zoo: read.zoo – R documentation

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read.zoo

Reading and Writing zoo Series

Description

read.zoo and write.zoo are convenience functions for reading and writing "zoo" series from/to text files. They are convenience interfaces to read.table and write.table, respectively. To employ read.csv, read.csv2, read.delim, read.delim2 instead of read.table additional functions read.csv.zoo etc. are provided.

Usage

read.zoo(file, format = "", tz = "", FUN = NULL,
  regular = FALSE, index.column = 1, drop = TRUE, FUN2 = NULL,
  split = NULL, aggregate = FALSE, ..., text, read = read.table)
  
write.zoo(x, file = "", index.name = "Index", row.names = FALSE, col.names = NULL, ...)

read.csv.zoo(..., read = read.csv)
read.csv2.zoo(..., read = read.csv2)
read.delim.zoo(..., read = read.delim)
read.delim2.zoo(..., read = read.delim2)

Arguments

`file`	character string or strings giving the name of the file(s) which the data are to be read from/written to. See `read.table` and `write.table` for more information. Alternatively, in `read.zoo`, `file` can be a `connection` or a `data.frame` (e.g., resulting from a previous `read.table` call) that is subsequently processed to a `"zoo"` series.
`format`	date format argument passed to `FUN`.
`tz`	time zone argument passed to `as.POSIXct`.
`FUN`	a function for computing the index from the first column of the data. See details.
`regular`	logical. Should the series be coerced to class `"zooreg"` (if the series is regular)?
`index.column`	numeric vector or list. The column names or numbers of the data frame in which the index/time is stored. If the `read.table` argument `colClasses` is used and `"NULL"` is among its components then `index.column` refers to the column numbers after the columns corresponding to `"NULL"` in `colClasses` have been removed. If specified as a list then one argument will be passed to argument `FUN` per component so that, for example, `index.column = list(1, 2)` will cause `FUN(x[,1], x[,2], ...)` to be called whereas `index.column = list(1:2)` will cause `FUN(x[,1:2], ...)` to be called where `x` is a data frame of characters data. Here `...` refers to `format` and/or `tz`, if they specified as arguments. `index.column = 0` can be used to specify that the row names be used as the index. In the case that no row names were input sequential numbering is used. If `index.column` is specified as an ordinary vector then if it has the same length as the number of arguments of `FUN` (or `FUN2` in the event that `FUN2` is specified and `FUN` is not) then `index.column` is converted to a list. Also it is always converted to a list if it has length 1.
`drop`	logical. If the data frame contains just a single data column, should the second dimension be dropped?
`x`	a `"zoo"` object.
`index.name`	character with name of the index column in the written data file.
`row.names`	logical. Should row names be written? Default is `FALSE` because the row names are just character representations of the index.
`col.names`	logical. Should column names be written? Default is to write column names only if `x` has column names.
`FUN2`	function. It is applied to the time index after `FUN` and before `aggregate`. If `FUN` is not specified but `FUN2` is specified then only `FUN2` is applied.
`split`	NULL or column number or name or vector of numbers or names. If not NULL then the data is assumed to be in long format and is split according to the indicated columns. See the R `reshape` command for description of long data. If `split = Inf` then the first of each run among the times are made into a separate series, the second of each run and so on. If `split= -Inf` then the last of each run is made into a separate series, the second last and so on.
`aggregate`	logical or function. If set to `TRUE`, then `aggregate.zoo` is applied to the zoo object created to compute the `mean` of all values with the same time index. Alternatively, `aggregate` can be set to any other function that should be used for aggregation. If `FALSE` (the default), no aggregation is performed and a warning is given if there are any duplicated time indexes. Note that most `zoo` functions do not accept objects with duplicate time indexes. See `aggregate.zoo`.
`...`	further arguments passed to other functions. In the `read.*.zoo` the arguments are passed to the function specified in `read` (unless `file` is a `data.frame` already). In `write.zoo` the arguments are passed to `write.table`.
`text`	character. If `file` is not supplied and this is, then data are read from the value of `text` via a text connection. See below for an example.
`read`	function. The function for reading `file` (unless it is a `data.frame` already).

Details

read.zoo is a convenience function which should make it easier to read data from a text file and turn it into a "zoo" series immediately. read.zoo reads the data file via read.table(file, ...). The column index.column (by default the first) of the resulting data is interpreted to be the index/time, the remaining columns the corresponding data. (If the file only has only column then that is assumed to be the data column and 1, 2, ... are used for the index.) To assign the appropriate class to the index, FUN can be specified and is applied to the first column.

To process the index, read.zoo calls FUN with the index as the first argument. If FUN is not specified, the following default is employed:

(a) If file is a data frame with a single index column that appears to be a time index already, then FUN = identity is used. The conditions for a readily produced time index are: It is not character or factor (and the arguments tz and format must not be specified).

(b) If the conditions from (a) do not hold then the following strategy is used. If there are multiple index columns they are pasted together with a space between each. Using the (pasted) index column: (1) If tz is specified then the index column is converted to POSIXct. (2) If format is specified then the index column is converted to Date. (3) Otherwise, a heuristic attempts to decide between "numeric", "POSIXct", and "Date" by trying them in that order (which may not always succeed though). By default, only the standard date/time format is used. Hence, supplying format and/or tz is necessary if some date/time format is used that is not the default. And even if the default format is appropriate for the index, explicitly supplying FUN or at least format and/or tz typically leads to more reliable results than the heuristic.

If regular is set to TRUE and the resulting series has an underlying regularity, it is coerced to a "zooreg" series.

To employ other functions than read.table to read the initial data, further convenience interfaces read.csv.zoo etc. are provided.

write.zoo is a convenience function for writing "zoo" series to text files. It first coerces its argument to a "data.frame", adds a column with the index and then calls write.table.

See also vignette("zoo-read", package = "zoo") for detailed examples.

Value

read.zoo returns an object of class "zoo" (or "zooreg").

Note

read.zoo works by first reading the data in using read.table and then processing it. This implies that if the index field is entirely numeric the default is to pass it to FUN or the built-in date conversion routine a number, rather than a character string. Thus, a date field such as 09122007 intended to represent December 12, 2007 would be seen as 9122007 and interpreted as the 91st day thereby generating an error.

This comment also applies to trailing decimals so that if 2000.10 were intended to represent the 10th month of 2000 in fact it would receive 2000.1 and regard it as the first month of 2000 unless similar precautions were taken.

In the above cases the index field should be specified to be "character" so that leading or trailing zeros are not dropped. This can be done by specifying a "character" index column in the "colClasses" argument, which is passed to read.table, as shown in the examples below.

Examples

## this manual page provides a few typical examples, many more cases
## are covered in vignette("zoo-read", package = "zoo")

## read text lines with a single date column
Lines <- "2013-12-24  2
2013-12-25 3
2013-12-26 8"
read.zoo(text = Lines, FUN = as.Date)       # explicit coercion
read.zoo(text = Lines, format = "%Y-%m-%d") # same
read.zoo(text = Lines)                      # same, via heuristic

## read text lines with date/time in separate columns
Lines <- "2013-11-24 12:41:21 2
2013-12-25 12:41:22.25 3
2013-12-26 12:41:22.75 8"
read.zoo(text = Lines, index = 1:2,
  FUN = paste, FUN2 = as.POSIXct)            # explicit coercion
read.zoo(text = Lines, index = 1:2, tz = "") # same
read.zoo(text = Lines, index = 1:2)          # same, via heuristic

## read text lines with month/year in separate columns
Lines <- "Jan 1998 4.36
Feb 1998 4.34"
read.zoo(text = Lines, index = 1:2, FUN = paste, FUN2 = as.yearmon)

## read directly from a data.frame (artificial and built-in BOD)
dat <- data.frame(date = paste("2000-01-", 10:15, sep = ""),
  a = sin(1:6), b = cos(1:6))
read.zoo(dat)
data("BOD", package = "datasets")
read.zoo(BOD)

## Not run: 
## descriptions of typical examples

## turn *numeric* first column into yearmon index
## where number is year + fraction of year represented by month
z <- read.zoo("foo.csv", sep = ",", FUN = as.yearmon)

## first column is of form yyyy.mm
## (Here we use format in place of as.character so that final zero 
## is not dropped in dates like 2001.10 which as.character would do.)
f <- function(x) as.yearmon(format(x, nsmall = 2), "%Y.%m")
z <- read.zoo("foo.csv", header = TRUE, FUN = f)

## turn *character* first column into "Date" index
## Assume lines look like: 12/22/2007 1 2
z <- read.zoo("foo.tab", format = "%m/%d/%Y")

# Suppose lines look like: 09112007 1 2 and there is no header
z <- read.zoo("foo.txt", format = "%d%m%Y")

## csv file with first column of form YYYY-mm-dd HH:MM:SS
## Read in times as "chron" class. Requires chron 2.3-22 or later.
z <- read.zoo("foo.csv", header = TRUE, sep = ",", FUN = as.chron)

## same but with custom format.  Note as.chron uses POSIXt-style 
## Read in times as "chron" class. Requires chron 2.3-24 or later.
z <- read.zoo("foo.csv", header = TRUE, sep = ",", FUN = as.chron, 
	format = "

## same file format but read it in times as "POSIXct" class.
z <- read.zoo("foo.csv", header = TRUE, sep = ",", tz = "")

## csv file with first column mm-dd-yyyy. Read times as "Date" class.
z <- read.zoo("foo.csv", header = TRUE, sep = ",", format = "%m-%d-%Y")

## whitespace separated file with first column of form YYYY-mm-ddTHH:MM:SS
## and no headers.  T appears literally.  Requires chron 2.3-22 or later.
z <- read.zoo("foo.csv", FUN = as.chron)

# read in all csv files in the current directory and merge them
read.zoo(Sys.glob("*.csv"), header = TRUE, sep = ",")

# We use "NULL" in colClasses for those columns we don't need but in 
# col.names we still have to include dummy names for them.  Of what 
# is left the index is the first three columns (1:3) which we convert 
# to chron class times in FUN and then truncate to 5 seconds in FUN2.  
# Finally we use aggregate = mean to average over the 5 second intervals.
library("chron")

Lines <- "CVX 20070201 9 30 51 73.25 81400 0
CVX 20070201 9 30 51 73.25 100 0
CVX 20070201 9 30 51 73.25 100 0
CVX 20070201 9 30 51 73.25 300 0
CVX 20070201 9 30 51 73.25 81400 0
CVX 20070201 9 40 51 73.25 100 0
CVX 20070201 9 40 52 73.25 100 0
CVX 20070201 9 40 53 73.25 300 0"

z <- read.zoo(text = Lines, 
  colClasses = c("NULL", "NULL", "numeric", "numeric", "numeric",
    "numeric", "numeric", "NULL"),
  col.names = c("Symbol", "Date", "Hour", "Minute", "Second", "Price", "Volume", "junk"),
  index = 1:3,  # do not count columns that are "NULL" in colClasses
  FUN = function(h, m, s) times(paste(h, m, s, sep = ":")),
  FUN2 = function(tt) trunc(tt, "00:00:05"),
  aggregate = mean)

## End(Not run)

zoo

S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations)

v1.8-10

GPL-2 | GPL-3

Authors

Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Gabor Grothendieck [aut], Jeffrey A. Ryan [aut], Joshua M. Ulrich [ctb], Felix Andrews [ctb]

Initial release

2022-04-15