Try setting `ylab=&quot;&quot;` in your `plot` call and use `title` to set the label of the y-axis manually. Using `line` you could adjust the position of the label, e.g.:

    plot(1:length(w), w, type=&quot;b&quot;, xlab=&quot;Number of clusters&quot;, ylab=&quot;&quot;,
         main=&quot;K=5 eliminates most of the within-cluster variance&quot;,
         cex.main=1.5,
         cex.lab=1.2,
         font.main=20,
         yaxt=&#39;n&#39;,lab=c(length(w),5,7), # no ticks on y axis, all ticks on x
         family=&quot;Calibri Light&quot;)

    title(ylab=&quot;Within-cluster variance&quot;, line=0, cex.lab=1.2, family=&quot;Calibri Light&quot;)

![enter image description here][1]

Please read `?title` for more details.


  [1]: http://i.stack.imgur.com/6dwlR.png

Adjust `mgp`, see `?par`

    title(ylab=&quot;Within-cluster variance&quot;, mgp=c(1,1,0), family=&quot;Calibri Light&quot;,cex.lab=1.2)

![enter image description here][1]


  [1]: http://i.stack.imgur.com/Ea99R.png

In Android Studio when you create a new project, you are prompted to put down a domain name.

I already know that you can make one up but what if you want to distribute your app on the Google Play store? Do I need to buy a web domain just to distribute my app even if I will never use my domain?

Android Studio - Company Domain Name

I am using node.js to create a web application. When I run the application (either by opening index.html on the browser or using the command &quot;npm start&quot; on the terminal) I get two errors:    


Uncaught ReferenceError: process is not defined    


Uncaught ReferenceError: require is not defined

I solved the &quot;require is not defined&quot; error by specifically including in my index.html head tag the link to [this][1] script, where the require function is defined.
However, I cannot find something similar for the process function.

My question is doublefold:

1. Why do built-in node.js modules need to be re-defined? Why are they not recognized as they are, that is &quot;built-in modules&quot;? Doesn&#39;t the term &quot;built-in module&quot; mean that a module need not be redefined externaly/second-handedly?

2. Is there a way to solve this problem? My script is very simple, I am just trying to use a basic function of node.js, so I cannot figure out what errors I might have done.

If anyone has come about this problem and has found a way around it or a reason this happens, you would be of great help.


  [1]: http://requirejs.org/docs/release/2.1.17/r.js

Uncaught ReferenceError: process is not defined

I have eliminated labels on the y axis because only the relative amount is really important.

    w &lt;- c(34170,24911,20323,14290,9605,7803,7113,6031,5140,4469)
    plot(1:length(w), w, type=&quot;b&quot;, xlab=&quot;Number of clusters&quot;,
         ylab=&quot;Within-cluster variance&quot;,
         main=&quot;K=5 eliminates most of the within-cluster variance&quot;,
         cex.main=1.5,
         cex.lab=1.2,
         font.main=20,
         yaxt=&#39;n&#39;,lab=c(length(w),5,7), # no ticks on y axis, all ticks on x
         family=&quot;Calibri Light&quot;)

![cluster plot][1]

However, suppressing those tick labels leaves a lot of white space between the y axis label (&quot;Within-cluster variance&quot;) and the y axis.  Is there a way to nudge it back over?  If I somehow set the (invisible) tick labels to go *inside* the axis, would the axis label settles along the axis?

  [1]: http://i.stack.imgur.com/c2ako.png

In R base plot, move axis label closer to axis

I have eliminated labels on the y axis because only the relative amount is really important.
<pre><code class="hljs language-ini">w &#x3C;- c(34170,24911,20323,14290,9605,7803,7113,6031,5140,4469)
plot(1:length(w), w, type="b", xlab="Number of clusters",
 ylab="Within-cluster variance",
 main="K=5 eliminates most of the within-cluster variance",
 cex.main=1.5,
 cex.lab=1.2,
 font.main=20,
 yaxt='n',lab=c(length(w),5,7), # no ticks on y axis, all ticks on x
 family="Calibri Light")
</code></pre>
<img src="http://i.stack.imgur.com/c2ako.png" alt="cluster plot">
However, suppressing those tick labels leaves a lot of white space between the y axis label ("Within-cluster variance") and the y axis. Is there a way to nudge it back over? If I somehow set the (invisible) tick labels to go inside the axis, would the axis label settles along the axis?

(Somewhat related question: https://stackoverflow.com/questions/26470465/enter-new-column-names-as-string-in-dplyrs-rename-function)

In the middle of a `dplyr` chain (`%&gt;%`), I would like to replace multiple column names with functions of their old names (using `tolower` or `gsub`, etc.)
    
    library(tidyr); library(dplyr)
    data(iris)
    # This is what I want to do, but I&#39;d like to use dplyr syntax
    names(iris) &lt;- tolower( gsub(&quot;\\.&quot;, &quot;_&quot;, names(iris) ) )
    glimpse(iris, 60)
    # Observations: 150
    # Variables:
    #   $ sepal_length (dbl) 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6,...
    #   $ sepal_width  (dbl) 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4,...
    #   $ petal_length (dbl) 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4,...
    #   $ petal_width  (dbl) 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3,...
    #   $ species      (fctr) setosa, setosa, setosa, setosa, s...

    # the rest of the chain:
    iris %&gt;% gather(measurement, value, -species) %&gt;%
      group_by(species,measurement) %&gt;%
      summarise(avg_value = mean(value)) 

&lt;strike&gt;I see `?rename` takes the argument `replace` as a `named character vector, with new names as values, and old names as names.`&lt;/strike&gt;

So I tried:

    iris %&gt;% rename(replace=c(names(iris)=tolower( gsub(&quot;\\.&quot;, &quot;_&quot;, names(iris) ) )  ))

but this (a) returns `Error: unexpected &#39;=&#39; in iris %&gt;% ...` and (b) requires referencing by name the data frame from the previous operation in the chain, which in my real use case I couldn&#39;t do.

    iris %&gt;% 
      rename(replace=c(    )) %&gt;% # ideally the fix would go here
      gather(measurement, value, -species) %&gt;%
      group_by(species,measurement) %&gt;%
      summarise(avg_value = mean(value)) # I realize I could mutate down here 
                                         #  instead, once the column names turn into values, 
                                         #  but that&#39;s not the point
    # ---- Desired output looks like: -------
    # Source: local data frame [12 x 3]
    # Groups: species
    # 
    #       species  measurement avg_value
    # 1      setosa sepal_length     5.006
    # 2      setosa  sepal_width     3.428
    # 3      setosa petal_length     1.462
    # 4      setosa  petal_width     0.246
    # 5  versicolor sepal_length     5.936
    # 6  versicolor  sepal_width     2.770
    # ... etc ....  
    

R dplyr: rename variables using string functions

I would like to know if there is a command, using which one can view all the functions that are built into an R package.

For example, let&#39;s say I loaded a package into environment:

    require(dplyr)

Now, I would like to get a list of all the functions present in the `dplyr` package.

Is there any way to get such a list?





Is there a command in R to view all the functions present in a package?

I don&#39;t know what is going on, everything was working great but suddenly I started to have this error message on the documentation:

&gt; Error in fetch(key) : lazy-load database &#39;......descopl.rdb&#39; is
&gt; corrupt

I removed almost all my code and build again then publish to Github, but when I use the other laptop to download the package, the package is being downloaded and loaded but I can&#39;t call any of the functions, and the documentation states that error.

I don&#39;t know what caused the problem, I am using roxygen to generate the documentation.

https://github.com/WilliamKinaan/descopl

Error in fetch(key) : lazy-load database

I&#39;ve read through and successfully use `?connections` in R but I really don&#39;t understand what they are.

 I get that I can download a file, read and write a compressed file, ... (_that is I understand what the result of using a conection (open, do stuff, close) but I really don&#39;t understand what they actually do, why you have to open and close them and so on_).

I&#39;m hoping this will also help me understand how to more effectively use them (principally understand the mechanics of what is happening so I can effectively debug when something is not working).

What exactly is a connection in R?

I have a working solution but am looking for a cleaner, more readable solution that perhaps takes advantage of some of the newer dplyr window functions.

Using the mtcars dataset, if I want to look at the 25th, 50th, 75th percentiles and the mean and count of miles per gallon (&quot;mpg&quot;) by the number of cylinders (&quot;cyl&quot;), I use the following code:

    library(dplyr)
    library(tidyr)

    # load data
    data(&quot;mtcars&quot;)
    
    # Percentiles used in calculation
    p &lt;- c(.25,.5,.75)
    
    # old dplyr solution 
    mtcars %&gt;% group_by(cyl) %&gt;% 
      do(data.frame(p=p, stats=quantile(.$mpg, probs=p), 
                    n = length(.$mpg), avg = mean(.$mpg))) %&gt;%
      spread(p, stats) %&gt;%
      select(1, 4:6, 3, 2)
    
    # note: the select and spread statements are just to get the data into
    #       the format in which I&#39;d like to see it, but are not critical

Is there a way I can do this more cleanly with dplyr using some of the summary functions (n_tiles, percent_rank, etc.)?  By cleanly, I mean without the &quot;do&quot; statement.

Thank you


Using dplyr window functions to calculate percentiles

My python script uses matplotlib to plot a 2D &quot;heat map&quot; of an x, y, z dataset. My x- and y-values represent amino acid residues in a protein and can therefore only be integers. When I zoom into the plot, it looks like this:

![2D heat map with float tick marks][1]

As I said, float values on the x-y axes do not make sense with my data and I therefore want it to look like this:
![enter image description here][2]

Any ideas how to achieve this?
This is the code that generates the plot:

    def plotDistanceMap(self):
		# Read on x,y,z
		x = self.currentGraph[&#39;xData&#39;]
		y = self.currentGraph[&#39;yData&#39;]
		X, Y = numpy.meshgrid(x, y)
		Z = self.currentGraph[&#39;zData&#39;]
		# Define colormap
		cmap = colors.ListedColormap([&#39;blue&#39;, &#39;green&#39;, &#39;orange&#39;, &#39;red&#39;])
		cmap.set_under(&#39;white&#39;)
		cmap.set_over(&#39;white&#39;)
		bounds = [1,15,50,80,100]
		norm = colors.BoundaryNorm(bounds, cmap.N)
		# Draw surface plot
		img = self.axes.pcolor(X, Y, Z, cmap=cmap, norm=norm)
		self.axes.set_xlim(x.min(), x.max())
		self.axes.set_ylim(y.min(), y.max())
		self.axes.set_xlabel(self.currentGraph[&#39;xTitle&#39;])
		self.axes.set_ylabel(self.currentGraph[&#39;yTitle&#39;])
		# Cosmetics
		#matplotlib.rcParams.update({&#39;font.size&#39;: 12})
		xminorLocator = MultipleLocator(10)
		yminorLocator = MultipleLocator(10)
		self.axes.xaxis.set_minor_locator(xminorLocator)
		self.axes.yaxis.set_minor_locator(yminorLocator)
		self.axes.tick_params(direction=&#39;out&#39;, length=6, width=1)
		self.axes.tick_params(which=&#39;minor&#39;, direction=&#39;out&#39;, length=3, width=1)
		self.axes.xaxis.labelpad = 15
		self.axes.yaxis.labelpad = 15
		# Draw colorbar
		colorbar = self.figure.colorbar(img, boundaries = [0,1,15,50,80,100], 
										spacing = &#39;proportional&#39;,
										ticks = [15,50,80,100], 
										extend = &#39;both&#39;)
		colorbar.ax.set_xlabel(&#39;Angstrom&#39;)
		colorbar.ax.xaxis.set_label_position(&#39;top&#39;)
		colorbar.ax.xaxis.labelpad = 20
		self.figure.tight_layout()		
		self.canvas.draw()

  [1]: http://i.stack.imgur.com/Zg4Xw.jpg
  [2]: http://i.stack.imgur.com/pMQ9N.jpg

Matplotlib: How to force integer tick labels?

I&#39;m trying to plot a ROC curve using seaborn (python).
With matplotlib I simply use the function `plot`:

    plt.plot(one_minus_specificity, sensitivity, &#39;bs--&#39;)

where `one_minus_specificity` and `sensitivity` are two lists of paired values.

Is there a simple counterparts of the plot function in seaborn? I had a look at the gallery but I didn&#39;t find any straightforward method.

Simple line plots using seaborn

I have an existing plot that was created with pandas like this:

    df[&#39;myvar&#39;].plot(kind=&#39;bar&#39;)

The y axis is format as float and I want to change the y axis to percentages.  All of the solutions I found use ax.xyz syntax and **I can only place code below the line above that creates the plot** (I cannot add ax=ax to the line above.) 

**How can I format the y axis as percentages without changing the line above?**

Here is the solution I found **but requires that I redefine the plot**:

    import matplotlib.pyplot as plt
    import numpy as np
    import matplotlib.ticker as mtick
    
    data = [8,12,15,17,18,18.5]
    perc = np.linspace(0,100,len(data))
    
    fig = plt.figure(1, (7,4))
    ax = fig.add_subplot(1,1,1)
    
    ax.plot(perc, data)
    
    fmt = &#39;%.0f%%&#39; # Format you want the ticks, e.g. &#39;40%&#39;
    xticks = mtick.FormatStrFormatter(fmt)
    ax.xaxis.set_major_formatter(xticks)
    
    plt.show()

Link to the above solution: https://stackoverflow.com/questions/26294360/pyplot-using-percentage-on-x-axis

Format y axis as percent

I am always bothered when I make a bar plot with pandas and I want to change the names of the labels in the legend. Consider for instance the output of this code:

    import pandas as pd
    from matplotlib.pyplot import *

    df = pd.DataFrame({&#39;A&#39;:26, &#39;B&#39;:20}, index=[&#39;N&#39;])
    df.plot(kind=&#39;bar&#39;)
    
[![enter image description here][1]][1]
Now, if I want to change the name in the legend, I would usually try to do:

    legend([&#39;AAA&#39;, &#39;BBB&#39;])

But I end up with this:

[![enter image description here][2]][2]

In fact, the first dashed line seems to correspond to an additional patch. 

So I wonder if there is a simple trick here to change the labels, or do I need to plot each of the columns independently with matplotlib and set the labels myself. Thanks.


  [1]: http://i.stack.imgur.com/eZoDd.png
  [2]: http://i.stack.imgur.com/QvvRl.png

Modify the legend of pandas bar plot

(Mac OSX 10.10.5)

I can reproduce from the matplotlib website [mplot3d][1] the example code for a 3D scatter plot [scatter3d_demo.py][2], however the plot renders as a static image. I can not click on the graph and dynamically rotate to view the 3D plotted data. 

I have achieved the static 3D plot using the example code - using (a) ipython from within Terminal, (b) ipython notebook from within terminal, and (c) ipython notebook launched from the Anaconda launcher. 

I think I am missing some very basic step as assumed knowledge. 

In past learning, plotting has opened a GUI Python App which has a graph viewer. (Solution 2 in code shown below opens this.) Perhaps I need to know the code to export the output graph to that display method? (Yes, use %matplotlib (only) as first line without inline or notebook as shown in comments in code block below.)

As an example in ipython notebook:
        
        # These lines are comments
        # Initial setup from an online python notebook tutorial is below. 
        # Note the first line &quot;%matplotlib inline&quot; this is how the tutorial has it.
        # Two solutions 1. use: &quot;%matplotlib notebook&quot; graphs appear dynamic in the notebook.
        #               2. use: &quot;%matplotlib&quot; (only) graphs appear dynamic in separate window. 
        #    ( 2. is the best solution for detailed graphs/plots. )
        
        %matplotlib inline  
        import pandas as pd
        import numpy as np
        import matplotlib as mpl
        import matplotlib.pyplot as plt
        from mpl_toolkits.mplot3d import Axes3D

        pd.set_option(&#39;html&#39;,False)
        pd.set_option(&#39;max_columns&#39;,30)
        pd.set_option(&#39;max_rows&#39;,10)


        # What follows is a copy of the 3D plot example code.
        # Data is randomly generated so there is no external data import.
        
        def randrange(n, vmin, vmax):
            return (vmax-vmin)*np.random.rand(n) + vmin

        fig = plt.figure()
        ax = fig.add_subplot(111, projection=&#39;3d&#39;)
        n = 100
        for c, m, zl, zh in [(&#39;r&#39;, &#39;o&#39;, -60, -25), (&#39;b&#39;, &#39;^&#39;, -30, -5)]:
            xs = randrange(n, 23, 50)
            ys = randrange(n, 0, 100)
            zs = randrange(n, zl, zh)
            ax.scatter(xs, ys, zs, c=c, marker=m)
        
        ax.set_xlabel(&#39;X Label&#39;)
        ax.set_ylabel(&#39;Y Label&#39;)
        ax.set_zlabel(&#39;Z Label&#39;)
        
        plt.show()


Can someone identify what I am missing?

Looking at Python 3.3.6 documentation, section 25.1perhaps the tkinter package ...

&gt; The tkinter package (“Tk interface”) is the standard Python interface to the Tk GUI toolkit. Both Tk and tkinter are available on most Unix platforms, as well as on Windows systems.

I think though, this relates to development of GUI programs so I am not sure this is relevant.  (Correct, this was not needed for the solution.) 


    


  [1]: https://matplotlib.org/gallery/#d-plotting
  [2]: https://matplotlib.org/gallery/mplot3d/scatter3d.html#sphx-glr-gallery-mplot3d-scatter3d-py

Content Type	Original Author	Original Content on Stackoverflow
Question	C8H10N4O2	View Question on Stackoverflow
Solution 1 - R	sgibb	View Answer on Stackoverflow
Solution 2 - R	xb.	View Answer on Stackoverflow

In R base plot, move axis label closer to axis

R Problem Overview

R Solutions

Solution 1 - R

Solution 2 - R

Uncaught ReferenceError: process is not defined

Android Studio - Company Domain Name

Attributions