The dat file has some lines of extra information before the actual data. Skip them with the `skip` argument:

    read.table(&quot;http://www.nilu.no/projects/ccc/onlinedata/ozone/CZ03_2009.dat&quot;, 
               header=TRUE, skip=3)

An easy way to check this if you are unfamiliar with the dataset is to first use `readLines` to check a few lines, as below:

    readLines(&quot;http://www.nilu.no/projects/ccc/onlinedata/ozone/CZ03_2009.dat&quot;, 
              n=10)
    # [1] &quot;Ozone data from CZ03 2009&quot;   &quot;Local time: GMT + 0&quot;        
    # [3] &quot;&quot;                            &quot;Date        Hour      Value&quot;
    # [5] &quot;01.01.2009 00:00       34.3&quot; &quot;01.01.2009 01:00       31.9&quot;
    # [7] &quot;01.01.2009 02:00       29.9&quot; &quot;01.01.2009 03:00       28.5&quot;
    # [9] &quot;01.01.2009 04:00       32.9&quot; &quot;01.01.2009 05:00       20.5&quot;

Here, we can see that the actual data starts at `[4]`, so we know to skip the first three lines.

# Update

If you *really* only wanted the `Value` column, you *could* do that by:

    as.vector(
        read.table(&quot;http://www.nilu.no/projects/ccc/onlinedata/ozone/CZ03_2009.dat&quot;,
                   header=TRUE, skip=3)$Value)

Again, `readLines` is useful for helping us figure out the actual name of the columns we will be importing.

But I don&#39;t see *much* advantage to doing that over reading the whole dataset in and extracting later.

I have a data frame which has two columns of dates in the format yyyy/mm/dd.
I am trying to calculate the number of days between these two dates for each observation within the data frame (and create a new variable with this number of days in it).

So far I have tried using the answer given here:

https://stackoverflow.com/questions/5046708/calculate-the-number-of-weekdays-between-2-dates-in-r

but editing the code so that it calculates number of total days rather than just the number of week days. This just came up with error saying:

    Error in del/by : non-numeric argument to binary operator
    In addition: Warning message:
    In Ops.factor(to, from) : - not meaningful for factors

I have also attempted using this code:

    finish &lt;- as.Date(survey$date, format=&quot;%yyyy/%mm/%dd&quot;)
    start &lt;- as.Date(survey$tx_start, format=&quot;%yyyy/%mm/%dd&quot;)
    date_diff&lt;-as.data.frame(finish-start)

with the plan of using &quot;cbind&quot; or something equivalent to combine the data frame &quot;days&quot; to my data frame &quot;survey&quot; which has data in it.

Although this does not give me any errors, the observations within the &quot;finish&quot; and &quot;start&quot; objects are all &quot;NA_real_&quot;, and the date_diff data frame therefore has all the observations listed as NA.

If someone could point me in the right direction that would be great! All the other question I have found do not seem to be dealing with dates within variables but as individual dates, and applying those techniques to variables hasn`t been working for me.


calculating number of days between 2 columns of dates in data frame

R help explains `invisible()` as &quot;a function that returns a temporarily invisible copy of an object&quot;. I have difficulty understanding what `invisible()` is used for. Would you be able to explain what `invisible()` does and when this function can be useful?

I&#39;ve seen that `invisible()` is almost always used in method functions for the `print()`. Here is one example:

    ### My Method function:
    print.myPrint &lt;- function(x, ...){
      print(unlist(x[1:2]))
      invisible(x)
    }

    x = list(v1 = c(1:5), v2 = c(-1:-5) )
    class(x) = &quot;myPrint&quot;
    print(x)

I was thinking that without `invisible(x)`, I wouldn&#39;t be able to do assignment like:
   
    a = print(x)

But it&#39;s actually not the case.
So, I&#39;d like to know what `invisible()` does, where it can be useful, and finally what it&#39;s role is in the method print function above?

Thank you very much for your help.

What does the function invisible() do?

Apologies in advance for the simplicity of this question. I am trying to import a .dat file from a website into R with the following code:

    www = &quot;http://www.nilu.no/projects/ccc/onlinedata/ozone/CZ03_2009.dat&quot;
    data &lt;- read.delim(www, header = TRUE, sep=&quot;\t&quot;) 

I want to access the Value portion of the data.frame, however, I am unsure about the dimensions of the data.frame, if I type ncol(data) it returns 1 which I was expecting three. How do I access the &quot;third&quot; column of this data.frame? 

import dat file into R

Apologies in advance for the simplicity of this question. I am trying to import a .dat file from a website into R with the following code:
<pre><code class="hljs language-ini">www = "http://www.nilu.no/projects/ccc/onlinedata/ozone/CZ03_2009.dat"
data &#x3C;- read.delim(www, header = TRUE, sep="\t") 
</code></pre>
I want to access the Value portion of the data.frame, however, I am unsure about the dimensions of the data.frame, if I type ncol(data) it returns 1 which I was expecting three. How do I access the "third" column of this data.frame?

I am wondering how and why the operator `%%` and `%/%` are for the remainder and the quotient.

Is there any reason or history that R developer had given them the meaning they have?

     &gt; 0 %/% 10
    [1] 0
    &gt; 30 %% 10
    [1] 0
    &gt; 35 %/% 10
    [1] 3
    &gt; 35 %% 10
    [1] 5


&quot;%%&quot; and &quot;%/%&quot; for the remainder and the quotient

What is the best way to assign to multiple columns using `data.table`? For example:

    f &lt;- function(x) {c(&quot;hi&quot;, &quot;hello&quot;)}
    x &lt;- data.table(id = 1:10)

I would like to do something like this (of course this syntax is incorrect):
  
    x[ , (col1, col2) := f(), by = &quot;id&quot;]

And to extend that, I may have many columns with names stored in a variable (say `col_names`) and I would like to do:

    x[ , col_names := another_f(), by = &quot;id&quot;, with = FALSE]

What is the correct way to do something like this?  

Assign multiple columns using := in data.table, by group

I have a simple data frame that I&#39;m trying to do a combined line and point plot using `ggplot2`. Supposing my data looks like this:

    df &lt;- data.frame(x=rep(1:10,2), y=c(1:10,11:20), 
                     group=c(rep(&quot;a&quot;,10),rep(&quot;b&quot;,10)))

And I&#39;m trying to make a plot:

    g &lt;- ggplot(df, aes(x=x, y=y, group=group))
    g &lt;- g + geom_line(aes(colour=group))
    g &lt;- g + geom_point(aes(colour=group, alpha = .8))
    g

The result looks fine with one exception. It has an extra legend showing the `alpha` for my `geom_point` layer.

![Extra Legend for `geom_point` transparency][1]

  [1]: http://i.stack.imgur.com/tCeVym.png

How can I keep the legend showing group colors, but not the one that shows my alpha settings?

Remove extra legends in ggplot2

I am quite new to R, and pretty much used to python. I am not so comfortable writing R code. I am looking for python interface to R, which lets me use R packages in **pythonic way**. 

I have done google research and found few packages which can do that:

 - [Rpy2](http://rpy.sourceforge.net/rpy2.html)
 - [PypeR](http://www.webarray.org/softwares/PypeR/)
 - [pyRserve](http://packages.python.org/pyRserve/manual.html)

But not sure which one is better ? Which has more contributers and more actively used ?

Please note my main requirement is **pythonic way for accessing R packages**. 

Python interface for R Programming Language

I&#39;m using python2.6 and got a problem this morning. It said &#39;module&#39; has no attribute &#39;Image&#39;. Here is my input. Why the first time I can not use PIL.Image?

    &gt;&gt;&gt; import PIL
    &gt;&gt;&gt; PIL.Image
    Traceback (most recent call last):
      File &quot;&lt;stdin&gt;&quot;, line 1, in &lt;module&gt;
    AttributeError: &#39;module&#39; object has no attribute &#39;Image&#39;
    &gt;&gt;&gt; from PIL import Image
    &gt;&gt;&gt; Image
    &lt;module &#39;PIL.Image&#39; from &#39;/usr/lib/python2.6/dist-packages/PIL/Image.pyc&#39;&gt;
    &gt;&gt;&gt; PIL.Image
    &lt;module &#39;PIL.Image&#39; from &#39;/usr/lib/python2.6/dist-packages/PIL/Image.pyc&#39;&gt;



Python PIL has no attribute &#39;Image&#39;

I fear that this is a messy way to approach the problem but... 

let&#39;s say that I want to make some imports in Python based on some conditions.

For this reason I want to write a function:

    def conditional_import_modules(test):
        if test == &#39;foo&#39;:
            import onemodule, anothermodule
        elif test == &#39;bar&#39;:
            import thirdmodule, and_another_module
        else:
            import all_the_other_modules

Now how can I have the imported modules globally available?

For example:

    conditional_import_modules(test=&#39;bar&#39;)
    thirdmodule.myfunction()



How to make global imports from a function?

Having already use flat packages, I was not expecting the issue I encountered with nested packages. Here is…


# Directory layout

    dir
     |
     +-- test.py
     |
     +-- package
          |
          +-- __init__.py
          |
          +-- subpackage
               |
               +-- __init__.py
               |
               +-- module.py

# Content of __init__.py

Both `package/__init__.py` and `package/subpackage/__init__.py` are empty.

# Content of `module.py`

    # file `package/subpackage/module.py`
    attribute1 = &quot;value 1&quot;
    attribute2 = &quot;value 2&quot;
    attribute3 = &quot;value 3&quot;
    # and as many more as you want...

# Content of `test.py` (3 versions)

## Version 1

    # file test.py
    from package.subpackage.module import *
    print attribute1 # OK

That&#39;s the bad and unsafe way of importing things (import all in a bulk), but it works.

## Version 2

    # file test.py
    import package.subpackage.module
    from package.subpackage import module # Alternative
    from module import attribute1

A safer way to import, item by item, but it fails, Python don&#39;t want this: fails with the message: &quot;No module named module&quot;. However&#160;…

    # file test.py
    import package.subpackage.module
    from package.subpackage import module # Alternative
    print module # Surprise here

…&#160;says `&lt;module &#39;package.subpackage.module&#39; from &#39;...&#39;&gt;`. So that&#39;s a module, but that&#39;s not a module /-P 8-O ... uh

## Version 3

    # file test.py v3
    from package.subpackage.module import attribute1
    print attribute1 # OK

This one works. So you are either forced to use the overkill prefix all the time or use the unsafe way as in version #1 and disallowed by Python to use the safe handy way? The better way, which is safe and avoid unecessary long prefix is the only one which Python reject? Is this because it loves `import *` or because it loves overlong prefixes (which does not help to enforce this practice)?.

Sorry for the hard words, but that&#39;s two days I trying to work around this stupid‑like behavior. Unless I was totally wrong somewhere, this will leave me with a feeling something is really broken in Python&#39;s model of package and sub‑packages.

Notes 

 * I don&#39;t want to rely on `sys.path`, to avoid global side effects, nor on `*.pth` files, which are just another way to play with `sys.path` with the same global effets. For the solution to be clean, it has to be local only. Either Python is able to handle subpackage, either it&#39;s not, but it should not require to play with global configuration to be able to handle local stuff.
 * I also tried use imports in `package/subpackage/__init__.py`, but it solved nothing, it do the same, and complains `subpackage` is not a known module, while `print subpackage` says it&#39;s a module (weird behavior, again).

May be I&#39;m entirely wrong tough (the option I would prefer), but this make me feel a lot disappointed about Python.

Any other known way beside of the three I tried? Something I don&#39;t know about?

(sigh)


----- %&lt; ----- edit ----- &gt;% -----

# Conclusion so far (after people&#39;s comments)

There is nothing like real sub‑package in Python, as all package references goes to a global dictionnary, only, which means there&#39;s no local dictionary, which implies there&#39;s is no way to manage local package reference.

You have to either use full prefix or short prefix or alias. As in:

## Full prefix version

    from package.subpackage.module import attribute1
    # An repeat it again an again
    # But after that, you can simply:
    use_of (attribute1)

## Short prefix version (but repeated prefix)

    from package.subpackage import module
    # Short but then you have to do:
    use_of (module.attribute1)
    # and repeat the prefix at every use place

Or else, a variation of the above.

    from package.subpackage import module as m
    use_of (m.attribute1)
    # `m` is a shorter prefix, but you could as well
    # define a more meaningful name after the context

# Factorized version

If you don&#39;t mind about importing multiple entity all at once in a batch, you can:

    from package.subpackage.module import attribute1, attribute2
    # and etc.

Not in my first favorite taste (I prefer to have one import statement per imported entity), but may be the one I will personally favor.

_Update (2012-09-14):_

Finally appears to be OK in practice, except with a comment about the layout. Instead of the above, I used:

    from package.subpackage.module import (

        attribute1, 
        attribute2,
        attribute3,
        ...)  # and etc.


Python: importing a sub‑package or sub‑module

Is there a way to remove unused imports in Intellij IDEA on commit?

It is not very optimal to do it manually, &lt;kbd&gt;CTRL&lt;/kbd&gt; + &lt;kbd&gt;ALT&lt;/kbd&gt; + &lt;kbd&gt;O&lt;/kbd&gt; helps but it&#39;s still manual.

How to remove unused imports in Intellij IDEA on commit?

does somebody know how to do a module.exports?

I tried some different ways ending up with

&lt;!-- language: typescript --&gt;

    export class Greeter {}

which will compile to

&lt;!-- language: typescript --&gt;

    exports.Greeter = Greeter;

But what I really want is this:

    exports = Greeter;

So that I can use it like this:

&lt;!-- language: typescript --&gt;

    import { Greeter } from &quot;greeter&quot;;
    
    const greeter = new Greeter();

and not

&lt;!-- language: typescript --&gt;

    import { Greeter } from &quot;greeter&quot;;
    
    const greeter = new Greeter.Greeter();

Is this possible with Typescript?

Content Type	Original Author	Original Content on Stackoverflow
Question	KatyB	View Question on Stackoverflow
Solution 1 - R	A5C1D2H2I1M1N2O1R2T1	View Answer on Stackoverflow

import dat file into R

R Problem Overview

R Solutions

Solution 1 - R

Update

What does the function invisible() do?

calculating number of days between 2 columns of dates in data frame

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