Why is it not advisable to use attach() in R, and what should I use instead?
up vote
39
down vote
favorite
Let's assume that we have a data frame x
which contains the columns job
and income
. Referring to the data in the frame normally requires the commands x$job
for the data in the job
column and x$income
for the data in the income
column.
However, using the command attach(x)
permits to do away with the name of the data frame and the $
symbol when referring to the same data. Consequently, x$job
becomes job
and x$income
becomes income
in the R code.
The problem is that many experts in R advise NOT to use the attach()
command when coding in R.
What is the main reason for that? What should be used instead?
r dataframe r-faq
migrated from stats.stackexchange.com Apr 9 '12 at 0:24
This question came from our site for people interested in statistics, machine learning, data analysis, data mining, and data visualization.
add a comment |
up vote
39
down vote
favorite
Let's assume that we have a data frame x
which contains the columns job
and income
. Referring to the data in the frame normally requires the commands x$job
for the data in the job
column and x$income
for the data in the income
column.
However, using the command attach(x)
permits to do away with the name of the data frame and the $
symbol when referring to the same data. Consequently, x$job
becomes job
and x$income
becomes income
in the R code.
The problem is that many experts in R advise NOT to use the attach()
command when coding in R.
What is the main reason for that? What should be used instead?
r dataframe r-faq
migrated from stats.stackexchange.com Apr 9 '12 at 0:24
This question came from our site for people interested in statistics, machine learning, data analysis, data mining, and data visualization.
4
One problem is that you may have other objects in memory, called (in your example)job
, orincome
. If you want to use them but haveattach()
ed data framex
, it's easy to mix up use of objectsx$job
andjob
, orx$income
andincome
.
– guest
Apr 8 '12 at 4:20
add a comment |
up vote
39
down vote
favorite
up vote
39
down vote
favorite
Let's assume that we have a data frame x
which contains the columns job
and income
. Referring to the data in the frame normally requires the commands x$job
for the data in the job
column and x$income
for the data in the income
column.
However, using the command attach(x)
permits to do away with the name of the data frame and the $
symbol when referring to the same data. Consequently, x$job
becomes job
and x$income
becomes income
in the R code.
The problem is that many experts in R advise NOT to use the attach()
command when coding in R.
What is the main reason for that? What should be used instead?
r dataframe r-faq
Let's assume that we have a data frame x
which contains the columns job
and income
. Referring to the data in the frame normally requires the commands x$job
for the data in the job
column and x$income
for the data in the income
column.
However, using the command attach(x)
permits to do away with the name of the data frame and the $
symbol when referring to the same data. Consequently, x$job
becomes job
and x$income
becomes income
in the R code.
The problem is that many experts in R advise NOT to use the attach()
command when coding in R.
What is the main reason for that? What should be used instead?
r dataframe r-faq
r dataframe r-faq
edited Feb 6 '17 at 15:04
Scarabee
3,58041843
3,58041843
asked Apr 8 '12 at 4:10
SavedByJESUS
87021328
87021328
migrated from stats.stackexchange.com Apr 9 '12 at 0:24
This question came from our site for people interested in statistics, machine learning, data analysis, data mining, and data visualization.
migrated from stats.stackexchange.com Apr 9 '12 at 0:24
This question came from our site for people interested in statistics, machine learning, data analysis, data mining, and data visualization.
4
One problem is that you may have other objects in memory, called (in your example)job
, orincome
. If you want to use them but haveattach()
ed data framex
, it's easy to mix up use of objectsx$job
andjob
, orx$income
andincome
.
– guest
Apr 8 '12 at 4:20
add a comment |
4
One problem is that you may have other objects in memory, called (in your example)job
, orincome
. If you want to use them but haveattach()
ed data framex
, it's easy to mix up use of objectsx$job
andjob
, orx$income
andincome
.
– guest
Apr 8 '12 at 4:20
4
4
One problem is that you may have other objects in memory, called (in your example)
job
, or income
. If you want to use them but have attach()
ed data frame x
, it's easy to mix up use of objects x$job
and job
, or x$income
and income
.– guest
Apr 8 '12 at 4:20
One problem is that you may have other objects in memory, called (in your example)
job
, or income
. If you want to use them but have attach()
ed data frame x
, it's easy to mix up use of objects x$job
and job
, or x$income
and income
.– guest
Apr 8 '12 at 4:20
add a comment |
4 Answers
4
active
oldest
votes
up vote
35
down vote
accepted
When to use it:
I use attach()
when I want the environment you get in most stats packages (eg Stata, SPSS) of working with one rectangular dataset at a time.
When not to use it:
However, it gets very messy and code quickly becomes unreadable when you have several different datasets, particularly if you are in effect using R as a crude relational database, where different rectangles of data, all relevant to the problem at hand and perhaps being used in various ways of matching data from the different rectangles, have variables with the same name.
The with()
function, or the data=
argument to many functions, are excellent alternatives to many instances where attach()
is tempting.
5
+1 for suggestingwith
. If you're looking to save typing/typos that is better thanattach
.
– Wayne
Apr 8 '12 at 15:16
add a comment |
up vote
18
down vote
Another reason not to use attach
: it allows access to the values of columns of a data frame for reading (access) only, and as they were when attached. It is not a shorthand for the current value of that column. Two examples:
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> dist <- 0.3048 * dist
> # convert speed to meters per second
> speed <- 0.44707 * speed
> # compute a meaningless time
> time <- dist / speed
> # check our work
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
No changes were made to the cars
data set even though dist
and speed
were assigned to.
If explicitly assigned back to the data set...
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> cars$dist <- 0.3048 * dist
> # convert speed to meters per second
> cars$speed <- 0.44707 * speed
> # compute a meaningless time
> cars$time <- dist / speed
> # compute meaningless time being explicit about using values in cars
> cars$time2 <- cars$dist / cars$speed
> # check our work
> head(cars)
speed dist time time2
1 1.78828 0.6096 0.5000000 0.3408862
2 1.78828 3.0480 2.5000000 1.7044311
3 3.12949 1.2192 0.5714286 0.3895842
4 3.12949 6.7056 3.1428571 2.1427133
5 3.57656 4.8768 2.0000000 1.3635449
6 4.02363 3.0480 1.1111111 0.7575249
the dist
and speed
that are referenced in computing time
are the original (untransformed) values; the values of cars$dist
and cars$speed
when cars
was attached.
What I don't like is that you still need to use the "cars$" on the left side of the equation.
– skan
May 18 '16 at 9:14
add a comment |
up vote
12
down vote
I think there's nothing wrong with using attach
. I myself don't use it (then again, I love animals, but don't keep any, either). When I think of attach
, I think long term. Sure, when I'm working with a script I know it inside and out. But in one week's time, a month or a year when I go back to the script, I find the overheads with searching where a certain variable is from, just too expensive. A lot of methods have the data
argument which makes calling variables pretty easy (sensulm(x ~ y + z, data = mydata)
). If not, I find the usage of with
to my satisfaction.
In short, in my book, attach is fine for short quick data exploration, but for developing scripts that I or other might want to use, I try to keep my code as readable (and transferable) as possible.
1
+1 for pointing out thatdata=
may accomplish the same task with various commands that have it.
– Wayne
Apr 8 '12 at 15:17
add a comment |
up vote
8
down vote
If you execute attach(data)
multiple time, eg, 5 times, then you can see (with the help of search()
) that your data has been attached 5 times in the workspace environment. So if you de-attach (detach(data)
) it once, there'll still be data
present 4 times in the environment. Hence, with()/within()
are better options. They help create a local environment containing that object and you can use it without creating any confusions.
add a comment |
4 Answers
4
active
oldest
votes
4 Answers
4
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
35
down vote
accepted
When to use it:
I use attach()
when I want the environment you get in most stats packages (eg Stata, SPSS) of working with one rectangular dataset at a time.
When not to use it:
However, it gets very messy and code quickly becomes unreadable when you have several different datasets, particularly if you are in effect using R as a crude relational database, where different rectangles of data, all relevant to the problem at hand and perhaps being used in various ways of matching data from the different rectangles, have variables with the same name.
The with()
function, or the data=
argument to many functions, are excellent alternatives to many instances where attach()
is tempting.
5
+1 for suggestingwith
. If you're looking to save typing/typos that is better thanattach
.
– Wayne
Apr 8 '12 at 15:16
add a comment |
up vote
35
down vote
accepted
When to use it:
I use attach()
when I want the environment you get in most stats packages (eg Stata, SPSS) of working with one rectangular dataset at a time.
When not to use it:
However, it gets very messy and code quickly becomes unreadable when you have several different datasets, particularly if you are in effect using R as a crude relational database, where different rectangles of data, all relevant to the problem at hand and perhaps being used in various ways of matching data from the different rectangles, have variables with the same name.
The with()
function, or the data=
argument to many functions, are excellent alternatives to many instances where attach()
is tempting.
5
+1 for suggestingwith
. If you're looking to save typing/typos that is better thanattach
.
– Wayne
Apr 8 '12 at 15:16
add a comment |
up vote
35
down vote
accepted
up vote
35
down vote
accepted
When to use it:
I use attach()
when I want the environment you get in most stats packages (eg Stata, SPSS) of working with one rectangular dataset at a time.
When not to use it:
However, it gets very messy and code quickly becomes unreadable when you have several different datasets, particularly if you are in effect using R as a crude relational database, where different rectangles of data, all relevant to the problem at hand and perhaps being used in various ways of matching data from the different rectangles, have variables with the same name.
The with()
function, or the data=
argument to many functions, are excellent alternatives to many instances where attach()
is tempting.
When to use it:
I use attach()
when I want the environment you get in most stats packages (eg Stata, SPSS) of working with one rectangular dataset at a time.
When not to use it:
However, it gets very messy and code quickly becomes unreadable when you have several different datasets, particularly if you are in effect using R as a crude relational database, where different rectangles of data, all relevant to the problem at hand and perhaps being used in various ways of matching data from the different rectangles, have variables with the same name.
The with()
function, or the data=
argument to many functions, are excellent alternatives to many instances where attach()
is tempting.
answered Apr 8 '12 at 7:09
Peter Ellis
3,2381837
3,2381837
5
+1 for suggestingwith
. If you're looking to save typing/typos that is better thanattach
.
– Wayne
Apr 8 '12 at 15:16
add a comment |
5
+1 for suggestingwith
. If you're looking to save typing/typos that is better thanattach
.
– Wayne
Apr 8 '12 at 15:16
5
5
+1 for suggesting
with
. If you're looking to save typing/typos that is better than attach
.– Wayne
Apr 8 '12 at 15:16
+1 for suggesting
with
. If you're looking to save typing/typos that is better than attach
.– Wayne
Apr 8 '12 at 15:16
add a comment |
up vote
18
down vote
Another reason not to use attach
: it allows access to the values of columns of a data frame for reading (access) only, and as they were when attached. It is not a shorthand for the current value of that column. Two examples:
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> dist <- 0.3048 * dist
> # convert speed to meters per second
> speed <- 0.44707 * speed
> # compute a meaningless time
> time <- dist / speed
> # check our work
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
No changes were made to the cars
data set even though dist
and speed
were assigned to.
If explicitly assigned back to the data set...
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> cars$dist <- 0.3048 * dist
> # convert speed to meters per second
> cars$speed <- 0.44707 * speed
> # compute a meaningless time
> cars$time <- dist / speed
> # compute meaningless time being explicit about using values in cars
> cars$time2 <- cars$dist / cars$speed
> # check our work
> head(cars)
speed dist time time2
1 1.78828 0.6096 0.5000000 0.3408862
2 1.78828 3.0480 2.5000000 1.7044311
3 3.12949 1.2192 0.5714286 0.3895842
4 3.12949 6.7056 3.1428571 2.1427133
5 3.57656 4.8768 2.0000000 1.3635449
6 4.02363 3.0480 1.1111111 0.7575249
the dist
and speed
that are referenced in computing time
are the original (untransformed) values; the values of cars$dist
and cars$speed
when cars
was attached.
What I don't like is that you still need to use the "cars$" on the left side of the equation.
– skan
May 18 '16 at 9:14
add a comment |
up vote
18
down vote
Another reason not to use attach
: it allows access to the values of columns of a data frame for reading (access) only, and as they were when attached. It is not a shorthand for the current value of that column. Two examples:
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> dist <- 0.3048 * dist
> # convert speed to meters per second
> speed <- 0.44707 * speed
> # compute a meaningless time
> time <- dist / speed
> # check our work
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
No changes were made to the cars
data set even though dist
and speed
were assigned to.
If explicitly assigned back to the data set...
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> cars$dist <- 0.3048 * dist
> # convert speed to meters per second
> cars$speed <- 0.44707 * speed
> # compute a meaningless time
> cars$time <- dist / speed
> # compute meaningless time being explicit about using values in cars
> cars$time2 <- cars$dist / cars$speed
> # check our work
> head(cars)
speed dist time time2
1 1.78828 0.6096 0.5000000 0.3408862
2 1.78828 3.0480 2.5000000 1.7044311
3 3.12949 1.2192 0.5714286 0.3895842
4 3.12949 6.7056 3.1428571 2.1427133
5 3.57656 4.8768 2.0000000 1.3635449
6 4.02363 3.0480 1.1111111 0.7575249
the dist
and speed
that are referenced in computing time
are the original (untransformed) values; the values of cars$dist
and cars$speed
when cars
was attached.
What I don't like is that you still need to use the "cars$" on the left side of the equation.
– skan
May 18 '16 at 9:14
add a comment |
up vote
18
down vote
up vote
18
down vote
Another reason not to use attach
: it allows access to the values of columns of a data frame for reading (access) only, and as they were when attached. It is not a shorthand for the current value of that column. Two examples:
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> dist <- 0.3048 * dist
> # convert speed to meters per second
> speed <- 0.44707 * speed
> # compute a meaningless time
> time <- dist / speed
> # check our work
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
No changes were made to the cars
data set even though dist
and speed
were assigned to.
If explicitly assigned back to the data set...
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> cars$dist <- 0.3048 * dist
> # convert speed to meters per second
> cars$speed <- 0.44707 * speed
> # compute a meaningless time
> cars$time <- dist / speed
> # compute meaningless time being explicit about using values in cars
> cars$time2 <- cars$dist / cars$speed
> # check our work
> head(cars)
speed dist time time2
1 1.78828 0.6096 0.5000000 0.3408862
2 1.78828 3.0480 2.5000000 1.7044311
3 3.12949 1.2192 0.5714286 0.3895842
4 3.12949 6.7056 3.1428571 2.1427133
5 3.57656 4.8768 2.0000000 1.3635449
6 4.02363 3.0480 1.1111111 0.7575249
the dist
and speed
that are referenced in computing time
are the original (untransformed) values; the values of cars$dist
and cars$speed
when cars
was attached.
Another reason not to use attach
: it allows access to the values of columns of a data frame for reading (access) only, and as they were when attached. It is not a shorthand for the current value of that column. Two examples:
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> dist <- 0.3048 * dist
> # convert speed to meters per second
> speed <- 0.44707 * speed
> # compute a meaningless time
> time <- dist / speed
> # check our work
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
No changes were made to the cars
data set even though dist
and speed
were assigned to.
If explicitly assigned back to the data set...
> head(cars)
speed dist
1 4 2
2 4 10
3 7 4
4 7 22
5 8 16
6 9 10
> attach(cars)
> # convert stopping distance to meters
> cars$dist <- 0.3048 * dist
> # convert speed to meters per second
> cars$speed <- 0.44707 * speed
> # compute a meaningless time
> cars$time <- dist / speed
> # compute meaningless time being explicit about using values in cars
> cars$time2 <- cars$dist / cars$speed
> # check our work
> head(cars)
speed dist time time2
1 1.78828 0.6096 0.5000000 0.3408862
2 1.78828 3.0480 2.5000000 1.7044311
3 3.12949 1.2192 0.5714286 0.3895842
4 3.12949 6.7056 3.1428571 2.1427133
5 3.57656 4.8768 2.0000000 1.3635449
6 4.02363 3.0480 1.1111111 0.7575249
the dist
and speed
that are referenced in computing time
are the original (untransformed) values; the values of cars$dist
and cars$speed
when cars
was attached.
answered Apr 9 '12 at 19:52
Brian Diggs
44.1k9119159
44.1k9119159
What I don't like is that you still need to use the "cars$" on the left side of the equation.
– skan
May 18 '16 at 9:14
add a comment |
What I don't like is that you still need to use the "cars$" on the left side of the equation.
– skan
May 18 '16 at 9:14
What I don't like is that you still need to use the "cars$" on the left side of the equation.
– skan
May 18 '16 at 9:14
What I don't like is that you still need to use the "cars$" on the left side of the equation.
– skan
May 18 '16 at 9:14
add a comment |
up vote
12
down vote
I think there's nothing wrong with using attach
. I myself don't use it (then again, I love animals, but don't keep any, either). When I think of attach
, I think long term. Sure, when I'm working with a script I know it inside and out. But in one week's time, a month or a year when I go back to the script, I find the overheads with searching where a certain variable is from, just too expensive. A lot of methods have the data
argument which makes calling variables pretty easy (sensulm(x ~ y + z, data = mydata)
). If not, I find the usage of with
to my satisfaction.
In short, in my book, attach is fine for short quick data exploration, but for developing scripts that I or other might want to use, I try to keep my code as readable (and transferable) as possible.
1
+1 for pointing out thatdata=
may accomplish the same task with various commands that have it.
– Wayne
Apr 8 '12 at 15:17
add a comment |
up vote
12
down vote
I think there's nothing wrong with using attach
. I myself don't use it (then again, I love animals, but don't keep any, either). When I think of attach
, I think long term. Sure, when I'm working with a script I know it inside and out. But in one week's time, a month or a year when I go back to the script, I find the overheads with searching where a certain variable is from, just too expensive. A lot of methods have the data
argument which makes calling variables pretty easy (sensulm(x ~ y + z, data = mydata)
). If not, I find the usage of with
to my satisfaction.
In short, in my book, attach is fine for short quick data exploration, but for developing scripts that I or other might want to use, I try to keep my code as readable (and transferable) as possible.
1
+1 for pointing out thatdata=
may accomplish the same task with various commands that have it.
– Wayne
Apr 8 '12 at 15:17
add a comment |
up vote
12
down vote
up vote
12
down vote
I think there's nothing wrong with using attach
. I myself don't use it (then again, I love animals, but don't keep any, either). When I think of attach
, I think long term. Sure, when I'm working with a script I know it inside and out. But in one week's time, a month or a year when I go back to the script, I find the overheads with searching where a certain variable is from, just too expensive. A lot of methods have the data
argument which makes calling variables pretty easy (sensulm(x ~ y + z, data = mydata)
). If not, I find the usage of with
to my satisfaction.
In short, in my book, attach is fine for short quick data exploration, but for developing scripts that I or other might want to use, I try to keep my code as readable (and transferable) as possible.
I think there's nothing wrong with using attach
. I myself don't use it (then again, I love animals, but don't keep any, either). When I think of attach
, I think long term. Sure, when I'm working with a script I know it inside and out. But in one week's time, a month or a year when I go back to the script, I find the overheads with searching where a certain variable is from, just too expensive. A lot of methods have the data
argument which makes calling variables pretty easy (sensulm(x ~ y + z, data = mydata)
). If not, I find the usage of with
to my satisfaction.
In short, in my book, attach is fine for short quick data exploration, but for developing scripts that I or other might want to use, I try to keep my code as readable (and transferable) as possible.
answered Apr 8 '12 at 9:04
Roman Luštrik
48.6k17104158
48.6k17104158
1
+1 for pointing out thatdata=
may accomplish the same task with various commands that have it.
– Wayne
Apr 8 '12 at 15:17
add a comment |
1
+1 for pointing out thatdata=
may accomplish the same task with various commands that have it.
– Wayne
Apr 8 '12 at 15:17
1
1
+1 for pointing out that
data=
may accomplish the same task with various commands that have it.– Wayne
Apr 8 '12 at 15:17
+1 for pointing out that
data=
may accomplish the same task with various commands that have it.– Wayne
Apr 8 '12 at 15:17
add a comment |
up vote
8
down vote
If you execute attach(data)
multiple time, eg, 5 times, then you can see (with the help of search()
) that your data has been attached 5 times in the workspace environment. So if you de-attach (detach(data)
) it once, there'll still be data
present 4 times in the environment. Hence, with()/within()
are better options. They help create a local environment containing that object and you can use it without creating any confusions.
add a comment |
up vote
8
down vote
If you execute attach(data)
multiple time, eg, 5 times, then you can see (with the help of search()
) that your data has been attached 5 times in the workspace environment. So if you de-attach (detach(data)
) it once, there'll still be data
present 4 times in the environment. Hence, with()/within()
are better options. They help create a local environment containing that object and you can use it without creating any confusions.
add a comment |
up vote
8
down vote
up vote
8
down vote
If you execute attach(data)
multiple time, eg, 5 times, then you can see (with the help of search()
) that your data has been attached 5 times in the workspace environment. So if you de-attach (detach(data)
) it once, there'll still be data
present 4 times in the environment. Hence, with()/within()
are better options. They help create a local environment containing that object and you can use it without creating any confusions.
If you execute attach(data)
multiple time, eg, 5 times, then you can see (with the help of search()
) that your data has been attached 5 times in the workspace environment. So if you de-attach (detach(data)
) it once, there'll still be data
present 4 times in the environment. Hence, with()/within()
are better options. They help create a local environment containing that object and you can use it without creating any confusions.
edited Nov 27 '17 at 3:10
SymbolixAU
15.9k32784
15.9k32784
answered Dec 12 '16 at 4:31
Aquarian91
8112
8112
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4
One problem is that you may have other objects in memory, called (in your example)
job
, orincome
. If you want to use them but haveattach()
ed data framex
, it's easy to mix up use of objectsx$job
andjob
, orx$income
andincome
.– guest
Apr 8 '12 at 4:20