View source: R/tool_pdata.frame.R
pdata.frame | R Documentation |
An object of class 'pdata.frame' is a data.frame with an index attribute that describes its individual and time dimensions.
pdata.frame(
x,
index = NULL,
drop.index = FALSE,
row.names = TRUE,
stringsAsFactors = FALSE,
replace.non.finite = FALSE,
drop.NA.series = FALSE,
drop.const.series = FALSE,
drop.unused.levels = FALSE,
...
)
## S3 replacement method for class 'pdata.frame'
x$name <- value
## S3 method for class 'pdata.frame'
x[i, j, drop]
## S3 method for class 'pdata.frame'
x[[y]]
## S3 method for class 'pdata.frame'
x$y
## S3 method for class 'pdata.frame'
print(x, ...)
## S3 method for class 'pdata.frame'
as.list(x, keep.attributes = FALSE, ...)
## S3 method for class 'pdata.frame'
as.data.frame(
x,
row.names = NULL,
optional = FALSE,
keep.attributes = TRUE,
...
)
x |
a |
index |
this argument indicates the individual and time indexes. See Details, |
drop.index |
logical, indicates whether the indexes are to be excluded from the resulting pdata.frame, |
row.names |
|
stringsAsFactors |
logical, indicating whether character vectors are to be converted to factors, |
replace.non.finite |
logical, indicating whether values for
which |
drop.NA.series |
logical, indicating whether all- |
drop.const.series |
logical, indicating whether constant
columns are to be removed from the pdata.frame (defaults to
|
drop.unused.levels |
logical, indicating whether unused levels
of factors are to be dropped (defaults to |
... |
further arguments passed on to internal usage of |
name |
the name of the |
value |
the name of the variable to include, |
i |
see |
j |
see |
drop |
see |
y |
one of the columns of the |
keep.attributes |
logical, only for as.list and as.data.frame methods, indicating whether the elements of the returned list/columns of the data.frame should have the pdata.frame's attributes added (default: FALSE for as.list, TRUE for as.data.frame), |
optional |
see |
The index
argument indicates the dimensions of the panel. It can
be:
a vector of two character strings which contains the names of the individual and of the time indexes,
a character string which is the name of the individual index variable. In this case, the time index is created automatically and a new variable called "time" is added, assuming consecutive and ascending time periods in the order of the original data,
an integer, the number of individuals. In this case, the data need to be a balanced panel and be organized as a stacked time series (successive blocks of individuals, each block being a time series for the respective individual) assuming consecutive and ascending time periods in the order of the original data. Two new variables are added: "id" and "time" which contain the individual and the time indexes.
The "[["
and "$"
extract a series from the pdata.frame
. The
"index"
attribute is then added to the series and a class
attribute "pseries"
is added. The "["
method behaves as for
data.frame
, except that the extraction is also applied to the
index
attribute. A safe way to extract the index attribute is to
use the function index()
for 'pdata.frames' (and other objects).
as.data.frame
removes the index attribute from the pdata.frame
and adds it to each column. For its argument row.names
set to
FALSE
row names are an integer series, TRUE
gives "fancy" row
names; if a character (with length of the resulting data frame),
the row names will be the character's elements.
as.list
behaves by default identical to
base::as.list.data.frame()
which means it drops the
attributes specific to a pdata.frame; if a list of pseries is
wanted, the attribute keep.attributes
can to be set to
TRUE
. This also makes lapply
work as expected on a pdata.frame
(see also Examples).
a pdata.frame
object: this is a data.frame
with an
index
attribute which is a data.frame
with two variables,
the individual and the time indexes, both being factors. The
resulting pdata.frame is sorted by the individual index, then
by the time index.
Yves Croissant
index()
to extract the index variables from a
'pdata.frame' (and other objects), pdim()
to check the
dimensions of a 'pdata.frame' (and other objects), pvar()
to
check for each variable if it varies cross-sectionally and over
time. To check if the time periods are consecutive per
individual, see is.pconsecutive()
.
# Gasoline contains two variables which are individual and time
# indexes
data("Gasoline", package = "plm")
Gas <- pdata.frame(Gasoline, index = c("country", "year"), drop.index = TRUE)
# Hedonic is an unbalanced panel, townid is the individual index
data("Hedonic", package = "plm")
Hed <- pdata.frame(Hedonic, index = "townid", row.names = FALSE)
# In case of balanced panel, it is sufficient to give number of
# individuals data set 'Wages' is organized as a stacked time
# series
data("Wages", package = "plm")
Wag <- pdata.frame(Wages, 595)
# lapply on a pdata.frame by making it a list of pseries first
lapply(as.list(Wag[ , c("ed", "lwage")], keep.attributes = TRUE), lag)
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