R: Summarise each group by time

summarise_by_time {tidyquant}

R Documentation

Summarise each group by time

Description

summarise_by_time() Is a time-series variant of the popular dplyr::summarise() function.

summarise_by_time() and summarize_by_time() are synonyms.

Usage

summarise_by_time(
  .data,
  .date_var,
  ...,
  .by = "week",
  .type = c("floor", "ceiling", "round")
)

summarize_by_time(
  .data,
  .date_var,
  ...,
  .by = "week",
  .type = c("floor", "ceiling", "round")
)

Arguments

`.data`	A `tbl` object or `data.frame`
`.date_var`	A column of date or date-time (e.g. POSIXct) data class
`...`	Name-value pairs of summary functions. The name will be the name of the variable in the result. The value can be: A vector of length 1, e.g. `min(x)`, `n()`, or `sum(is.na(y))`. A vector of length `n`, e.g. `quantile()`. A data frame, to add multiple columns from a single expression.
`.by`	A time unit to summarise by. Time units are collapsed using `lubridate::floor_date()` or `lubridate::ceiling_date()`. The value can be: `second` `minute` `hour` `day` `week` `month` `bimonth` `quarter` `season` `halfyear` `year` Arbitrary unique English abbreviations as in the `lubridate::period()` constructor are allowed.
`.type`	One of "floor", "ceiling", or "round. Defaults to "floor". See `lubridate::round_date`.

Value

An object usually of the same type as .data.

The rows come from the underlying group_keys().
The columns are a combination of the grouping keys and the summary expressions that you provide.
If x is grouped by more than one variable, the output will be another grouped_df with the right-most group removed.
If x is grouped by one variable, or is not grouped, the output will be a tibble.
Data frame attributes are not preserved, because summarise() fundamentally creates a new data frame.

Useful summary functions

Sum: SUM()
Center: AVERAGE(), MEDIAN()
Spread: STDEV(), VAR()
Range: MIN(), MAX()
Count: COUNT(), COUNT_UNIQUE()
Position: FIRST(), LAST(), NTH()
Correlation: COR(), COV()

Methods

This function is a generic, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.

Examples

# Libraries
library(tidyquant)
library(dplyr)

# First adjusted price in each month
FANG %>%
    group_by(symbol) %>%
    summarise_by_time(
        .date_var  = date,
        .by         = "month",
        adjusted   = FIRST(adjusted)
    )

# Last adjused price in each month (day is last day of month with ceiling option)
FANG %>%
    group_by(symbol) %>%
    summarise_by_time(
        .date_var  = date,
        .by        = "month",
        adjusted   = LAST(adjusted),
        .type      = "ceiling")

# Total Volume each year (.by is set to "year" now)
FANG %>%
    group_by(symbol) %>%
    summarise_by_time(
        .date_var  = date,
        .by        = "year",
        adjusted   = SUM(volume))

[Package tidyquant version 1.0.0 Index]