pass `level=[0,1]` to just reset those levels:

    dist_df = dist_df.reset_index(level=[0,1])

    In [28]:
    df.reset_index(level=[0,1])

    Out[28]:
                YEAR  MONTH  NI
    datetime                     
    2000-01-01  2000      1   NaN
    2000-01-02  2000      1   NaN
    2000-01-03  2000      1   NaN
    2000-01-04  2000      1   NaN
    2000-01-05  2000      1   NaN


you can pass the label names alternatively:

    df.reset_index(level=[&#39;YEAR&#39;,&#39;MONTH&#39;])

Another simple way would be to set columns for dataframe


    consolidated_data.columns=country_master


ref: https://riptutorial.com/pandas/example/18695/how-to-change-multiindex-columns-to-standard-columns

Is there a way i can remove the &quot;basic-error-controller&quot; from springfox swagger-ui?

Picture:

[![enter image description here][1]][1]


  [1]: http://i.stack.imgur.com/XaWzq.png

Remove Basic Error Controller In SpringFox SwaggerUI

I am making an android app on Android Studio and I have this emulator for Nexus S.
When the emulator is running, it shows the frame of the device.
I want the emulator to show the screen of the device only.
I&#39;ve tried looking in the settings but can&#39;t help it. Thanks.

How to remove the device&#39;s frame on Android Studio&#39;s emulators

                           NI
    YEAR MONTH datetime        
    2000 1     2000-01-01   NaN
               2000-01-02   NaN
               2000-01-03   NaN
               2000-01-04   NaN
               2000-01-05   NaN

In the dataframe above, I have a multilevel index consisting of the columns:

    names=[u&#39;YEAR&#39;, u&#39;MONTH&#39;, u&#39;datetime&#39;]

How do I revert to a dataframe with &#39;datetime&#39; as index and &#39;YEAR&#39; and &#39;MONTH&#39; as normal columns?


Reverting from multiindex to single index dataframe in pandas

<pre><code class="hljs language-yaml"> NI
YEAR MONTH datetime 
2000 1 2000-01-01 NaN
 2000-01-02 NaN
 2000-01-03 NaN
 2000-01-04 NaN
 2000-01-05 NaN
</code></pre>
In the dataframe above, I have a multilevel index consisting of the columns:
<pre><code class="hljs language-python">names=[u'YEAR', u'MONTH', u'datetime']
</code></pre>
How do I revert to a dataframe with 'datetime' as index and 'YEAR' and 'MONTH' as normal columns?

I have a Flask application which uses Flask-SQLAlchemy to connect to a MySQL database.

I would like to be able to check whether a row is present in a table. How would I modify a query like so to check the row exists:

    db.session.query(User).filter_by(name=&#39;John Smith&#39;)


I found a solution on [this question][1] which uses SQLAlchemy but does not seem to fit with the way Flask-SQLAlchemy works:

    from sqlalchemy.sql import exists    
    print session.query(exists().where(User.email == &#39;...&#39;)).scalar()

Thanks.


  [1]: https://stackoverflow.com/a/13336408/2961662

Flask-SQLAlchemy check if row exists in table

It is quite easy to add many pandas dataframes into excel work book as long as it is different worksheets. But, it is somewhat tricky to get many dataframes into one worksheet if you want to use pandas built-in df.to_excel functionality. 

	# Creating Excel Writer Object from Pandas  
    writer = pd.ExcelWriter(&#39;test.xlsx&#39;,engine=&#39;xlsxwriter&#39;)   
	workbook=writer.book
	worksheet=workbook.add_worksheet(&#39;Validation&#39;) 
	df.to_excel(writer,sheet_name=&#39;Validation&#39;,startrow=0 , startcol=0)   
	another_df.to_excel(writer,sheet_name=&#39;Validation&#39;,startrow=20, startcol=0) 


The above code won&#39;t work. You will get the error of 

     Sheetname &#39;Validation&#39;, with case ignored, is already in use.

Now, I have experimented enough that I found a way to make it work. 

	writer = pd.ExcelWriter(&#39;test.xlsx&#39;,engine=&#39;xlsxwriter&#39;)   # Creating Excel Writer Object from Pandas  
	workbook=writer.book
	df.to_excel(writer,sheet_name=&#39;Validation&#39;,startrow=0 , startcol=0)   
	another_df.to_excel(writer,sheet_name=&#39;Validation&#39;,startrow=20, startcol=0) 

This will work. So, my purpose of posting this question on stackoverflow is twofold. Firstly, I hope this will help someone if he/she is trying to put many dataframes into a single work sheet at excel. 

Secondly,  Can someone help me understand the difference between those two blocks of code? It appears to me that they are pretty much the same except the first block of code created worksheet called &quot;Validation&quot; in advance while the second does not. I get that part. 

What I don&#39;t understand is why should it be any different ? Even if I don&#39;t create the worksheet in advance, this line, the line right before the last one, 
 
     df.to_excel(writer,sheet_name=&#39;Validation&#39;,startrow=0 , startcol=0)  

will create a worksheet anyway. Consequently, by the time we reached the last line of code the worksheet &quot;Validation&quot; is already created as well in the second block of code.  So, my question basically, why should the second block of code  work while the first doesn&#39;t?  

Please also share if there is another way to put many dataframes into excel using the built-in df.to_excel functionality !! 

Putting many python pandas dataframes to one excel worksheet

I&#39;m trying to do some text classification using Textblob. I&#39;m first training the model and serializing it using pickle as shown below. 

    import pickle
    from textblob.classifiers import NaiveBayesClassifier
    
    with open(&#39;sample.csv&#39;, &#39;r&#39;) as fp:
         cl = NaiveBayesClassifier(fp, format=&quot;csv&quot;)
    
    f = open(&#39;sample_classifier.pickle&#39;, &#39;wb&#39;)
    pickle.dump(cl, f)
    f.close()

And when I try to run this file:

    import pickle
    f = open(&#39;sample_classifier.pickle&#39;, encoding=&quot;utf8&quot;)
    cl = pickle.load(f)    
    f.close()

I get this error:

&gt; UnicodeDecodeError: &#39;utf-8&#39; codec can&#39;t decode byte 0x80 in position
&gt; 0: invalid start byte

Following are the content of my sample.csv:

&gt; My SQL is not working correctly at all. This was a wrong choice, SQL
&gt; 
&gt; I&#39;ve issues. Please respond immediately, Support



Where am I going wrong here? Please help.

Python pickle error: UnicodeDecodeError

I want to get image width and height, how can I do that in OpenCV?

For example:

    Mat src = imread(&quot;path_to_image&quot;);
    cout &lt;&lt; src.width;

Is that right?

How to get image width and height in OpenCV?

The following is the code that tries to modify the input supplied by a user by using sockets:

    from socket import *

    serverName = &#39;127.0.0.1&#39;
    serverPort = 12000
    clientSocket = socket(AF_INET, SOCK_DGRAM)
    message = input(&#39;Input lowercase sentence:&#39;)
    clientSocket.sendto(message,(serverName, serverPort))
    modifiedMessage, serverAddress = clientSocket.recvfrom(2048)
    print (modifiedMessage)
    clientSocket.close()

When I execute it and supply input the following error occurs:

    Input lowercase sentence:fdsgfdf
    Traceback (most recent call last):
      File &quot;C:\srinath files\NETWORKS\UDPclient.py&quot;, line 6, in &lt;module&gt;
        clientSocket.sendto(message,(serverName, serverPort))
    TypeError: a bytes-like object is required, not &#39;str&#39;

What can I do to solve this?

TypeError: a bytes-like object is required, not &#39;str&#39;

I&#39;ve got a dataframe `df_a` with id information:

        unique_id lacet_number 
    15    5570613  TLA-0138365 
    24    5025490  EMP-0138757 
    36    4354431  DXN-0025343 

and another dataframe `df_b`, with the same number of rows that I know correspond to the rows in `df_a`:

         latitude  longitude 
    0  -93.193560  31.217029  
    1  -93.948082  35.360874  
    2 -103.131508  37.787609  


What I want to do is simply cbind the two and get:

        unique_id lacet_number      latitude  longitude 
    0     5570613  TLA-0138365    -93.193560  31.217029  
    1     5025490  EMP-0138757    -93.948082  35.360874  
    2     4354431  DXN-0025343   -103.131508  37.787609  

What I have tried:

    df_c = pd.concat([df_a, df_b], axis=1)

which gives me an outer join. 

        unique_id lacet_number    latitude  longitude
    0         NaN          NaN  -93.193560  31.217029
    1         NaN          NaN  -93.948082  35.360874
    2         NaN          NaN -103.131508  37.787609
    15    5570613  TLA-0138365         NaN        NaN
    24    5025490  EMP-0138757         NaN        NaN
    36    4354431  DXN-0025343         NaN        NaN

The problem is that the indices for the two dataframes do not match. I read the documentation for [`pandas.concat`](https://pandas.pydata.org/docs/reference/api/pandas.concat.html), and saw that there is an option `ignore_index`. But that only applies to the concatenation axis, in my case the columns and it certainly is not the right choice for me. So my question is: is there a simple way to achieve this?

Pandas column bind (cbind) two data frames

I have some data I&#39;m trying to organize into a `DataFrame` in `Pandas`.  I was trying to make each row a `Series` and append it to the `DataFrame`.  I found a way to do it by appending the `Series` to an empty `list` and then converting the `list` of `Series` to a `DataFrame` 

e.g. `DF = DataFrame([series1,series2],columns=series1.index)`

This `list` to `DataFrame` step seems to be excessive.  I&#39;ve checked out a few examples on here but none of the `Series` preserved the `Index` labels from the `Series` to use them as column labels.

My long way where columns are id_names and rows are type_names:
[![enter image description here][1]][1] 


**Is it possible to append Series to rows of DataFrame without making a list first?**



    #!/usr/bin/python
    
    DF = DataFrame()
    for sample,data in D_sample_data.items():
        SR_row = pd.Series(data.D_key_value)
        DF.append(SR_row)
    DF.head()
    
    TypeError: Can only append a Series if ignore_index=True or if the Series has a name
    

Then I tried


    DF = DataFrame()
    for sample,data in D_sample_data.items():
        SR_row = pd.Series(data.D_key_value,name=sample)
        DF.append(SR_row)
    DF.head()

Empty DataFrame

Tried https://stackoverflow.com/questions/24284342/insert-a-row-to-pandas-dataframe
Still getting an empty dataframe :/ 

**I am trying to get the Series to be the rows, where the index of the Series becomes the column labels of the DataFrame**


  [1]: http://i.stack.imgur.com/L83C8.png

Is it possible to append Series to rows of DataFrame without making a list first?

I have a pandas data frame like this:

       Column1  Column2  Column3  Column4  Column5
     0    a        1        2        3        4
     1    a        3        4        5
     2    b        6        7        8
     3    c        7        7        

What I want to do now is getting a new dataframe containing Column1 and a new columnA. This columnA should contain all values from columns 2 -(to) n (where n is the number of columns from Column2 to the end of the row) like this:

      Column1  ColumnA
    0   a      1,2,3,4
    1   a      3,4,5
    2   b      6,7,8
    3   c      7,7
How could I best approach this issue? Any advice would be helpful. Thanks in advance!

Merge multiple column values into one column in python pandas

I have a data series which looks like this:
    
    print mys

    id_L1
    2       NaN
    3       NaN
    4       NaN
    5       NaN
    6       NaN
    7       NaN
    8       NaN

I would like to check is all the values are NaN. 

My attempt:

    pd.isnull(mys).all()

Output:
  
    True

Is this the correct way to do it? 

Content Type	Original Author	Original Content on Stackoverflow
Question	user308827	View Question on Stackoverflow
Solution 1 - Python	EdChum	View Answer on Stackoverflow
Solution 2 - Python	Shujaath Khan	View Answer on Stackoverflow

Reverting from multiindex to single index dataframe in pandas

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

How to remove the device's frame on Android Studio's emulators

Remove Basic Error Controller In SpringFox SwaggerUI

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