You probably want the graphical parameters `xaxs` and `yaxs` with style &quot;i&quot;:

    plot(1:10, rnorm(10), ylim=c(0,10), yaxs=&quot;i&quot;)

See `?par`:

&gt; **xaxs**: The style of axis interval
&gt; calculation to be used for the x-axis.
&gt; Possible values are &quot;r&quot;, &quot;i&quot;, &quot;e&quot;,
&gt; &quot;s&quot;, &quot;d&quot;. The styles are generally
&gt; controlled by the range of data or
&gt; xlim, if given. Style &quot;r&quot; (regular)
&gt; first extends the data range by 4
&gt; percent at each end and then finds an
&gt; axis with pretty labels that fits
&gt; within the extended range. Style &quot;i&quot;
&gt; (internal) just finds an axis with
&gt; pretty labels that fits within the
&gt; original data range. Style &quot;s&quot;
&gt; (standard) finds an axis with pretty
&gt; labels within which the original data
&gt; range fits. Style &quot;e&quot; (extended) is
&gt; like style &quot;s&quot;, except that it is also
&gt; ensures that there is room for
&gt; plotting symbols within the bounding
&gt; box. Style &quot;d&quot; (direct) specifies that
&gt; the current axis should be used on
&gt; subsequent plots. (Only &quot;r&quot; and &quot;i&quot;
&gt; styles are currently implemented)
&gt; 
&gt; **yaxs**: The style of axis interval calculation to be used for the y-axis.
&gt; See *xaxs* above.



Another option is to disable the axis plotting in plot using `axes=F` and then put the axes in separately using the axis command, with the `pos` option controlling the axis spacing.

    plot(1:10, runif(10), ylim=c(0,1), xlim=c(0,10),axes=F)
         axis(1, pos=0)
         axis(2, pos=0)   

 

I didn&#39;t find a good comparison of jinja2 and Mako. What would you use for what tasks ? 

I personnaly was satisfied by mako (in a pylons web app context) but am curious to know if jinja2 has some nice features/improvements that mako doesn&#39;t ? -or maybe downsides ?-

Mako or Jinja2?

Is there a way to store an array into mysql field? I&#39;m creating a comment rating system so I want to store the arrays of user ids to prevent multiple votings. I&#39;m going to create new table that holds the comment id and the array of user ids who have voted on this comment. Than I&#39;ll join comments table and this table and check whether the current user id exists in the voters array or note. If it does than the voting icons would be disabled. I think I&#39;ll prevent to use mysql query in loop in this way.

Do you happen to know any better ways?

How to store an array into mysql?

Usually when I plot some R line plot and set `ylim=c(0,some_value)`, there is small space between the x axis and y=0.

I would like the y axis to show exactly at y=0 so points (x,0) will be plotted on the y axis (and not above).



Set R plots x axis to show at y=0

<p>Usually when I plot some R line plot and set <code>ylim=c(0,some_value)</code>, there is small space between the x axis and y=0.</p>
<p>I would like the y axis to show exactly at y=0 so points (x,0) will be plotted on the y axis (and not above).</p>


Is there any convenient way to automatically parse command line arguments passed to R scripts?

Something like perl&#39;s `Getopt::Long`?


Parsing command line arguments in R scripts

I have a number, for example 1.128347132904321674821 that I would like to show as only two decimal places when output to screen (or written to a file). How does one do that? 

    x &lt;- 1.128347132904321674821

EDIT: 

The use of: 

    options(digits=2)

Has been suggested as a possible answer. Is there a way to specify this within a script for one-time use? When I add it to my script it doesn&#39;t seem to do anything different and I&#39;m not interested in a lot of re-typing to format each number (I&#39;m automating a very large report). 


-- 

Answer: round(x, digits=2)



Formatting Decimal places in R

When I look at the source of R Packages, i see the function `sweep` used quite often.
Sometimes it&#39;s used when a simpler function would have sufficed (e.g., `apply`),
other times, it&#39;s impossible to know exactly what it&#39;s is doing without
spending a fair amount of time to step through the code block it&#39;s in.

The fact that I can reproduce `sweep`&#39;s effect using a simpler function suggests that
i don&#39;t understand `sweep`&#39;s core use cases, and the fact that this function is used so often suggests that it&#39;s quite useful.

The context:

`sweep` is a function in R&#39;s standard library; its arguments are:

    sweep(x, MARGIN, STATS, FUN=&quot;-&quot;, check.margin=T, ...)

    # x is the data
    # STATS refers to the summary statistics which you wish to &#39;sweep out&#39;
    # FUN is the function used to carry out the sweep, &quot;-&quot; is the default

As you can see, the arguments are similar to `apply` though `sweep` requires
one more parameter, `STATS`.

Another key difference is that `sweep` returns an array of the *same shape* as the input array, whereas the result returned by `apply` depends on the function passed in.

`sweep` in action:

    # e.g., use &#39;sweep&#39; to express a given matrix in terms of distance from 
    # the respective column mean

    # create some data:
    M = matrix( 1:12, ncol=3)

    # calculate column-wise mean for M
    dx = colMeans(M)

    # now &#39;sweep&#39; that summary statistic from M
    sweep(M, 2, dx, FUN=&quot;-&quot;)

         [,1] [,2] [,3]
    [1,] -1.5 -1.5 -1.5
    [2,] -0.5 -0.5 -0.5
    [3,]  0.5  0.5  0.5
    [4,]  1.5  1.5  1.5


So in sum, what i&#39;m looking for is an exemplary use case or two for `sweep`.

Please, do not recite or link to the R Documentation, mailing lists, or any of the &#39;primary&#39; R sources--assume I&#39;ve read them. What I&#39;m interested in is how experienced R programmers/analysts use `sweep` in their own code.


How to use the &#39;sweep&#39; function

One of the basic data types in R is factors. In my experience factors are basically a pain and I never use them. I always convert to characters. I feel oddly like I&#39;m missing something. 

Are there some important examples of functions that use factors as grouping variables where the factor data type becomes necessary? Are there specific circumstances when I *should* be using factors?

Factors in R: more than an annoyance?

Given a data frame &quot;foo&quot;, how can I select only those rows from &quot;foo&quot; where e.g. `foo$location = &quot;there&quot;`?

    foo = data.frame(location = c(&quot;here&quot;, &quot;there&quot;, &quot;here&quot;, &quot;there&quot;, &quot;where&quot;), x = 1:5, y = 6:10)
    foo
    #   location x  y
    # 1     here 1  6
    # 2    there 2  7
    # 3     here 3  8
    # 4    there 4  9
    # 5    where 5 10

Desired result, &quot;bar&quot;:

    #   location x y
    # 2    there 2 7
    # 4    there 4 9

Subset / filter rows in a data frame based on a condition in a column

I&#39;m trying to draw a smooth curve in `R`. I have the following simple toy data:

    &gt; x
     [1]  1  2  3  4  5  6  7  8  9 10
    &gt; y
     [1]  2  4  6  8  7 12 14 16 18 20

Now when I plot it with a standard command it looks bumpy and edgy, of course:

    &gt; plot(x,y, type=&#39;l&#39;, lwd=2, col=&#39;red&#39;)

How can I make the curve smooth so that the 3 edges are rounded using estimated values? I know there are many methods to fit a smooth curve but I&#39;m not sure which one would be most appropriate for this type of curve and how you would write it in `R`. 

How to fit a smooth curve to my data in R?

I frequently use kernel density plots to illustrate distributions. These are easy and fast to create in R like so:

    set.seed(1)
    draws &lt;- rnorm(100)^2
    dens &lt;- density(draws)
    plot(dens)
    #or in one line like this: plot(density(rnorm(100)^2))

Which gives me this nice little PDF:

[![enter image description here][1]][1]

I&#39;d like to shade the area under the PDF from the 75th to 95th percentiles. It&#39;s easy to calculate the points using the `quantile` function:

    q75 &lt;- quantile(draws, .75)
    q95 &lt;- quantile(draws, .95)

But how do I shade the the area between `q75` and `q95`?


  [1]: https://i.stack.imgur.com/lAOVK.png

Shading a kernel density plot between two points.

I am using R and I have two data frames: carrots and cucumbers. Each data frame has a single numeric column that lists the length of all measured carrots (total: 100k carrots) and cucumbers (total: 50k cucumbers).

I wish to plot two histograms - carrot length and cucumbers lengths - on the same plot. They overlap, so I guess I also need some transparency. I also need to use relative frequencies not absolute numbers since the number of instances in each group is different. 

Something like this would be nice but I don&#39;t understand how to create it from my two tables:

![overlapped density][1]


  [1]: http://i.stack.imgur.com/nn4JT.png

How to plot two histograms together in R?

I plot the following:

    library(ggplot2)    

    carrots &lt;- data.frame(length = rnorm(500000, 10000, 10000))
    cukes &lt;- data.frame(length = rnorm(50000, 10000, 20000))
    carrots$veg &lt;- &#39;carrot&#39;
    cukes$veg &lt;- &#39;cuke&#39;
    vegLengths &lt;- rbind(carrots, cukes)

    ggplot(vegLengths, aes(length, fill = veg)) +
     geom_density(alpha = 0.2)

Now say, I only want to plot the region between `x=-5000` to `5000`, instead of the entire range.

How can I do that?

How to set limits for axes in ggplot2 R plots?

How can I adjust only the size of Y-axis labels in R?

I know that cex.axis alters the size of the axis labels but it only affects the x-axis. Why, and how can I adjust the y axis?

Content Type	Original Author	Original Content on Stackoverflow
Question	David B	View Question on Stackoverflow
Solution 1 - R	rcs	View Answer on Stackoverflow
Solution 2 - R	WetlabStudent	View Answer on Stackoverflow

Set R plots x axis to show at y=0

R Problem Overview

R Solutions

Solution 1 - R

Solution 2 - R

How to store an array into mysql?

Mako or Jinja2?

Attributions