View source: R/f_data_processing.R
data_filtering | R Documentation |
This function returns a filtered data set, i.e. a reduced user's data frame with the same columns and rows limited by a criterion defined by filters
.
data_filtering(
data,
start,
end,
filters = c(),
plimits = c(),
pquantiles = c(),
dplimits = c(),
lambda = 1.25,
interval = FALSE,
retailers = FALSE
)
data |
The user's data frame with information about products to be filtered. It must contain columns: |
start |
The base period (as character) limited to the year and month, e.g. "2020-03". |
end |
The research period (as character) limited to the year and month, e.g. "2020-04". |
filters |
A vector of filter names (options are: |
plimits |
A two-dimensional vector of thresholds for minimum and maximum price change (it works if one of the chosen filters is |
pquantiles |
A two-dimensional vector of quantile levels for minimum and maximum price change (it works if one of the chosen filters is |
dplimits |
A two-dimensional vector of thresholds for maximum price drop and maximum drop in sales value (it works if one of the chosen filters is |
lambda |
The lambda parameter for |
interval |
A logical value indicating whether the filtering process concerns only two periods defined by |
retailers |
A logical parameter indicating whether filtering should be done for each outlet ( |
This function returns a filtered data set (a reduced user's data frame). If the set of filters
is empty, then the function returns the original data frame (defined by the data
parameter) limited to considered months. On the other hand, if all filters are chosen, i.e. filters=c(extremeprices,dumpprices,lowsales)
, then these filters work independently and a summary result is returned. Please note that both variants of extremeprices
filter can be chosen at the same time, i.e. plimits
and pquantiles
, and they work also independently.
Van Loon, K., Roels, D. (2018) Integrating big data in Belgian CPI. Meeting of the Group of Experts on Consumer Price Indices, Geneva.
data_filtering(milk,start="2018-12",end="2019-03",
filters=c("extremeprices"),pquantiles=c(0.01,0.99),interval=TRUE)
data_filtering(milk,start="2018-12",end="2019-03",
filters=c("extremeprices","lowsales"), plimits=c(0.25,2))
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