easyr

Helpful functions from Oliver Wyman Actuarial Consulting.

easyr makes difficult operations easy.

Installation

You can install the latest version available on CRAN:


install.packages('easyr')
require(easyr)

Or install the latest version from github:


devtools::install_github( "oliver-wyman-actuarial/easyr" )
require(easyr)

Getting Started

Tutorial: https://www.kaggle.com/brycechamberlain/easyr-tutorial.

Here is what a project looks like using easyr:

# start with begin() to set up your workspace.
# begin will set the working directory to the location of this file and
#     run anything in fun/ or functions/ so put your functions there.
require(easyr)
begin()

# read.any reads in your data regardless of format, with powerful typing to get numbers and dates.
# use ?read.any to see the many options.
dt = read.any( 'path/to/file.extension' )

# let's look at a data dictionary to understand our data.
View( dict( dt ) )

# begin has already loaded dplyr and magrittr so you are ready to go.
dt %<>% 
  filter( !is.na(id) ) %>% 
  mutate( newcol = oldcol1 + oldcol 2 )

# use w to quickly write to out.csv'.
w( dt )

Function categories:

Data:

Built, shared, and managed by Oliver Wyman Actuarial Consulting.

Now accepting proposed contributions through GitHub!

Highlights

Philosophy

This packages comes from code we’ve written to make our daily work more efficient. We rely on it heavily in our organization.

It is built on the following tenets:

Make A Contribution

Any and all contributions are welcome. The easiest way to contribute is to add an Issue. This can be a bug identified or even an idea you have on how we can improve easyr. Please be detailed and provide examples to make it easy for the community to resolve your issue/idea.

If you would like to make a more material contribution via Pull Request, please consider: * The Issue page page lists open issues that we need your help to resolve. * build-install-test.R is included to let you run tests. Please run this to ensure your changes don’t cause tests or examples to fail. * tests/testthat folder contains tests. Consider adding a test to validate your change and prevent someone else from breaking it in the future. * cmd-code-run-checks.txt contains command-line scripts you can run to check if your changes will be acceptable to CRAN. If it isn’t, it’ll require extra work by us before we can submit to CRAN.

Support

Submit an Issue or Pull Request via GitHub and the community will review it.

Functions

Here are the functions in easyr by category. Use ?functionName to view detailed documentation for a function.

Shorthand

Common operations shortened for elegance, simplicity, and speed.

Name Description
cc Shorthand paste0/paste function to make typing these common function easier. Intuitively understands how to combine various-length inputs.
coalf dplyr function “coalesce” but handles factors appropriately. Checks each argument vector starting with the first until a non-null value is found.
crun Concatenate arguments and run them as a command. Shorthand for eval( parse( text = paste0( … ) ) ). Consider also using base::get() which can be used to get an object from a string, but only if it already exists.
ddiff Date difference function plus shorthand mdiff, qdiff, ydiff.
eq Vectorized flexible equality comparison which considers NAs as a value. Returns TRUE if both values are NA, and FALSE when only one is NA.
gr Get the golden ratio.
left/right/mid Behaves like Excel’s LEFT, RIGHT, and MID functions.
nanull Facilitates checking for missing values. NULL values can cause errors on is.na checks, and is.na can cause warnings if it is inside if() and is passed multiple values.
%ni% Not in. Opposite of %in% operator. Equivalent to x %ni% y is equivalent to ! x %in% y.
isval Opposite of nanull.
read.txt Read the text of a file into a character variable.
other shorthand (multiple) functions to save you keystrokes : na (is.na), nan (is.nan), null (is.null), ischar (is.character), isdate (is.Date), isnum (is.numeric), tochar (as.character)
pad0 Adds leading zeros to a character vector to make each value a specific length. For values shorter than length passed, leading zeros are removed.
spl Extract a uniform random sample from a dataset or vector.
strx base::str (structure) function but only for names matching a character value (regex).
w write function. Writes to csv without row names and automatically adds .csv to the file name if it isn’t there already. Changes to .csv if another extension is passed.

Type Conversion

Helpful for setting or changing variable/vector data types.

Name Description
atype Auto-type a dataframe: automatically determine data types and perform conversions per column. Used by read.any to automatically set types.
char2fac, fac2char Convert all character columns to factors and vice-versa.
match.factors Modifies two datasets so matching factor columns have the same levels. Typically this is used prior to joining or bind_rows in the easyr functions bindf, ijoinf, lfjoinf.
tobool Flexible boolean conversion function.
todate Flexible date conversion function using lubridate. Works with dates in many formats, without needing to know the format in advance.
tonum Flexible number conversion for converting strings to numbers. Handles $ , ’ and spaces.
xldate Converts dates from Excel integers to something usable in R.
fmat Format numbers and dates into character quickly and easily.

Data Wrangling

Help with reading and manipulating data.

Name Description
binbyvol Bins a numerical column according to another numerical column’s volume.
bindf dplyr’s bind_rows doesn’t work well when the data frame has factors. This function handles factors before applying bind rows.
dict Get information about a Data Frame or Data Table. Use getinfo to explore a single column instead.
drows Pull rows with a duplicated value.
getbetterint Takes bucket names of binned values such as [1e3,2e3) or [0.1234567, 0.2) and formats the values nicely into values such as 1,000-2,000 or 0.12-0.20
fldict Data dictionary for all data in a folder.
getinfo Get information about a Column in a Data Frame or Data Table. Use getdatadict to explore all columns in a dataset instead.
namesx Get column names that match a pattern.
ijoinf dplyr’s joins doesn’t work well when the data frame has factors. This function handles factors before applying dplyr::inner_join. Also availalbe are ljoinf, rjoinf for left and right join.
jrepl Join and replace. Joins to another dataset and replaces matched values on a given column. Good for quickly grabbing values from another dataset to fill in or replace.
read.any Flexible read function to handle many types of files, data types, etc. Reduces downstream errors from read issues. Currently handles CSV, TSV, DBF, RDS, XLS (incl. when formatted as HTML), and XLSX.
sch Search a data frame or vector. Attempts to replicate Excel search but with regex.
short_dollars Converts numeric plot axis dollars and attaches K and divides by 1000.
short_nums Shortens axis numbering to thousands or millions and adds.
sumnum Summarize all numeric columns in a dataset.
tcol Transpose operation that sets column names equal to a column in the original data.

Workflow

Operations to run projects and organize code.

Name Description
begin Perform common operations before running a script. Includes clearing environment variables, disabling scientific notation, loading common packages, and setting the working directory to the location of the current file.
caching functions including cache.init, cache.ok, save.cache, and clear.cache.
check_equal Check actual versus expected values and get helpful metrics back.
hashfiles Create a hash uniquely representing the state of files or folders. Helpful for checking for changes.
runfolder Run scripts in a folder. If an error occurs, it will tell you what file had the error. Helpful for running ordered scripts.
tcmsg Easy Try/Catch implementation to return the same message on error or warning. Makes it easier to write tryCatches.
tcwarn Like tcmsg but returns a warning instead of an error when an error occurs, so code can continue to run.
validate.equal Check that two data frames are equivalent.

Data

These data resources are also included.

Name Description
nastrings List of strings considered NA by easyr. Includes blank strings, “NA”, excel errors, etc.
states Helpul dataset of U.S. State abbreviations and names.
cblind Charting colors optimized for and selected by colorblind individuals.