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.
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.tablecolClasses
argument is used and "NULL" is among its componennts 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 Rreshape 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 read.table or
write.table, respectively.
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.
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.
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.
See Also
zoo
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 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)