tidyquant package integrates the best resources for collecting and analyzing financial data,
PerformanceAnalytics, with the tidy data infrastructure of the
tidyverse allowing for seamless interaction between each. You can now perform complete financial analyses in the
A brief introduction to
What users are saying about tidyquant
Thanks very much for the tidyquant package, it's an absolute breeze to work with. I am a self-taught user of the "tidyverse" and your package saves me (a) a ton of work and (b) helps produce understandable and manageable code. The latest integration with the PerformanceAnalytics package is even better! Thank you.
timetk package enables the user to more easily work with time series objects in R. The package has tools for inspecting, analyzing and manipulating the time-based index and converting time-based objects to and from the many time series classes. The package is well-suited for time series data mining and time series machine learning using the time series signature.
Time Series Machine Learning with timetk
sweep package enables
broom-style "tidying" of ARIMA, ETS, BATS, and other models and forecast objects used in the
forecast package. The output is a "tidy" data frame that fits into the data science workflow of the
Forecasting in the "tidyverse" with sweep
Introducing the tibbletime functions
filter_time()- Succinctly filter a
tbl_timeobject by date.
as_period()- Convert a
tbl_timeobject from daily to monthly, from minute data to hourly, and more. This allows the user to easily aggregate data to a less granular level.
collapse_by()- Take an
tbl_timeobject, and collapse the index so that all observations in an interval share the same date. The most common use of this is to then group on this column with
dplyr::group_by()and perform time-based calculations with
mutate(), or any other
collapse_index()- A lower level version of
collapse_by()that directly modifies the
indexcolumn and not the entire
tbl_timeobject. It allows the user more flexibility when collapsing, like the ability to assign the resulting collapsed index to a new column.
rollify()- Modify a function so that it calculates a value (or a set of values) at specific time intervals. This can be used for rolling averages and other rolling calculations inside the tidyverse framework.
create_series()- Use shorthand notation to quickly initialize a tbl_time object containing a regularly spaced index column of class
Built on top of the
anomalize enables a "tidy" workflow for detecting anomalies in time series data. The main functions are