You can now use `%matplotlib notebook` instead of `%matplotlib inline` and you&#39;ll be able to interact with your plots.

Now thanks to [mpld3][1] it&#39;s super easy to enable zooming in inline plots!

All you have to do is install mpld3 (`pip install mpld3`), and then add this to your notebook:

    %matplotlib inline
    import mpld3
    mpld3.enable_notebook()

Now your plots will get a toolbar menu at the bottom left, in which you can enable mouse zooming :)


  [1]: http://mpld3.github.io/

At present, the closest you can come is to redraw it at a larger size using the `figsize` function. It expects dimensions in inches, which caught me out the first time I tried to use it.

There are some plants for a rich backend that would allow plots to be manipulated live, using HTML5, but I think it will be a few more months before that&#39;s ready.

If you&#39;re using the notebook on your local computer, for now the easiest option might be not to use inline mode, so the plots pop up as separate windows.

*mpld3* slowed down the execution of my notebooks. I found it better to use the [nbagg][1] backend that provides the same interactive tools but also allows to save graphs by the right-click menu:

    import matplotlib
    matplotlib.use(&#39;nbagg&#39;)
    import matplotlib.pyplot as plt

  [1]: http://matplotlib.org/users/whats_new.html#the-nbagg-backend

Another good example that has emerged recently is to outsource the job to plotly:

&gt; https://plot.ly/python/3d-plots-tutorial/

Let them handle the rendering, panning, and zooming for you!

`matplotlib.use(&#39;nbagg&#39;)` didnt work for me either. I did find `mdplt3` quite slow. Instead of zooming, I ended up resizing my figure (making it big), using this post: https://stackoverflow.com/questions/29589119/plot-width-settings-in-ipython-notebook


For my unittest, I want to check if two arrays are identical.  Reduced example: 

    a = np.array([1, 2, np.NaN])
    b = np.array([1, 2, np.NaN])

    if np.all(a==b):
        print &#39;arrays are equal&#39;

This does not work because `nan != nan`.
What is the best way to proceed?

Comparing numpy arrays containing NaN

Let&#39;s imagine we have a struct for holding 3 doubles with some member functions:

    struct Vector {
      double x, y, z;
      // ...
      Vector &amp;negate() {
        x = -x; y = -y; z = -z;
        return *this;
      }
      Vector &amp;normalize() {
         double s = 1./sqrt(x*x+y*y+z*z);
         x *= s; y *= s; z *= s;
         return *this;
      }
      // ...
    };

This is a little contrived for simplicity, but I&#39;m sure you agree that similar code is out there. The methods allow you to conveniently chain, for example:

    Vector v = ...;
    v.normalize().negate();

Or even:

    Vector v = Vector{1., 2., 3.}.normalize().negate();

Now if we provided begin() and end() functions, we could use our Vector in a new-style for loop, say to loop over the 3 coordinates x, y, and z (you can no doubt construct more &quot;useful&quot; examples by replacing Vector with e.g. String):

    Vector v = ...;
    for (double x : v) { ... }

We can even do:

    Vector v = ...;
    for (double x : v.normalize().negate()) { ... }

and also:

    for (double x : Vector{1., 2., 3.}) { ... }

However, the following (it seems to me) is broken:

    for (double x : Vector{1., 2., 3.}.normalize()) { ... }

While it seems like a logical combination of the previous two usages, I think this last usage creates a dangling reference while the previous two are completely fine.

- Is this correct and Widely appreciated?   
- Which part of the above is the &quot;bad&quot; part, that should be avoided?   
- Would the language be improved by changing the definition of the range-based for loop such that temporaries constructed in the for-expression exist for the duration of the loop?

Is this a known pitfall of C++11 for loops?

Is it possible to zoom into a plot if inline is activated? Especially regarding to 3d-plots rotating and zooming is a necessary feature. 

ipython notebook --pylab inline: zooming of a plot

<p>Is it possible to zoom into a plot if inline is activated? Especially regarding to 3d-plots rotating and zooming is a necessary feature.</p>


I have a very long query. I would like to split it in several lines in Python. A way to do it in JavaScript would be using several sentences and joining them with a `+` operator (I know, maybe it&#39;s not the most efficient way to do it, but I&#39;m not really concerned about performance in this stage, just code readability). Example:
```python    
var long_string = &#39;some text not important. just garbage to&#39; +
                      &#39;illustrate my example&#39;;
```
I tried doing something similar in Python, but it didn&#39;t work, so I used `\` to split the long string. However, I&#39;m not sure if this is the only/best/pythonicest way of doing it. It looks awkward. 
Actual code:

```python
    query = &#39;SELECT action.descr as &quot;action&quot;, &#39;\
		&#39;role.id as role_id,&#39;\
		&#39;role.descr as role&#39;\
		&#39;FROM &#39;\
		&#39;public.role_action_def,&#39;\
		&#39;public.role,&#39;\
		&#39;public.record_def, &#39;\
		&#39;public.action&#39;\
		&#39;WHERE role.id = role_action_def.role_id AND&#39;\
		&#39;record_def.id = role_action_def.def_id AND&#39;\
		&#39;action.id = role_action_def.action_id AND&#39;\
		&#39;role_action_def.account_id = &#39; + account_id + &#39; AND&#39;\
		&#39;record_def.account_id=&#39; + account_id + &#39; AND&#39;\
		&#39;def_id=&#39; + def_id
```


How to split the definition of a long string over multiple lines?

I&#39;ve been using the following python code to format an integer part ID as a formatted part number string:

    pn = &#39;PN-{:0&gt;9}&#39;.format(id)

I would like to know if there is a way to use that same format string (`&#39;PN-{:0&gt;9}&#39;`) in reverse to extract the integer ID from the formatted part number. If that can&#39;t be done, is there a way to use a single format string (or regex?) to create and parse?

Use Python format string in reverse for parsing

I need to convert time value strings given in the following format to seconds, for example:
```
1.&#39;00:00:00,000&#39; -&gt; 0 seconds

2.&#39;00:00:10,000&#39; -&gt; 10 seconds

3.&#39;00:01:04,000&#39; -&gt; 64 seconds

4.&#39;01:01:09,000&#39; -&gt; 3669 seconds
```

Do I need to use regex to do this? I tried to use the time module, but 
```
time.strptime(&#39;00:00:00,000&#39;,&#39;%I:%M:%S&#39;)
```
throws: 
```
ValueError: time data &#39;00:00:00,000&#39; does not match format &#39;%I:%M:%S&#39;
```


----------


**Edit**:

Looks like this:
```
from datetime import datetime
pt = datetime.strptime(timestring,&#39;%H:%M:%S,%f&#39;)
total_seconds = pt.second + pt.minute*60 + pt.hour*3600
```

gives the correct result. I was just using the wrong module.

How to convert a time string to seconds?

Is it possible to use Python to write cross-platform apps for both iOS and Android

Is it possible to use Python to write cross-platform apps for both iOS and Android?

I have been developing a basic app. Now at the deployment stage it has become clear I have need for both a local settings and production settings.

It would be great to know the following:

 - How best to deal with development and production settings. 
 - How to keep apps such as django-debug-toolbar only in a development environment.
 - Any other tips and best practices for development and deployment settings.

Django: How to manage development and production settings?

I am making a chart in matplotlib and I have many subplots in it each of them with a different title, but on the top I also want to a put a title to the whole chart. How this can be done?

Common title to many subplots in Matplotlib

I am making an application in Python which collects data from a serial port and plots a graph of the collected data against arrival time. The time of arrival for the data is uncertain. I want the plot to be updated when data is received. I searched on how to do this and found two methods:

 1. Clear the plot and re-draw the plot with all the points again.
 2. Animate the plot by changing it after a particular interval.

I do not prefer the first one as the program runs and collects data for a long time (a day for example), and redrawing the plot will be pretty slow.
The second one is also not preferable as time of arrival of data is uncertain and I want the plot to update only when the data is received.

Is there a way in which I can update the plot just by adding more points to it only when the data is received?

Dynamically updating plot in matplotlib

I am new to Python and want to use its `plot` functionality to create graphs. I am using ubuntu 12.04. I followed the Python installation steps from http://eli.thegreenplace.net/2011/10/10/installing-python-2-7-on-ubuntu/ but when I do 

    from pylab import *

I am getting this error

    &gt;&gt;&gt; from pylab import *
    Traceback (most recent call last):
      File &quot;&lt;stdin&gt;&quot;, line 1, in &lt;module&gt;
    ImportError: No module named pylab

My Python version is `python 2.7`. Can anybody tell me what I am missing here?


python error: no module named pylab

I have a simple problem, but I cannot find a good solution to it.

I want to take a NumPy 2D array which represents a grayscale image, and convert it to an RGB PIL image while applying some of the matplotlib colormaps.

I can get a reasonable PNG output by using the `pyplot.figure.figimage` command:

    dpi = 100.0
    w, h = myarray.shape[1]/dpi, myarray.shape[0]/dpi
    fig = plt.figure(figsize=(w,h), dpi=dpi)
    fig.figimage(sub, cmap=cm.gist_earth)
    plt.savefig(&#39;out.png&#39;)

Although I could adapt this to get what I want (probably using StringIO do get the PIL image), I wonder if there is not a simpler way to do that, since it seems to be a very natural problem of image visualization. Let&#39;s say, something like this:

    colored_PIL_image = magic_function(array, cmap)


How to convert a NumPy array to PIL image applying matplotlib colormap

I&#39;m plotting data in Python using matplotlib. I am updating the data of the plot based upon some calculations and want the ylim and xlim to be rescaled automatically. Instead what happens is the scale is set based upon the limits of the initial plot. A MWE is

    import random
    import matplotlib.pyplot as pyplot

    pyplot.ion()

    x = range(10)
    y = lambda m: [m*random.random() for i in range(10)]
    
    pLine, = pyplot.plot(x, y(1))

    for i in range(10):
        pLine.set_ydata(y(i+1))
        pyplot.draw()

The first plot command generates a plot from `[0,1]` and I can see everything just fine. At the end, the y-data array goes from `[0,10)` with most of it greater than `1`, but the y-limits of the figure remain `[0,1]`. 

I know I can manually change the limits using `pyplot.ylim(...)`, but I don&#39;t know what to change them to. In the `for` loop, can I tell pyplot to scale the limits as if it was the first time being plotted?

Automatically Rescale ylim and xlim in Matplotlib

I want to copy already indented Python code / whole functions and classes into IPython. Everytime I try the indentation is screwed up and I get following error message:

`IndentationError: unindent does not match any outer indentation level (&lt;ipython-input-23-354f8c8be51b&gt;, line 12)`

`If you want to paste code into IPython, try the %paste and %cpaste magic functions.`


How does IPython&#39;s magic %paste work?

Error reports from most language kernels running in IPython/Jupyter Notebooks indicate the line on which the error occurred; but (at least by default) no line numbers are indicated in Notebooks.

Is it possibile to add the line numbers to IPython/Jupyter Notebooks?

Showing line numbers in IPython/Jupyter Notebooks

I find myself typing `import numpy as np` almost every single time I fire up the python interpreter. How do I set up the python or ipython interpreter so that numpy is automatically imported?

Automatically import modules when entering the python or ipython interpreter

Is it possible to run a python script (not module) from inside ipython without indicating its path? I tried to set PYTHONPATH but it seems to work only for modules. 
I would like to execute

    %run my_script.py
without being in the directory containing the file.

Running python script inside ipython

I would like to use an [IPython notebook][notebook] as a way to interactively analyze some genome charts I am making with Biopython&#39;s [`GenomeDiagram`][genomediagram] module. While there is extensive documentation on how to use `matplotlib` to get graphs inline in IPython notebook, GenomeDiagram uses the ReportLab toolkit which I don&#39;t think is supported for inline graphing in IPython. 

I was thinking, however, that a way around this would be to write out the plot/genome diagram to a file and then open the image inline which would have the same result with something like this:

    gd_diagram.write(&quot;test.png&quot;, &quot;PNG&quot;)
    display(file=&quot;test.png&quot;)

However, I can&#39;t figure out how to do this - or know if it&#39;s possible. So does anyone know if images can be opened/displayed in IPython?


  [genomediagram]: http://biopython.org/DIST/docs/tutorial/Tutorial.html#sec329
  [notebook]: http://ipython.org/notebook.html

Content Type	Original Author	Original Content on Stackoverflow
Question	varantir	View Question on Stackoverflow
Solution 1 - Python	João Abrantes	View Answer on Stackoverflow
Solution 2 - Python	yonilevy	View Answer on Stackoverflow
Solution 3 - Python	Thomas K	View Answer on Stackoverflow
Solution 4 - Python	Victor Bettachini	View Answer on Stackoverflow
Solution 5 - Python	Andrew Mao	View Answer on Stackoverflow
Solution 6 - Python	Ruta Desai	View Answer on Stackoverflow

ipython notebook --pylab inline: zooming of a plot

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

Solution 3 - Python

Solution 4 - Python

Solution 5 - Python

Solution 6 - Python

Is this a known pitfall of C++11 for loops?

Comparing numpy arrays containing NaN

Attributions