`\text` won&#39;t work because it requires the _amsmath_ package (not included in mathtext - the math rendering engine of matplotlib). So you basically have two options:

* use latex based font rendering

&lt;!-- language: python --&gt;

    from matplotlib import pyplot as plt
    import matplotlib as mpl
    mpl.rcParams[&#39;text.usetex&#39;] = True
    mpl.rcParams[&#39;text.latex.preamble&#39;] = [r&#39;\usepackage{amsmath}&#39;] #for \text command
    plt.plot([1,2,3])
    plt.title(r&quot;$f_{\text{cor, r}}$&quot;)
    plt.show()

2. use mathtext but use `\mathrm` instead of `\text`

&lt;!-- language: python --&gt;

    from matplotlib import pyplot as plt
    import matplotlib as mpl
    mpl.rcParams[&#39;text.usetex&#39;] = False  # not really needed
    plt.plot([1,2,3])
    plt.title(r&quot;$f_{\mathrm{cor, r}}$&quot;)
    plt.show()

The latter approach creates a figure like
![enter image description here][1]    
Be aware that unlike with the `\text` command, spaces inside the `\mathrm` environment are not respected. If you want more space between the variables you have to use latex style commands (`\&lt;space&gt;`, `\;`, ...).


  [1]: http://i.stack.imgur.com/PXSZh.png

One option is to let matplot lib [use LaTeX directly](http://matplotlib.org/users/usetex.html) for your text rendering (rather than the [mathtext](http://matplotlib.org/users/mathtext.html) implementation that matplotlib provides).  

    import matplotlib as mpl
    mpl.rcParams[&#39;text.usetex&#39;] = True
    # (create your plot as before)
    plt.title(r&quot;$f_{\mathrm{cor, r}}$&quot;)


This requires a fully working LaTeX installation.  I can&#39;t seem to get it to recognise `\text`, but `\mathrm` does work (for &#39;roman family&#39; font) just fine.  

is there a way to conveniently merge two data frames side by side?

both two data frames have 30 rows, they have different number of columns, say, df1 has 20 columns and df2 has 40 columns.

how can i easily get a new data frame of 30 rows and 60 columns?


    df3 = pd.someSpecialMergeFunct(df1, df2)

or maybe there is some special parameter in append

    df3 = pd.append(df1, df2, left_index=False, right_index=false, how=&#39;left&#39;)


ps: if possible, i hope the replicated column names could be resolved automatically.

thanks!

How to merge two dataframes side-by-side?

I installed Jenkins on a windows virtual server and want to run it as window service. 

Since the port 8080 is being used by other service, I changed the http port to 8081 in jenkins.xml file. However, I am not able to launch localhost:8081/jenkins at all.  I need detail instruction/steps to configure port 8081 or something to run Jenkins.

How to change port for jenkins window service when 8080 is being used

I am using matplotlib together with latex labels for the axis, title and colorbar labels

While it works really great most of the time, it has some issues when you have a formula using \text.

One really simple example.

    from matplotlib import pyplot as plt
    plt.plot([1,2,3])
    plt.title(r&quot;$f_{\text{cor, r}}$&quot;)

    plt.show()

This will result in an error message like:

    IPython/core/formatters.py:239: FormatterWarning: Exception in image/png formatter: 
    f_{\text{1cor, r}}
       ^
    Unknown symbol: \text (at char 3), (line:1, col:4)
      FormatterWarning,

Is there an easy way to use \text in there? 


\text does not work in a matplotlib label

I am using matplotlib together with latex labels for the axis, title and colorbar labels
While it works really great most of the time, it has some issues when you have a formula using \text.
One really simple example.
<pre><code class="hljs language-python">from matplotlib import pyplot as plt
plt.plot([1,2,3])
plt.title(r"$f_{\text{cor, r}}$")

plt.show()
</code></pre>
This will result in an error message like:
<pre><code class="hljs language-arduino">IPython/core/formatters.py:239: FormatterWarning: Exception in image/png formatter: 
f_{\text{1cor, r}}
 ^
Unknown symbol: \text (at char 3), (line:1, col:4)
 FormatterWarning,
</code></pre>
Is there an easy way to use \text in there?

What&#39;s the best practice to define an abstract instance attribute, but not as a property?

I would like to write something like:

    class AbstractFoo(metaclass=ABCMeta):

        @property
        @abstractmethod
        def bar(self):
            pass

    class Foo(AbstractFoo):

        def __init__(self):
            self.bar = 3

Instead of:

    class Foo(AbstractFoo):

        def __init__(self):
            self._bar = 3
        
        @property
        def bar(self):
            return self._bar

        @bar.setter
        def setbar(self, bar):
            self._bar = bar

        @bar.deleter
        def delbar(self):
            del self._bar

Properties are handy, but for simple attribute requiring no computation they are an overkill. This is especially important for abstract classes which will be subclassed and implemented by the user (I don&#39;t want to force someone to use `@property` when he just could have written `self.foo = foo` in the `__init__`).

https://stackoverflow.com/questions/2736255/abstract-attributes-in-python question proposes as only answer to use `@property` and `@abstractmethod`: it doesn&#39;t answer my question.

The ActiveState recipe for an abstract class attribute via [`AbstractAttribute`](http://code.activestate.com/recipes/577761-simple-abstract-constants-to-use-when-abstractprop) may be the right way, but I am not sure. It also only works with class attributes and not instance attributes.


Abstract attribute (not property)?

I have a pandas data frame where the first 3 columns are strings:

             ID        text1    text 2
    0       2345656     blah      blah
    1          3456     blah      blah
    2        541304     blah      blah        
    3        201306       hi      blah        
    4   12313201308    hello      blah         

I want to add leading zeros to the ID:

                    ID    text1    text 2
    0  000000002345656     blah      blah
    1  000000000003456     blah      blah
    2  000000000541304     blah      blah        
    3  000000000201306       hi      blah        
    4  000012313201308    hello      blah 

I have tried:

    df[&#39;ID&#39;] = df.ID.zfill(15)
    df[&#39;ID&#39;] = &#39;{0:0&gt;15}&#39;.format(df[&#39;ID&#39;])




Add Leading Zeros to Strings in Pandas Dataframe

In the sklearn-python toolbox, there are two functions `transform` and `fit_transform` about `sklearn.decomposition.RandomizedPCA`. The description of two functions are as follows 

![enter image description here][1]
![enter image description here][2]


But what is the difference between them ? 


  [1]: http://i.stack.imgur.com/Oy8kD.png
  [2]: http://i.stack.imgur.com/JpZk6.png

what is the difference between &#39;transform&#39; and &#39;fit_transform&#39; in sklearn

Using [virtualenv][1], I run my projects with the default version of Python (2.7). On one project, I need to use Python 3.4. 

I used `brew install python3` to install it on my Mac. Now, how do I create a virtualenv that uses the new version?

e.g. sudo virtualenv envPython3

If I try:


    virtualenv -p python3 test

I get:

    Running virtualenv with interpreter /usr/local/bin/python3
    Using base prefix &#39;/usr/local/Cellar/python3/3.4.0_1/Frameworks/Python.framework/Versions/3.4&#39;
    New python executable in test/bin/python3.4
    Also creating executable in test/bin/python
    Failed to import the site module
    Traceback (most recent call last):
      File &quot;/Users/user/Documents/workspace/test/test/bin/../lib/python3.4/site.py&quot;, line 67, in &lt;module&gt;
        import os
      File &quot;/Users/user/Documents/workspace/test/test/bin/../lib/python3.4/os.py&quot;, line 634, in &lt;module&gt;
        from _collections_abc import MutableMapping
    ImportError: No module named &#39;_collections_abc&#39;
    ERROR: The executable test/bin/python3.4 is not functioning
    ERROR: It thinks sys.prefix is &#39;/Users/user/Documents/workspace/test&#39; (should be &#39;/Users/user/Documents/workspace/test/test&#39;)
    ERROR: virtualenv is not compatible with this system or executable

[1]: https://virtualenv.pypa.io/en/latest/

Using Python 3 in virtualenv

Under what situations would I want to use one over the other?

What is the difference between:

    &gt;&gt;&gt; import inspect
    &gt;&gt;&gt; print(inspect.getouterframes(inspect.currentframe()))
    [(&lt;frame object at 0x8fc262c&gt;, &#39;&lt;stdin&gt;&#39;, 1, &#39;&lt;module&gt;&#39;, None, None)]

And:

    &gt;&gt;&gt; import traceback
    &gt;&gt;&gt; traceback.extract_stack()
    [(&#39;&lt;stdin&gt;&#39;, 1, &#39;&lt;module&gt;&#39;, None)]

**Update:**

Another:

    &gt;&gt;&gt; import sys
    &gt;&gt;&gt; print(sys._getframe().f_trace,sys._getframe().f_code)
    (None, &lt;code object &lt;module&gt; at 0x8682a88, file &quot;&lt;stdin&gt;&quot;, line 1&gt;)

I do not understand the nuances here:

 - Stack Frame
 - Frame Object
 - Stack Trace

**update 2, a bit of time since the question was asked, but very relevant**

- https://stackoverflow.com/questions/10057443/explain-the-concept-of-a-stack-frame-in-a-nutshell

What is the difference between a stack and a frame?

I would like to add a separate colorbar to each subplot in a 2x2 plot.

    fig , ( (ax1,ax2) , (ax3,ax4)) = plt.subplots(2, 2,sharex = True,sharey=True)
    z1_plot = ax1.scatter(x,y,c = z1,vmin=0.0,vmax=0.4)
    plt.colorbar(z1_plot,cax=ax1)
    z2_plot = ax2.scatter(x,y,c = z2,vmin=0.0,vmax=40)
    plt.colorbar(z1_plot,cax=ax2)
    z3_plot = ax3.scatter(x,y,c = z3,vmin=0.0,vmax=894)
    plt.colorbar(z1_plot,cax=ax3)
    z4_plot = ax4.scatter(x,y,c = z4,vmin=0.0,vmax=234324)
    plt.colorbar(z1_plot,cax=ax4)
    plt.show()

I thought that this is how you do it, but the resulting plot is really messed up; it just has an all grey background and ignores the set_xlim , set_ylim commands I have (not shown here for simplicity). + it shows no color bars. Is this the right way to do it?

I also tried getting rid of the &quot;cax = ...&quot;, but then the colorbar all goes on the bottom right plot and not to each separate plot!

matplotlib colorbar in each subplot

I strongly prefer using `matplotlib` in OOP style:

    f, axarr = plt.subplots(2, sharex=True)
    axarr[0].plot(...)
    axarr[1].plot(...)

This makes it easier to keep track of multiple figures and subplots.

Question: How to use seaborn this way? Or, how to change [this example](http://www.stanford.edu/~mwaskom/software/seaborn/examples/anscombes_quartet.html) to OOP style? How to tell `seaborn` plotting functions like `lmplot` which `Figure` or `Axes` it plots to?

Plotting with seaborn using the matplotlib object-oriented interface

I&#39;m very new to Python and programming in general, so apologies in advance if I&#39;m missing something obvious. I&#39;m trying to plot a graph and label the axes, but every time I try to label the y axis an exception is raised. I wrote the code below in a new script to make sure the problem wasn&#39;t coming from somewhere else in the module. I&#39;m using Python 3.4.

    from numpy import *
    from matplotlib import *
    
    a = [1, 2, 3, 4, 5]
    b = [2, 3, 2, 3, 2]
    pyplot.plot(a, b)
    pylab.xlabel(&quot;Time&quot;)
    pylab.ylabel(&quot;Speed&quot;)

Every time, I get the error &#39;TypeError: &#39;str&#39; object is not callable&#39; for the final line. If I change the y to an x, everything is fine. If I change the x to a y, I get the same error. However, ylabel comes up on the drop down list for ylabel so the function does exist and the documentation says a string is the only necessary argument, exactly as for xlabel (matplotlib.pyplot.ylabel(s, *args, **kwargs) and matplotlib.pyplot.xlabel(s, *args, **kwargs)). What on earth could be going on here?

Strange error with matplotlib axes labels

I have a DataFrame looking like this:

         amount     price
    age
    A     40929   4066443
    B     93904   9611272
    C    188349  19360005
    D    248438  24335536
    E    205622  18888604
    F    140173  12580900
    G     76243   6751731
    H     36859   3418329
    I     29304   2758928
    J     39768   3201269
    K     30350   2867059

Now I&#39;d like to plot a bar-plot with the age on the x-axis as labels. For each x-tick there should be two bars, one bar for the amount, and one for the price. I can get this working by using simply:

    df.plot(kind=&#39;bar&#39;)

The problem is the scaling. The prices are so much higher that I can not really identify the amount in that graph, see:

![enter image description here][1]

Thus I&#39;d like a second y-axis. I tried it using:

    df.loc[:,&#39;amount&#39;].plot(kind=&#39;bar&#39;)
    df.loc[:,&#39;price&#39;].plot(kind=&#39;bar&#39;,secondary_y=True)

but this just overwrites the bars and does NOT place them side-by-side.
Is there any way to do this without having to access the lower-level matplotlib (which would be possible obviously by placing the bars side by side manually)?

For now, I&#39;m using two single plots within subplots:

    df.plot(kind=&#39;bar&#39;,grid=True,subplots=True,sharex=True); 

resulting in:

![enter image description here][2]


  [1]: http://i.stack.imgur.com/8PZSi.png
  [2]: http://i.stack.imgur.com/oSz6a.png

Pandas: Bar-Plot with two bars and two y-axis

Say I have data about 3 trading strategies, each with and without transaction costs.  I want to plot, on the same axes, the time series of each of the 6 variants (3 strategies * 2 trading costs).  I would like the &quot;with transaction cost&quot; lines to be plotted with `alpha=1` and `linewidth=1` while I want the &quot;no transaction costs&quot; to be plotted with `alpha=0.25` and `linewidth=5`.  But I would like the color to be the same for both versions of each strategy. 

I would like something along the lines of:
    
    fig, ax = plt.subplots(1, 1, figsize=(10, 10))
    
    for c in with_transaction_frame.columns:
        ax.plot(with_transaction_frame[c], label=c, alpha=1, linewidth=1)
    
    ****SOME MAGIC GOES HERE TO RESET THE COLOR CYCLE
    
    for c in no_transaction_frame.columns:
        ax.plot(no_transaction_frame[c], label=c, alpha=0.25, linewidth=5)
    
    ax.legend()

What is the appropriate code to put on the indicated line to reset the color cycle so it is &quot;back to the start&quot; when the second loop is invoked?

Content Type	Original Author	Original Content on Stackoverflow
Question	Daniel Wehner	View Question on Stackoverflow
Solution 1 - Python	Jakob	View Answer on Stackoverflow
Solution 2 - Python	Bonlenfum	View Answer on Stackoverflow

\text does not work in a matplotlib label

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

How to change port for jenkins window service when 8080 is being used

How to merge two dataframes side-by-side?

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