first letter of every word
Description
Capitalizes the first letter of every word
Usage
capitalize_words(words, lowercase_of = TRUE)
Arguments
words |
A string or vector of strings with words you want capitalized |
lowercase_of |
If TRUE (default), keeps the string " of " to be lowercased as is custom in English writing (e.g. District of Columbia). |
Value
The original string with the first letter of each word capitalized
Examples
capitalize_words("district of columbia")
Creates new columns to indicate which values are outliers based on the average value.
Description
Creates new columns to indicate which values are outliers based on the average value.
Usage
indicate_outliers(
data,
select_columns = NULL,
group_variable,
std_dev_value = 1.96,
zero_is_outlier = FALSE
)
Arguments
data |
A data.frame |
select_columns |
A string or vector of strings with the name(s) of the numeric columns to check for outliers. If NULL (default), will use all numeric columns in the data. |
group_variable |
A string with the name of the column with the grouping variable. |
std_dev_value |
A number indicating how many standard deviations away from the mean to determine if a value is an outlier. |
zero_is_outlier |
If TRUE (not default), reports any zero value as an outlier. |
Value
The initial data.frame with new columns for each numeric variable included with a value of 0 if not an outlier and 1 if that row is an outlier.
Examples
indicate_outliers(mtcars, "drat", group_variable = "am")
indicate_outliers(mtcars, "drat", group_variable = "am", zero_is_outlier = TRUE)
Create a line graph with 95% confidence interval bars
Description
Create a line graph with 95% confidence interval bars
Usage
make_average_graph(
data,
x_col,
y_col,
confidence_interval_error_bars = TRUE,
mean_line = TRUE,
type = c("line", "bar")
)
Arguments
data |
A data.frame with the data you want to graph |
x_col |
A string with the name of the x-axis column |
y_col |
A string with the name of the y-axis column |
confidence_interval_error_bars |
A boolean (default TRUE) for whether to include 95% confidence intervals or not. |
mean_line |
If TRUE (default) willadd a dashed line with the overall mean. |
type |
A string for whether it should make a linegraph ("line", default) or a bargraph ("bar") |
Value
A ggplot object. Also prints the graph to the Plots panel.
Examples
data = data.frame(x = sample(15:25, size = 200, replace = TRUE),
y = sample(1:100, size = 200, replace = TRUE))
make_average_graph(data, "x", "y")
make_average_graph(data, "x", "y", confidence_interval_error_bars = FALSE)
make_average_graph(data, "x", "y", type = "bar", mean_line = FALSE)
make_average_graph(data, "x", "y", confidence_interval_error_bars = FALSE, type = "bar")
Make a nice-looking barplot.
Description
Make a nice-looking barplot.
Usage
make_barplots(data, column, count = TRUE, title = NULL, ylab = NULL)
Arguments
data |
A data.frame with the data you want to graph. |
column |
A string with the name of the column you want to make the plot from. |
count |
A boolean (default TRUE) indicating if you want the barplot to show a count of the column values or a percent. |
title |
A string with the text you want as the title. |
ylab |
A string with the text you want as the y-axis label. |
Value
A barplot object.
Examples
make_barplots(mtcars, "cyl")
make_barplots(mtcars, "cyl", count = FALSE, title = "hello", ylab = "YLAB Label")
Create a descriptive statistics table from numeric variables
Description
Create a descriptive statistics table from numeric variables
Usage
make_desc_stats_table(
data,
columns,
output = c("min", "median", "mean", "sd", "max", "sum", "NAs"),
decimals = 2,
title = NULL,
subtitle = NULL,
footnote = NULL
)
Arguments
data |
A data.frame with the data you want to make the table from. |
columns |
A string or vector of strings with the names of the columns you want to use. |
output |
A string or vector of strings indicating which math functions you want to perform on the columns and present in the table. Options are: 'min', 'median', 'mean', 'sd', 'max', and 'N'. Default is to use all of these math functions. The order you put in these values is the order the table will present the columns. |
decimals |
A positive integer for how many decimal places you want to round to. |
title |
A string with the text you want as the title |
subtitle |
A string with the text you want as the subtitle. |
footnote |
A string with the text you want as the footnote. |
Value
A data.frame with the data that generates the table, which is outputted in the Viewer tab.
Examples
make_desc_stats_table(mtcars, columns = c("mpg", "disp", "wt", "cyl"))
make_desc_stats_table(mtcars, c("mpg", "disp", "wt"), output = c("mean", "min"),
decimals = 4, title = "hello", subtitle = "world")
Creates a .tex file with LaTeX code to create a table from an R data.frame.
Description
Creates a .tex file with LaTeX code to create a table from an R data.frame.
Usage
make_latex_tables(
data,
file,
caption = "",
label = "",
multi_column = NULL,
footnote = "",
sideways = FALSE,
longtable = FALSE
)
Arguments
data |
A data.frame or a list of data.frames. If a data.frame, the table is created with the values in that data.frame. If a list of data.frames, the table gets one panel for each data.frame. If the list is named, will use the names to create panel labels. |
file |
A string with the name of the file to save the .tex as. |
caption |
(Optional) A string with the caption for the table (i.e. the table title). |
label |
(Optional) A string with the reference for the table - to be used when referencing the table in the text. If NULL, |
multi_column |
(Optional) A named vector with the names being the names of the multi-column and the values being the width of the multi-column. |
footnote |
(Optional) A string with text for the footnote of the table. |
sideways |
(Optional) If TRUE, will make a sideways table (useful for large tables), otherwise (default) will make a normal table. |
longtable |
(Optional) If TRUE, will make a longtable table (useful for long tables), otherwise (default) will make a normal table. |
Value
Nothing. It will create a .tex file in the current working directory.
Examples
## Not run:
make_latex_tables(mtcars, file = "text.tex", caption = "This is a description of the table",
label = "internal_table_label", footnote = "Here is some info you should know to read this table",
longtable = TRUE)
## End(Not run)
Create a table showing the mean, median, and mode of a certain column
Description
Create a table showing the mean, median, and mode of a certain column
Usage
make_mean_median_mode_table_by_group(
data,
group_column,
data_column,
total_row = TRUE
)
Arguments
data |
A data.frame with the data you want to make the table from. |
group_column |
A string with the name of the variable you are grouping by |
data_column |
A string for the variable you want to get the mean, median, and mode from, Variable should be numeric. |
total_row |
A boolean (default TRUE) for whether to include a row a the bottom for the overall mean and standard deviation (i.e. not by group). |
Value
A data.frame with the first column showing the category grouped by. Then one column for the mean, one column for the median, and one column for the mode.
Examples
make_mean_median_mode_table_by_group(mtcars, "gear", "mpg")
Get mean and standard deviation of variables by group
Description
Get mean and standard deviation of variables by group
Usage
make_mean_std_dev_by_group_table(data, group_column, columns, total_row = TRUE)
Arguments
data |
A data.frame with the data you want to make the table from. |
group_column |
A string with the name of the variable you are grouping by |
columns |
A string or vector of strings for the variables you want to get the mean and standard deviation for. |
total_row |
A boolean (default TRUE) for whether to include a row a the bottom for the overall mean and standard deviation (i.e. not by group). |
Value
A data.frame with the first column showing the category grouped by. Then one column for each variable you want the mean and standard deviation for. Will give the mean and standard deviation as a single string with the standard deviation in parentheses.
Examples
make_mean_std_dev_by_group_table(mtcars, "gear", c("mpg", "disp"))
Make a table showing the number (n) and percent of the population (e.g. % of nrow()) for each value in a variable(s).
Description
Make a table showing the number (n) and percent of the population (e.g. % of nrow()) for each value in a variable(s).
Usage
make_n_and_percent_table(data, columns)
Arguments
data |
A data.frame with the data you want to make the table from. |
columns |
A string or vector of strings with the column names to make the N and % from. |
Value
A data.frame with one row for each value in the inputted variable(s) and columns showing the N and % for that value.
Examples
make_n_and_percent_table(mtcars, c("cyl", "gear"))
Make a graph of coefficient values and 95 percent confidence interval for regression.
Description
Make a graph of coefficient values and 95 percent confidence interval for regression.
Usage
make_regression_graph(model, coefficients = NULL)
Arguments
model |
A 'lm' object made from making a model using 'lm()'. |
coefficients |
A string or vector of strings with the coefficient names. Will then make the graph only with those coefficients. |
Value
Outputs a 'ggplot2' graph
Examples
make_regression_graph(model = lm(mpg ~ cyl + disp + hp + drat, data = mtcars))
make_regression_graph(model = lm(mpg ~ cyl + disp + hp + drat, data = mtcars),
coefficients = c("cyl", "disp"))
make_regression_graph(model = lm(mpg ~ cyl + disp, data = mtcars))
Turns regression results in a data.frame for easy conversion to a table
Description
Turns regression results in a data.frame for easy conversion to a table
Usage
make_regression_table(model, coefficients_only = TRUE)
Arguments
model |
A 'lm' object made from making a model using 'lm()'. |
coefficients_only |
If TRUE (default), returns only the coefficients,standard error, t-value, p-value, and confidence intervals. Else also returns the r-squared, the adjusted r-squared,f-stat, p-value for the f-stat, and the degrees of freedom. |
Value
A data.frame with the regression results
Examples
make_regression_table(lm(mpg ~ cyl, data = mtcars))
make_regression_table(lm(mpg ~ cyl, data = mtcars), coefficients_only = FALSE)
Make a nice-looking stat_count (similar to barplot) plot.
Description
Make a nice-looking stat_count (similar to barplot) plot.
Usage
make_stat_count_plots(
data,
column,
count = TRUE,
title = NULL,
ylab = NULL,
xlab = NULL
)
Arguments
data |
A data.frame with the data you want to graph. |
column |
A string with the name of the column you want to make the plot from. |
count |
A boolean (default TRUE) indicating if you want the barplot to show a count of the column values or a percent. |
title |
A string with the text you want as the title. |
ylab |
A string with the text you want as the y-axis label. |
xlab |
A string with the text you want as the x-axis label. |
Value
A stat_count object
Examples
make_stat_count_plots(mtcars, "mpg")
make_stat_count_plots(mtcars, "mpg", count = FALSE, title = "hello", ylab = "YLAB Label")
Returns abbreviations of state name input.
Description
Returns abbreviations of state name input.
Usage
make_state_abb(state)
Arguments
state |
A vector of strings with the names of US states. |
Value
A vector of strings with the abbreviations of the inputted state names.
Examples
make_state_abb("california")
Pad decimal places with trailing zeros.
Description
Pad decimal places with trailing zeros.
Usage
pad_decimals(numbers, digits = NULL)
Arguments
numbers |
A number or vector of numbers. |
digits |
Number of decimal places to pad. If NULL (default), uses the maximum number of decimal places in the numbers input. If digits is less than the number of decimal places in the data, rounds the data to the decimal place specified. If rounding at a 5, follows R's rules to round to the nearest even number. |
Value
The original numbers, now as strings with trailing zeros added to the decimal places.
Examples
pad_decimals(c(2, 3.4, 8.808))
A set of colorblind friendly colors for graphs.
Description
A set of colorblind friendly colors for graphs.
Usage
scale_color_crim(...)
Arguments
... |
Arguments passed to discrete_scale() |
Value
The ggplot graph with colors set.
Examples
ggplot2::ggplot(mtcars, ggplot2::aes(x = mpg, y = hp, color = as.character(cyl))) +
ggplot2::geom_point(size = 2) +
scale_color_crim()
A set of colorblind friendly fill colors for graphs.
Description
A set of colorblind friendly fill colors for graphs.
Usage
scale_fill_crim(...)
Arguments
... |
Arguments passed to discrete_scale() |
Value
The ggplot graph with fills set.
Examples
ggplot2::ggplot(mtcars, ggplot2::aes(x = cyl, fill = as.character(cyl))) +
ggplot2::geom_bar() +
scale_fill_crim()
A set of linetypes
Description
A set of linetypes
Usage
scale_linetype_crim(...)
Arguments
... |
Arguments passed to discrete_scale() |
Value
The ggplot graph with linetypes set.
Examples
ggplot2::ggplot(mtcars, ggplot2::aes(x = mpg, y = hp, linetype = as.character(cyl))) +
ggplot2::geom_line(size = 1) +
scale_linetype_crim() +
theme_crim()
Create a PDF with one scatterplot for each group in the data.
Description
Create a PDF with one scatterplot for each group in the data.
Usage
scatterplot_data_graph(
data,
numeric_variable1,
numeric_variable2,
group_variable,
file_name
)
Arguments
data |
A data.frame with the data you want to graph. |
numeric_variable1 |
A string with the name of the first column with numeric data to graph. |
numeric_variable2 |
A string with the name of the second column with numeric data to graph. |
group_variable |
A string with the name of the column with the grouping variable. |
file_name |
A string with the name of the PDF to be made with one page for each graph. |
Value
A PDF with one page per graph
Examples
## Not run:
scatterplot_data_graph(mtcars, numeric_variable1 = "mpg", numeric_variable2 = "disp",
group_variable = "gear", file_name = "test.pdf")
## End(Not run)
A minimalist theme designed for graphics in academic research
Description
A minimalist theme designed for graphics in academic research
Usage
theme_crim()
Value
The graph with the theme changed.
Examples
ggplot2::ggplot(mtcars) +
ggplot2::geom_point(ggplot2::aes(x = wt, y = mpg)) +
theme_crim()
Create a PDF with one time-series graph for each group in the data.
Description
Create a PDF with one time-series graph for each group in the data.
Usage
time_series_data_graph(
data,
numeric_variable,
time_variable,
group_variable,
outlier_std_dev_value = 1.96,
file_name
)
Arguments
data |
A data.frame with the data you want to graph. |
numeric_variable |
A string with the name of the column with numeric data to graph. |
time_variable |
A string with the name of the column that contains the time variable. |
group_variable |
A string with the name of the column with the grouping variable. |
outlier_std_dev_value |
A number that indicates how many standard deviations from the group mean an outlier is. Outliers will be colored orange in the data. |
file_name |
A string with the name of the PDF to be made with one page for each graph. |
Value
A PDF with one page per graph
Get ORIs that consistently report their data every year.
Description
Get ORIs that consistently report their data every year.
Usage
ucr_constant_reporter_oris(data, minimum_months_reported)
Arguments
data |
A data.frame with Uniform Crime Report (UCR) data. Requires at least the ORI, year, and number_of_months_reported columns. |
minimum_months_reported |
Integer indicating the minimum number of months requesting to keep in data. |
Value
A vector with the ORIs that report the minimum number of months for every year in the data.