See https://stackoverflow.com/questions/19365513/how-to-add-an-extra-row-to-a-pandas-dataframe/19368360#19368360

Upcoming pandas 0.13 version will allow to add rows through `loc` on non existing index data.

Description is [here][1] and this new feature is called *Setting With Enlargement*.

  [1]: https://pandas-docs.github.io/pandas-docs-travis/indexing.html#setting-with-enlargement

Why not use concat?

    df = pd.concat([df, pd.DataFrame(new_data)])

I&#39;d like to know if there is a &quot;safe&quot; way to convert an object to an `int`, avoiding exceptions.

I&#39;m looking for something like `public static bool TryToInt32(object value, out int result);`

I know I could make something like this:
   
    public static bool TryToInt32(object value, out int result)
    {
        try
        {
            result = Convert.ToInt32(value);
            return true;
        }
        catch
        {
            result = 0;
            return false;
        }
    }

But I&#39;d rather avoid exceptions, because they are slowing down the process.

I think this is more elegant, but it&#39;s still &quot;cheap&quot;:

    public static bool TryToInt32(object value, out int result)
    {
        if (value == null)
        {
            result = 0;
            return false;
        }

        return int.TryParse(value.ToString(), out result);
    }

Does anyone have better ideas?

UPDATE:

This sounds a little like splitting hairs, but converting an object to string forces the implementer to create a clear `ToString()` function. For example:

    public class Percentage
    {
        public int Value { get; set; }

        public override string ToString()
        {
            return string.Format(&quot;{0}%&quot;, Value);
        }
    }

    Percentage p = new Percentage();
    p.Value = 50;

    int v;
    if (int.TryParse(p.ToString(), out v))
    {
        
    }

This goes wrong, I can do two things here, or implement the `IConvertable` like this:

    public static bool ToInt32(object value, out int result)
    {
        if (value == null)
        {
            result = 0;
            return false;
        }

        if (value is IConvertible)
        {
            result = ((IConvertible)value).ToInt32(Thread.CurrentThread.CurrentCulture);
            return true;
        }

        return int.TryParse(value.ToString(), out result);
    }

But the `ToInt32` method of the `IConvertible` cannot be canceled. So if it&#39;s not possible to convert the value, an exception cannot be avoided.

Or two: Is there a way to check if the object contains a implicit operator?

This is very poor:

    if (value.GetType().GetMethods().FirstOrDefault(method =&gt; method.Name == &quot;op_Implicit&quot; &amp;&amp; method.ReturnType == typeof(int)) != null)
    {
        result = (int)value;
        return true;
    }

Is there a try Convert.ToInt32... avoiding exceptions

I have a survey file in which row are observation and column question.

Here are some [fake data][1] they look like:

    People,Food,Music,People
    P1,Very Bad,Bad,Good
    P2,Good,Good,Very Bad
    P3,Good,Bad,Good
    P4,Good,Very Bad,Very Good
    P5,Bad,Good,Very Good
    P6,Bad,Good,Very Good


My aim is to create this kind of plot with `ggplot2`. 

 - I absolutely **don&#39;t care of the colors, design, etc.**
 - The plot doesn&#39;t correspond to the fake data

![enter image description here][2]


Here are my fake data:

    raw &lt;- read.csv(&quot;http://pastebin.com/raw.php?i=L8cEKcxS&quot;,sep=&quot;,&quot;)
    raw[,2]&lt;-factor(raw[,2],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)
    raw[,3]&lt;-factor(raw[,3],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)
    raw[,4]&lt;-factor(raw[,4],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)


But if I choose Y as count then I&#39;m facing an issue about choosing the X and the Group values... I don&#39;t know if I can succeed without using `reshape2`... I&#39;ve also tired to use reshape with melt function. But I don&#39;t understand how to use it...


  [1]: http://pastebin.com/raw.php?i=L8cEKcxS
  [2]: http://i.stack.imgur.com/yCWRc.png

Grouped bar plot in ggplot

The pandas [documentation](http://pandas.pydata.org/pandas-docs/stable/merging.html) includes a note:

&gt;Note Unlike list.append method, which appends to the original list and returns nothing, append here does not modify df1 and returns its copy with df2 appended.

How can I append to an existing DataFrame without making a copy? Or in the terms of the note how can I modify df1 in place by appending df2 and return nothing?



Append rows to a pandas DataFrame without making a new copy

The pandas <a href="http://pandas.pydata.org/pandas-docs/stable/merging.html" target="_blank" rel="noopener noreferrer">documentation</a> includes a note:
>Note Unlike list.append method, which appends to the original list and returns nothing, append here does not modify df1 and returns its copy with df2 appended.
How can I append to an existing DataFrame without making a copy? Or in the terms of the note how can I modify df1 in place by appending df2 and return nothing?

I&#39;ve been doing a lot of research lately into using Pyramid with SQLAlchemy versus keeping a current application in Django.  That by itself is an entire debate, but I&#39;m not here to discuss that.

What I do want to know is, why is SQLAlchemy universally considered better than Django ORM?  Almost every, if not every, comparison I&#39;ve found between the two favors SQLAlchemy.  I assume performance is a big one, as the structure of SQLAlchemy lets it translate to SQL much more smoothly.

But, I&#39;ve also heard that with harder tasks, Django ORM is nearly impossible to use.  I want to scope out how huge of an issue this can be.  I&#39;ve been reading one of the reasons to switch to SQLAlchemy is when Django ORM is no longer suiting your needs.

So, in short, could someone provide a query (doesn&#39;t have to be actual SQL syntax) that SQLAlchemy can do, but Django ORM cannot possibly do without adding in additional raw SQL?

**Update**:

I&#39;ve been noticing this question getting quite some attention since I first asked, so I&#39;d like to throw in my extra two cents.

In the end we ended up using SQLAlchemy and I must say I&#39;m happy with the decision.

I&#39;m revisiting this question to provide an additional feature of SQLAlchemy that, so far, I&#39;ve not been able to replicate in Django ORM.  If someone can provide an example of how to do this I&#39;ll gladly eat my words.

Let&#39;s say you want to use some postgresql function, such as similarity(), which provides a fuzzy comparison (see: https://stackoverflow.com/questions/11249635/finding-similar-strings-with-postgresql-quickly - tl;dr input two strings get back a percent similarity).

I&#39;ve done some searching on how to do this using the Django ORM and have found nothing other than using raw sql as seems to be apparent from their documentation: https://docs.djangoproject.com/en/dev/topics/db/sql/.

i.e.

    Model.objects.raw(&#39;SELECT * FROM app_model ORDER BY \
    similarity(name, %s) DESC;&#39;, [input_name])

SQLalchemy, however, has func(), as described here: http://docs.sqlalchemy.org/en/latest/core/sqlelement.html#sqlalchemy.sql.expression.func

    from sqlalchemy import desc, func
    session.query(Model).order_by(func.similarity(Model.name, input_name))

This allows you to generate sql for any defined sql/postgresql/etc function and not require raw sql.

Example of what SQLAlchemy can do, and Django ORM cannot

I have the following DataFrame:

       a  b  c
    b
    2  1  2  3
    5  4  5  6

As you can see, column `b` is used as an index. I want to get the ordinal number of the row fulfilling `(&#39;b&#39; == 5)`, which in this case would be `1`.

The column being tested can be either an index column (as with `b` in this case) or a regular column, e.g. I may want to find the index of the row fulfilling `(&#39;c&#39; == 6)`.

Getting the integer index of a Pandas DataFrame row fulfilling a condition?

I am trying my very first formal python program using Threading and Multiprocessing on a windows machine. I am unable to launch the processes though, with python giving the following message. The thing is, I am not launching my threads in the __main__ module. The threads are handled in a separate module inside a class.


**EDIT**: By the way this code runs fine on ubuntu. Not quite on windows

    RuntimeError: 
                Attempt to start a new process before the current process
                has finished its bootstrapping phase.
                This probably means that you are on Windows and you have
                forgotten to use the proper idiom in the main module:
                    if __name__ == &#39;__main__&#39;:
                        freeze_support()
                        ...
                The &quot;freeze_support()&quot; line can be omitted if the program
                is not going to be frozen to produce a Windows executable.

My original code is pretty long, but I was able to reproduce the error in an abridged version of the code. It is split in two files, the first is the main module and does very little other than import the module which handles processes/threads and calls a method. The second module is where the meat of the code is.

----------

**testMain.py:**

    import parallelTestModule
    
    extractor = parallelTestModule.ParallelExtractor()
    extractor.runInParallel(numProcesses=2, numThreads=4)

----------

**parallelTestModule.py:**

    import multiprocessing
    from multiprocessing import Process
    import threading
            
    class ThreadRunner(threading.Thread):
        &quot;&quot;&quot; This class represents a single instance of a running thread&quot;&quot;&quot;
        def __init__(self, name):
            threading.Thread.__init__(self)
            self.name = name
        def run(self):
            print self.name,&#39;\n&#39;
                    
    class ProcessRunner:
        &quot;&quot;&quot; This class represents a single instance of a running process &quot;&quot;&quot;
        def runp(self, pid, numThreads):
            mythreads = []
            for tid in range(numThreads):
                name = &quot;Proc-&quot;+str(pid)+&quot;-Thread-&quot;+str(tid)
                th = ThreadRunner(name)
                mythreads.append(th) 
            for i in mythreads:
                i.start()
            for i in mythreads:
                i.join()
            
    class ParallelExtractor:    
        def runInParallel(self, numProcesses, numThreads):
            myprocs = []
            prunner = ProcessRunner()
            for pid in range(numProcesses):
                pr = Process(target=prunner.runp, args=(pid, numThreads)) 
                myprocs.append(pr) 
    #        if __name__ == &#39;parallelTestModule&#39;:    #This didnt work
    #        if __name__ == &#39;__main__&#39;:              #This obviously doesnt work
    #        multiprocessing.freeze_support()        #added after seeing error to no avail
            for i in myprocs:
                i.start()

            for i in myprocs:
                i.join()



RuntimeError on windows trying python multiprocessing

Are there any helper methods to draw a rotated rectangle that is returned by [cv2.minAreaRect()][1] presumably as `((x1,y1),(x2,y2),angle)`? [cv2.rectangle()][2] does not support an angle.
And since the tuple returned is not of the &quot;RotatedRect&quot; class (because it seems to not be implemented in the Python bindings) there is no `points()` method, as shown in the C++ tutorial [&quot;Creating Bounding rotated boxes and ellipses for contours&#182;&quot;][3].

How could a rotated rectangle be drawn from lines - rotate about the center point or the first point given?


  [1]: http://docs.opencv.org/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html?highlight=minarearect#cv2.minAreaRect
  [2]: http://docs.opencv.org/modules/core/doc/drawing_functions.html#rectangle
  [3]: http://docs.opencv.org/doc/tutorials/imgproc/shapedescriptors/bounding_rotated_ellipses/bounding_rotated_ellipses.html#bounding-rotated-ellipses

OpenCV Python: Draw minAreaRect ( RotatedRect not implemented)

I&#39;ve recently discovered (via StackOverflow) that to call a method in a base class I should call:

`super([[derived class]], self).[[base class method]]()`

That&#39;s fine, it works.  However, I find myself often copying and pasting between classes when I make a change and frequently I forget to fix the derived class argument to the super() function.  

I&#39;d like to avoid having to remember to change the derived class argument.  Can I instead just use `self.__class__` as the first argument of the super() function?

It seems to work but are there good reasons why I shouldn&#39;t do this?

When calling super() in a derived class, can I pass in self.__class__?

I am using pandas/python and I have two date time series s1 and s2, that have been generated using the &#39;to_datetime&#39; function on a field of the df containing dates/times.

When I subtract s1 from s2

&gt; s3 = s2 - s1

I get a series, s3, of type 

&gt; timedelta64[ns]

    0    385 days, 04:10:36
    1     57 days, 22:54:00
    2    642 days, 21:15:23
    3    615 days, 00:55:44
    4    160 days, 22:13:35
    5    196 days, 23:06:49
    6     23 days, 22:57:17
    7      2 days, 22:17:31
    8    622 days, 01:29:25
    9     79 days, 20:15:14
    10    23 days, 22:46:51
    11   268 days, 19:23:04
    12                  NaT
    13                  NaT
    14   583 days, 03:40:39

How do I look at 1 element of the series:

&gt; s3[10]

I get something like this:

&gt; numpy.timedelta64(2069211000000000,&#39;ns&#39;)

How do I extract days from s3 and maybe keep them as integers(not so interested in hours/mins etc.)?

Thanks in advance for any help.

extracting days from a numpy.timedelta64 value

Looks ugly:

    df_cut = df_new[
                 (
                 (df_new[&#39;l_ext&#39;]==31) |
                 (df_new[&#39;l_ext&#39;]==22) |
                 (df_new[&#39;l_ext&#39;]==30) |
                 (df_new[&#39;l_ext&#39;]==25) |
                 (df_new[&#39;l_ext&#39;]==64)
                 )
                ]

Does not work:

    df_cut = df_new[(df_new[&#39;l_ext&#39;] in [31, 22, 30, 25, 64])]

Is there an elegant and working solution of the above &quot;problem&quot;?

How to check if a value is in the list in selection from pandas data frame?

Lets say I have a MultiIndex Series `s`:

    &gt;&gt;&gt; s
         values
    a b
    1 2  0.1 
    3 6  0.3
    4 4  0.7

and I want to apply a function which uses the index of the row:

    def f(x):
       # conditions or computations using the indexes
       if x.index[0] and ...: 
       other = sum(x.index) + ...
       return something

How can I do `s.apply(f)` for such a function? What is the recommended way to make this kind of operations? I expect to obtain a new Series with the values resulting from this function applied on each row and the same MultiIndex.

Access index in pandas.Series.apply

I know this is a very basic question but for some reason I can&#39;t find an answer. How can I get the index of certain element of a Series in python pandas? (first occurrence would suffice)

I.e., I&#39;d like something like:

    import pandas as pd
    myseries = pd.Series([1,4,0,7,5], index=[0,1,2,3,4])
    print myseries.find(7) # should output 3

Certainly, it is possible to define such a method with a loop:

    def find(s, el):
        for i in s.index:
            if s[i] == el: 
                return i
        return None
   
    print find(myseries, 7)

but I assume there should be a better way. Is there?

Content Type	Original Author	Original Content on Stackoverflow
Question	cameron.bracken	View Question on Stackoverflow
Solution 1 - Python	Nasser Al-Wohaibi	View Answer on Stackoverflow
Solution 2 - Python	mattexx	View Answer on Stackoverflow

Append rows to a pandas DataFrame without making a new copy

Python Problem Overview

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Solution 1 - Python

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Grouped bar plot in ggplot

Is there a try Convert.ToInt32... avoiding exceptions

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