Use the [`.ndim`][1] property of the ndarray:

    &gt;&gt;&gt; a = np.array([[ -7.94627203e+01,  -1.81562235e+02,  -3.05418070e+02,  -2.38451033e+02],[  9.43740653e+01,   1.69312771e+02,   1.68545575e+01,  -1.44450299e+02],[  5.61599000e+00,   8.76135909e+01,   1.18959245e+02,  -1.44049237e+02]])
    &gt;&gt;&gt; a.ndim
    2


  [1]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.ndim.html

In some cases, you should also add `np.squeeze()` to make sure there are no &quot;empty&quot; dimensions

    &gt;&gt;&gt; a = np.array([[1,2,3]])
    &gt;&gt;&gt; a.ndim
    2
    &gt;&gt;&gt; a = np.squeeze(a)
    &gt;&gt;&gt; a .ndim
    1



I&#39;m using the font library font awesome. It works when the project is not built/uglified with grunt. 

But when I&#39;m building the project with grunt it&#39;s not working. I get this error in console: .../fonts/fontawesome-webfont.woff?v=4.0.3 404 (Not Found) 

I&#39;ve scaffolded the project with yeoman.

This is my ref in index.html

        &lt;!-- build:css styles/fontawesome.css --&gt;
        &lt;link rel=&quot;stylesheet&quot; href=&quot;bower_components/font-awesome/css/font-awesome.min.css&quot;&gt;
        &lt;!-- endbuild --&gt;


Any ideas what can be wrong?

**Update**
I need to copy the folder /bower_components/font-awesome/fonts to dist/fonts. This needs to be done in the grunt-file. Probably under the &quot;copy&quot; options

    copy: {
      dist: {
        files: [{
          expand: true,
          dot: true,
          cwd: &#39;&lt;%= yeoman.app %&gt;&#39;,
          dest: &#39;&lt;%= yeoman.dist %&gt;&#39;,
          src: [
            &#39;*.{ico,png,txt}&#39;,
            &#39;.htaccess&#39;,
            &#39;bower_components/**/*&#39;,
            &#39;images/{,*/}*.{gif,webp}&#39;,
            &#39;styles/fonts/*&#39;
          ]
        }, {
          expand: true,
          cwd: &#39;.tmp/images&#39;,
          dest: &#39;&lt;%= yeoman.dist %&gt;/images&#39;,
          src: [
            &#39;generated/*&#39;
          ]
        }]
      },

But I&#39;m not really sure where to include this. 

Fontawesome is not working when project is built with grunt

Developing an app for an iPhone with audio files that need to be listened too through headphones.

How do I check if headphones aren&#39;t plugged in so I can tell the user to plug in headphones.

I have the following code from another thread but the audioSessionGetProperty method is deprecated. Anyone know how to alter the following code to make this work OR have there own code/solution. 

Thanks.

    - (BOOL)isHeadsetPluggedIn {
        UInt32 routeSize = sizeof (CFStringRef);
        CFStringRef route;


        //Maybe changing it to something like the following would work for iOS7?
        //AVAudioSession* session = [AVAudioSession sharedInstance];
        //OSStatus error = [session setCategory:kAudioSessionProperty_AudioRoute...?
        
    
        //the line below is whats giving me the warning
        OSStatus error = AudioSessionGetProperty (kAudioSessionProperty_AudioRoute,
                                                  &amp;routeSize,
                                                  &amp;route);
        
        /* Known values of route:
         * &quot;Headset&quot;
         * &quot;Headphone&quot;
         * &quot;Speaker&quot;
         * &quot;SpeakerAndMicrophone&quot;
         * &quot;HeadphonesAndMicrophone&quot;
         * &quot;HeadsetInOut&quot;
         * &quot;ReceiverAndMicrophone&quot;
         * &quot;Lineout&quot;
         */
        
        if (!error &amp;&amp; (route != NULL)) {
            
            NSString* routeStr = (__bridge NSString*)route;
            
            NSRange headphoneRange = [routeStr rangeOfString : @&quot;Head&quot;];
            
            if (headphoneRange.location != NSNotFound) return YES;
            
        }
        
        return NO;
    }

Are headphones plugged in? iOS7

I want to check if a numpy array is multidimensional or not?

    V = [[ -7.94627203e+01  -1.81562235e+02  -3.05418070e+02  -2.38451033e+02][  9.43740653e+01   1.69312771e+02   1.68545575e+01  -1.44450299e+02][  5.61599000e+00   8.76135909e+01   1.18959245e+02  -1.44049237e+02]]

How can I do that in numpy?



check if numpy array is multidimensional or not

I want to check if a numpy array is multidimensional or not?
<pre><code class="hljs language-lua">V = [[ -7.94627203e+01 -1.81562235e+02 -3.05418070e+02 -2.38451033e+02][ 9.43740653e+01 1.69312771e+02 1.68545575e+01 -1.44450299e+02][ 5.61599000e+00 8.76135909e+01 1.18959245e+02 -1.44049237e+02]]
</code></pre>
How can I do that in numpy?

Given a list

    l = [1, 7, 3, 5]

I want to iterate over all pairs of consecutive list items `(1,7), (7,3), (3,5)`, i.e.

    for i in xrange(len(l) - 1):
        x = l[i]
        y = l[i + 1]
        # do something

I would like to do this in a more compact way, like

    for x, y in someiterator(l): ...

Is there a way to do do this using builtin Python iterators? I&#39;m sure the `itertools` module should have a solution, but I just can&#39;t figure it out.

Iterate over all pairs of consecutive items in a list

I deleted a pip package with `rm -rf` command thinking that the package will be removed. Now the package has been deleted but it still shows up in `pip list` and I&#39;m unable to remove it with `pip uninstall` nor can I update with `pip install --upgrade`. 




I&#39;d like to remove it completely. Can anyone please tell me how?


**EDIT**

The package is psycopg2.

If I try to uninstall :

    hammad@hammad-P5QL-E:~$ pip uninstall psycopg2
    Can&#39;t uninstall &#39;psycopg2&#39;. No files were found to uninstall.

This is the directory in which psycopg2 was located `/usr/lib/python2.7/dist-packages`and I `rm -rf` &#39;d it from the same directory.

TIA

How to remove pip package after deleting it manually

I want to implement a function that gives information about all the tables (and their column names) that are present in a database (not only those created with SQLAlchemy). While reading the documentation it seems to me that this is done via reflection but I didn&#39;t manage to get something working. Any suggestions or examples on how to do this?

List database tables with SQLAlchemy

How can I divide two numbers in Python 2.7 and get the result with decimals?

I don&#39;t get it why there is difference:

in Python 3: 

    &gt;&gt;&gt; 20/15
    1.3333333333333333

in Python 2:

    &gt;&gt;&gt; 20/15
    1

Isn&#39;t this a modulo actually?

Division in Python 2.7. and 3.3

I&#39;d like to concatenate two dataframes `A`, `B` to a new one without duplicate rows (if rows in `B` already exist in `A`, don&#39;t add):

Dataframe `A`:
              
       I    II   
    0  1    2    
    1  3    1    

Dataframe `B`:

       I    II
    0  5    6
    1  3    1

New Dataframe:

         I    II
      0  1    2
      1  3    1
      2  5    6

How can I do this?
   


How to concatenate two dataframes without duplicates?

What does `np.random.seed` do in the below code from a Scikit-Learn tutorial? I&#39;m not very familiar with NumPy&#39;s random state generator stuff, so I&#39;d really appreciate a layman&#39;s terms explanation of this.

    np.random.seed(0)
    indices = np.random.permutation(len(iris_X))

What does numpy.random.seed(0) do?

Following the documentation for setting up Sphinx documentation links between packages, I have added 

    intersphinx_mapping = {&#39;python&#39;: (&#39;http://docs.python.org/2&#39;, None),
                           &#39;numpy&#39;: (&#39;http://docs.scipy.org/doc/numpy/&#39;, None),
                           &#39;scipy&#39;: (&#39;http://docs.scipy.org/doc/scipy/reference/&#39;, None),
                           &#39;matplotlib&#39;: (&#39;http://matplotlib.sourceforge.net/&#39;, None)}

to my `conf.py`, but can&#39;t seem to get links to any project other than Python itself to work. For example

    :term:`svg graphics &lt;matplotlib:svg&gt;`

just takes me to the index page, without adding the expected `#term-svg` anchor, and I can&#39;t even locate the glossary for `scipy` or figure out how to determine what `:ref:`s or `:term:`s are supported by a package.

Where can I find instructions on how to specify targets for `:ref:`s and `:term:`s in `numpy`, `scipy`, and `matplotlib`?

---

For that matter, how do I link to Sphinx itself? Adding

    intersphinx_mapping[&#39;sphinx&#39;] = (&#39;http://sphinx-doc.org/&#39;, None)

and

    :ref:`Intersphinx &lt;intersphinx&gt;`

doesn&#39;t work.



Specifying targets for intersphinx links to numpy, scipy, and matplotlib

When I multiply two `numpy` arrays of sizes (n x n)*(n x 1), I get a matrix of size (n x n). Following normal matrix multiplication rules, an (n x 1) vector is expected, but I simply cannot find any information about how this is done in Python&#39;s Numpy module.

The thing is that I don&#39;t want to implement it manually to preserve the speed of the program.

Example code is shown below:

    a = np.array([[5, 1, 3], [1, 1, 1], [1, 2, 1]])
    b = np.array([1, 2, 3])

    print a*b
       &gt;&gt;
       [[5 2 9]
       [1 2 3]
       [1 4 3]]

What I want is:

    print a*b
       &gt;&gt;
       [16 6 8]


numpy matrix vector multiplication

I&#39;ve written a bunch of code on the assumption that I was going to use Numpy arrays. Turns out the data I am getting is loaded through Pandas. I remember now that I loaded it in Pandas because I was having some problems loading it in Numpy. I believe the data was just too large.

Therefore I was wondering, is there a difference in computational ability when using Numpy vs Pandas?

If Pandas is more efficient then I would rather rewrite all my code for Pandas but if there is no more efficiency then I&#39;ll just use a numpy array...

Is there a performance difference between Numpy and Pandas?

I am using numpy.log10 to calculate the log of an array of probability values. There are some zeros in the array, and I am trying to get around it using
    
    result = numpy.where(prob &gt; 0.0000000001, numpy.log10(prob), -10)



However, `RuntimeWarning: divide by zero encountered in log10` still appeared and I am sure it is this line caused the warning. 

Although my problem is solved, I am confused why this warning appeared again and again?

Content Type	Original Author	Original Content on Stackoverflow
Question	sam	View Question on Stackoverflow
Solution 1 - Python	Ashwini Chaudhary	View Answer on Stackoverflow
Solution 2 - Python	Baragorn	View Answer on Stackoverflow

check if numpy array is multidimensional or not

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

Are headphones plugged in? iOS7

Fontawesome is not working when project is built with grunt

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