read.zoo {zoo} | R Documentation |
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 |
format |
date format argument passed to |
tz |
time zone argument passed to |
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 |
index.column |
numeric vector or list. The column names or numbers of the data frame
in which the index/time is stored. If the |
drop |
logical. If the data frame contains just a single data column, should the second dimension be dropped? |
x |
a |
index.name |
character with name of the index column in the written data file. |
row.names |
logical. Should row names be written? Default is |
col.names |
logical. Should column names be written? Default is to
write column names only if |
FUN2 |
function. It is applied to the time index after
|
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
|
aggregate |
logical or function. If set to |
... |
further arguments passed to other functions. In the |
text |
character. If |
read |
function. The function for reading |
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.
See Also
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)