Yes, you can try something like:

    plt.xticks(list(plt.xticks()[0]) + extraticks)

The function to use is [`xticks()`][1]. When called without arguments, it returns the current ticks. Calling it with arguments, you can set the tick positions and, optionally, labels.


  [1]: http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.xticks

For the sake of completeness, I would like to give the OO version of @Lev-Levitsky&#39;s great answer:

    lines = plt.plot(x,y)
    ax = lines[0].axes
    ax.set_xticks(list(ax.get_xticks()) + extraticks)

Here we use the `Axes` object extracted from the `Lines2D` sequence returned by `plot`. Normally if you are using the OO interface you would already have a reference to the `Axes` up front and you would call `plot` on that instead of on `pyplot`.

**Corner Caveat**

If for some reason you have modified your axis limits (e.g, by programatically zooming in to a portion of the data), you will need to restore them after this operation:

    lim = ax.get_xlim()
    ax.set_xticks(list(ax.get_xticks()) + extraticks)
    ax.set_xlim(lim)

Otherwise, the plot will make the x-axis show all the available ticks on the axis.

I&#39;m using SQLAlchemy with a MySQL database and I&#39;d like to count the rows in a table (roughly 300k). The SQLAlchemy [count][1] function takes about 50 times as long to run as writing the same query directly in MySQL. Am I doing something wrong?

    # this takes over 3 seconds to return
    session.query(Segment).count()
    
However:

    SELECT COUNT(*) FROM segments;
    +----------+
    | COUNT(*) |
    +----------+
    |   281992 |
    +----------+
    1 row in set (0.07 sec)

The difference in speed increases with the size of the table (it is barely noticeable under 100k rows).

**Update**

Using `session.query(Segment.id).count()` instead of `session.query(Segment).count()` seems to do the trick and get it up to speed. I&#39;m still puzzled why the initial query is slower though.

  [1]: http://docs.sqlalchemy.org/ru/latest/orm/query.html#sqlalchemy.orm.query.Query.count
  

Why is SQLAlchemy count() much slower than the raw query?

I am creating my own bash script, but I am stuck at the moment. Basically, the script would be used to automate server setup in CentOS. Some software normally asks the user to type a password. I want the script to put the password that I have generated and stored as a variable instead of asking the user.

When the message &quot;New password:&quot; appears during install, how can I make the script put the value stored in a variable `$key` as if the user had typed it, with a bash script?



Simulate user input in bash script

I have a simple plot code as

    plt.plot(x,y)
    plt.show()

I want to add some extra ticks on the x-axis in addition to the current ones, let&#39;s say at

    extraticks=[2.1, 3, 7.6]

As you see I do not have a pattern for ticks so I do not want to increase the tick frequency for the whole axis; just keep the original ones and add those extras...

Is it possible, at all?

Regards

adding extra axis ticks using matplotlib

I have a simple plot code as
<pre><code class="hljs language-scss">plt.plot(x,y)
plt.show()
</code></pre>
I want to add some extra ticks on the x-axis in addition to the current ones, let's say at
<pre><code class="hljs language-ini">extraticks=[2.1, 3, 7.6]
</code></pre>
As you see I do not have a pattern for ticks so I do not want to increase the tick frequency for the whole axis; just keep the original ones and add those extras...
Is it possible, at all?
Regards

Python has a few different implementations: CPython, Jython, PyPy, etc.  I want to programmatically determine which implementation my code is running on.  How can I do that?

To be specific, write a function called ``get_implementation_name()`` for me:

    impl_name = get_implementation_name()
    if impl_name == &quot;CPython&quot;:
      print &quot;I can abuse CPython implementation details. (I&#39;m a bad, bad man.)&quot;
    elif impl_name == &quot;PyPy&quot;:
      print &quot;Can&#39;t count on reference-counting garbage collection here...&quot;
    else:
      print &quot;I better be careful...&quot;


How can I tell which python implementation I&#39;m using?

What&#39;s the trivial example of how to generate random colors for passing to plotting functions?

I&#39;m calling scatter inside a loop and want each plot a different color.

    for X,Y in data:
       scatter(X, Y, c=??)

&gt; c:
a color. c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped to colors using the cmap and norm specified via kwargs (see below). Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. c can be a 2-D array in which the rows are RGB or RGBA, however.



How to generate random colors in matplotlib?

I connected to a mysql database using python `con = _mysql.connect(&#39;localhost&#39;, &#39;dell-pc&#39;, &#39;&#39;, &#39;test&#39;)`
The program that I wrote takes a lot of time in full execution i.e. around 10 hours. Actually, I am trying to read distinct words from a corpus. 
After reading was finished there was a timeout error.

I checked Mysql default timeouts which were:

    +----------------------------+----------+
    | Variable_name              | Value    |
    +----------------------------+----------+
    | connect_timeout            | 10       |
    | delayed_insert_timeout     | 300      |
    | innodb_lock_wait_timeout   | 50       |
    | innodb_rollback_on_timeout | OFF      |
    | interactive_timeout        | 28800    |
    | lock_wait_timeout          | 31536000 |
    | net_read_timeout           | 30       |
    | net_write_timeout          | 60       |
    | slave_net_timeout          | 3600     |
    | wait_timeout               | 28800    |
    +----------------------------+----------+

How can I change the default timeout ?

How can I change the default Mysql connection timeout when connecting through python?

Prompted by the discussion [here](https://stackoverflow.com/a/14721700/174728)

The [docs](http://docs.python.org/2/library/functions.html#all) suggest some equivalent code for the behaviour of [`all`](http://docs.python.org/2/library/functions.html#all) and [`any`](http://docs.python.org/2/library/functions.html#any)

Should the behaviour of the equivalent code be considered part of the definition, or can an implementation implement them in a non-shortcircuit manner?

Here is the relevant excerpt from cpython/Lib/test/test_builtin.py

    def test_all(self):
        self.assertEqual(all([2, 4, 6]), True)
        self.assertEqual(all([2, None, 6]), False)
        self.assertRaises(RuntimeError, all, [2, TestFailingBool(), 6])
        self.assertRaises(RuntimeError, all, TestFailingIter())
        self.assertRaises(TypeError, all, 10)               # Non-iterable
        self.assertRaises(TypeError, all)                   # No args
        self.assertRaises(TypeError, all, [2, 4, 6], [])    # Too many args
        self.assertEqual(all([]), True)                     # Empty iterator
        S = [50, 60]
        self.assertEqual(all(x &gt; 42 for x in S), True)
        S = [50, 40, 60]
        self.assertEqual(all(x &gt; 42 for x in S), False)

    def test_any(self):
        self.assertEqual(any([None, None, None]), False)
        self.assertEqual(any([None, 4, None]), True)
        self.assertRaises(RuntimeError, any, [None, TestFailingBool(), 6])
        self.assertRaises(RuntimeError, all, TestFailingIter())
        self.assertRaises(TypeError, any, 10)               # Non-iterable
        self.assertRaises(TypeError, any)                   # No args
        self.assertRaises(TypeError, any, [2, 4, 6], [])    # Too many args
        self.assertEqual(any([]), False)                    # Empty iterator
        S = [40, 60, 30]
        self.assertEqual(any(x &gt; 42 for x in S), True)
        S = [10, 20, 30]
        self.assertEqual(any(x &gt; 42 for x in S), False)

It doesn&#39;t do anything to enforce the shortcircuit behaviour

Is the shortcircuit behaviour of Python&#39;s any/all explicit?

I have a dataset with multi-index columns in a pandas df that I would like to sort by values in a specific column.  I have tried using sortindex and sortlevel but haven&#39;t been able get the results I am looking for.  My dataset looks like:

        Group1    Group2
        A B C     A B C
    1   1 0 3     2 5 7
    2   5 6 9     1 0 0
    3   7 0 2     0 3 5 

I want to sort all data and the index by column C in Group 1 in descending order so my results look like:

        Group1    Group2
        A B C     A B C
     2  5 6 9     1 0 0
     1  1 0 3     2 5 7
     3  7 0 2     0 3 5 


Is it possible to do this sort with the structure that my data is in, or should I be swapping Group1 to the index side?


Multi Index Sorting in Pandas

I can add a y label to the left y-axis using `plt.ylabel`, but how can I add it to the secondary y-axis?


    table = sql.read_frame(query,connection)

    table[0].plot(color=colors[0],ylim=(0,100))
    table[1].plot(secondary_y=True,color=colors[1])
    plt.ylabel(&#39;$&#39;)





Adding a y-axis label to secondary y-axis in matplotlib

I came across [this example][1] in the Matplotlib website. I was wondering if it was possible to increase the figure size.

I tried with

    f.figsize(15,15)

but it does nothing.

  [1]: http://matplotlib.org/examples/pylab_examples/subplots_demo.html


How do I change the figure size with subplots?

I am trying to make a discrete colorbar for a scatterplot in matplotlib

I have my x, y data and for each point an integer tag value which I want to be represented with a unique colour, e.g.

    plt.scatter(x, y, c=tag)

typically tag will be an integer ranging from 0-20, but the exact range may change

so far I have just used the default settings, e.g.

    plt.colorbar()

which gives a continuous range of colours. Ideally i would like a set of n discrete colours (n=20 in this example). Even better would be to get a tag value of 0 to produce a gray colour and 1-20 be colourful.

I have found some &#39;cookbook&#39; scripts but they are very complicated and I cannot think they are the right way to solve a seemingly simple problem

Matplotlib discrete colorbar

I can import matplotlib but when I try to run the following:

    matplotlib.pyplot(x)

   I get:
    
    Traceback (most recent call last):
       File &quot;&lt;pyshell#31&gt;&quot;, line 1, in &lt;module&gt;
           matplotlib.pyplot(x)
    AttributeError: &#39;module&#39; object has no attribute &#39;pyplot&#39;



matplotlib has no attribute &#39;pyplot&#39;

I am fairly new to R and I have the following queries :

I am trying to generate a plot in R which has multiple lines (data series). Each of these lines is a category and I want it to have a unique color. 

Currently my code is setup in this way :

First, I am creating an empty plot :

    plot(1,type=&#39;n&#39;,xlim=c(1,10),ylim=c(0,max_y),xlab=&#39;ID&#39;, ylab=&#39;Frequency&#39;)

Then for each of my category, I am plotting lines in this empty plot using a &quot;for&quot; loop like so :

    for (category in categories){
    lines(data.frame.for.this.category, type=&#39;o&#39;, col=sample(rainbow(10)), lwd=2)
    }

There are 8 categories here, and so there are 8 lines produced in the plot. As you can see, I am trying to sample a color from the rainbows() function to generate a color for each line. 

However, when the plot is generated, I find that there are multiple lines which have the same color. For instance, 3 of those 8 lines have green color. 

How do I make each of these 8 lines have a unique color ? 

Also, how do I reflect this uniqueness in the legend of the plot ? I was trying to lookup the `legend()` function, however it was not clear which parameter I should use to reflect this unique color for each category ? 

Any help or suggestions would be much appreciated.

Plot multiple lines (data series) each with unique color in R

The data I&#39;m playing with comes from the internet source listed below

    nba &lt;- read.csv(&quot;http://datasets.flowingdata.com/ppg2008.csv&quot;, sep=&quot;,&quot;)


What I want to do, is create a 2D points graph comparing two metrics from this table, with each player representing a dot on the graph. I have the following code: 

    nbaplot &lt;- ggplot(nba, aes(x= MIN, y= PTS, colour=&quot;green&quot;, label=Name)) + 
                      geom_point() 

This gives me the following: 

![NBA Plot][1]


  [1]: http://i.stack.imgur.com/RVZz8.png


What I want is a label of player&#39;s name right next to the dots. I thought the label function in ggplot&#39;s aesthetics would do this for me, but it didn&#39;t.  

I also tried `text()` function and the `textxy()` function from `library(calibrate)`, neither of which appears to work with ggplot. 

How can I add name labels to these points? 

Label points in geom_point

I am using matplotlib to make some graphs and unfortunately I cannot export them without the white background. 

![sample plot with solid white background][1]

In other words, when I export a plot like this and position it on top of another image, the white background hides what is behind it rather than allowing it to show through. How can I export plots with a transparent background instead?

  [1]: http://i.stack.imgur.com/wfysS.png



How to export plots from matplotlib with transparent background?

I would like to limit the X and Y axis in matplotlib for a specific subplot.
The subplot figure itself doesn&#39;t have any axis property. I want for example to change only the limits for the second plot:


    import matplotlib.pyplot as plt
    fig=plt.subplot(131)
    plt.scatter([1,2],[3,4])
    fig=plt.subplot(132)
    plt.scatter([10,20],[30,40])
    fig=plt.subplot(133)
    plt.scatter([15,23],[35,43])
    plt.show()



How to set xlim and ylim for a subplot in matplotlib

Is there any way to plot a bar plot using `matplotlib` using data directly from a dict? 

My dict looks like this: 

    D = {u&#39;Label1&#39;:26, u&#39;Label2&#39;: 17, u&#39;Label3&#39;:30}

I was expecting 

    fig = plt.figure(figsize=(5.5,3),dpi=300)
    ax = fig.add_subplot(111)
    bar = ax.bar(D,range(1,len(D)+1,1),0.5)

to work, but it does not. 

Here is the error:

    &gt;&gt;&gt; ax.bar(D,range(1,len(D)+1,1),0.5)
    Traceback (most recent call last):
      File &quot;&lt;stdin&gt;&quot;, line 1, in &lt;module&gt;
      File &quot;/usr/local/lib/python2.7/site-packages/matplotlib/axes.py&quot;, line 4904, in bar
        self.add_patch(r)
      File &quot;/usr/local/lib/python2.7/site-packages/matplotlib/axes.py&quot;, line 1570, in add_patch
        self._update_patch_limits(p)
      File &quot;/usr/local/lib/python2.7/site-packages/matplotlib/axes.py&quot;, line 1588, in _update_patch_limits
        xys = patch.get_patch_transform().transform(vertices)
      File &quot;/usr/local/lib/python2.7/site-packages/matplotlib/patches.py&quot;, line 580, in get_patch_transform
        self._update_patch_transform()
      File &quot;/usr/local/lib/python2.7/site-packages/matplotlib/patches.py&quot;, line 576, in _update_patch_transform
        bbox = transforms.Bbox.from_bounds(x, y, width, height)
      File &quot;/usr/local/lib/python2.7/site-packages/matplotlib/transforms.py&quot;, line 786, in from_bounds
        return Bbox.from_extents(x0, y0, x0 + width, y0 + height)
    TypeError: coercing to Unicode: need string or buffer, float found

Content Type	Original Author	Original Content on Stackoverflow
Question	ahmethungari	View Question on Stackoverflow
Solution 1 - Python	Lev Levitsky	View Answer on Stackoverflow
Solution 2 - Python	Mad Physicist	View Answer on Stackoverflow

adding extra axis ticks using matplotlib

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

Simulate user input in bash script

Why is SQLAlchemy count() much slower than the raw query?

Attributions