This is because of the differences between python 2 and python 3. Use the built-in function `next` in python 3. That is, write `next(reader)` instead of `reader.next()` in line 47. In addition, you should open the file in the text mode. So, change line 47 as `i = open( input_file, &#39;r&#39; )`.

For Python 3.x:

Use ```next(reader)``` instead of ```reader.next()```

I have a bar chart that&#39;s created using chart.js. Everything works fine on page load, but when I change the time frame using a daterangepicker, a glitch appears. The new data is brought in, but when I hover over it, the old data is shown. I&#39;m new to javascript so I&#39;m hoping to get some help. It looks like I need to incorporate .destroy(); somehow, but I don&#39;t know how. A snippet of my code is below:

    function loadFTPRChart(startdate, enddate){
    var BCData = {
    labels: [],
    datasets: [
     {
      label: &quot;Pass %&quot;,
      backgroundColor: &quot;#536A7F&quot;,
      data: [],
      stack: 1
    },
    {
      label: &quot;Fail %&quot;,
      backgroundColor: &quot;#e6e6e6&quot;,
      data: [],
      stack: 1
    },
    {
      label: &quot;Auto %&quot;,
      backgroundColor: &quot;#286090&quot;,
      data: [],
      stack: 2
    },
    {
      label: &quot;Manual %&quot;,
      backgroundColor: &quot;#f0f0f0&quot;,
      data: [],
      stack: 2
    }
     ]
    };
      $.getJSON( &quot;content/FTPR_AM_Graph_ajax.php&quot;, {
        startdate: startdate,
        enddate: enddate,
        location: &quot;M&quot;
    })
    .done(function( data ) {
        console.log(&quot;data&quot;, data);
        $.each( data.aaData, function( key, val ) {
          if(val == &quot;&quot;){return true}
          BCData.labels.push(&quot;Coater &quot; + val[0]);
          BCData.datasets[0].data.push(parseFloat(val[2]));
          BCData.datasets[1].data.push(parseFloat(100-val[2]));
          BCData.datasets[2].data.push(parseFloat(val[1]));
          BCData.datasets[3].data.push(parseFloat(100-val[1]));
        });
  
        var option = {   
         responsive:true,
    };
    console.log(&quot;BCData&quot;, BCData);
  
   
    //console.log(&quot;PrevData&quot;, data);
    var ctx = document.getElementById(&quot;mybarChart2&quot;).getContext(&quot;2d&quot;);
    new Chart(ctx, {
      type: &#39;groupableBar&#39;,
      data: BCData,
      options: {
        scales: {
          yAxes: [{
            ticks: {
              max: 100,
            },
            stacked: true,
          }]
        }
      }
    });
    });
  
    }
  
  
    loadFTPRChart($(&#39;#reportrange&#39;).data().daterangepicker.startDate.format(&#39;MM/DD/YYYY&#39;), $(&#39;#reportrange&#39;).data().daterangepicker.endDate.format(&#39;MM/DD/YYYY&#39;));



What is the best way to destroy the original data so that when I change the date range and hover over the new chart, the old data no longer flickers?

Thanks

Chartjs Bar Chart showing old data when hovering

This is the table partition key setting
[![enter image description here][1]][1]

The table content
[![enter image description here][2]][2]

When I tried to get an item from the table, it prints this error 

&gt; botocore.exceptions.ClientError: An error occurred
&gt; (ValidationException) when calling the GetItem operation: The provided
&gt; key element does not match the schema

This is my code

    dynamodb = boto3.resource(&#39;dynamodb&#39;)
    table = dynamodb.Table(&#39;testDynamodb&#39;)
    response = table.get_item(Key={&#39;userId&#39;: &quot;user2873&quot;})
    item = response[&#39;Item&#39;]
    print(item)

Any ideas? thanks.

  [1]: https://i.stack.imgur.com/RPnjj.png
  [2]: https://i.stack.imgur.com/kbKPU.png

&quot;The provided key element does not match the schema&quot; error when getting an item from DynamoDB

I want to convert a csv file into sparse format file with csv2libsvm.py (https://github.com/zygmuntz/phraug/blob/master/csv2libsvm.py).

The CSV file contains 37 attributes + the label (last column). it doesn&#39;t contain header or index.
Exp of the 1st row:     63651000000.0,63651000000.0,153.1,0,0,0,0,0,0,5,1,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1

When entring the following command line : 
    python csv2libsvm.py Z.csv data.txt 38 1

I got the following error:

    Traceback (most recent call last):
      File &quot;csv2libsvm.py&quot;, line 47, in &lt;module&gt;
        headers = reader.next()
    AttributeError: &#39;_csv.reader&#39; object has no attribute &#39;next&#39;

Do you have any idea about the problem ?

python csv2libsvm.py: AttributeError: &#39;_csv.reader&#39; object has no attribute &#39;next&#39;

I want to convert a csv file into sparse format file with csv2libsvm.py (<a href="https://github.com/zygmuntz/phraug/blob/master/csv2libsvm.py" target="_blank" rel="noopener noreferrer">https://github.com/zygmuntz/phraug/blob/master/csv2libsvm.py</a>).
The CSV file contains 37 attributes + the label (last column). it doesn't contain header or index.
Exp of the 1st row: 63651000000.0,63651000000.0,153.1,0,0,0,0,0,0,5,1,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
When entring the following command line :
python csv2libsvm.py Z.csv data.txt 38 1
I got the following error:
<pre><code class="hljs language-arduino">Traceback (most recent call last):
 File "csv2libsvm.py", line 47, in &#x3C;module>
 headers = reader.next()
AttributeError: '_csv.reader' object has no attribute 'next'
</code></pre>
Do you have any idea about the problem ?

Is there any advantage in using `tf.nn.*` over `tf.layers.*`?

Most of the examples in the doc use `tf.nn.conv2d`, for instance, but it is not clear why they do so.

tf.nn.conv2d vs tf.layers.conv2d

I&#39;m learning about working with streams in Python and I noticed that the [IO docs][1] say the following:

&gt;The easiest way to create a binary stream is with open() with &#39;b&#39; in the mode string:
&gt;
&gt;`f = open(&quot;myfile.jpg&quot;, &quot;rb&quot;)`
&gt;
&gt;In-memory binary streams are also available as BytesIO objects:
&gt;
&gt;`f = io.BytesIO(b&quot;some initial binary data: \x00\x01&quot;)`

What is the difference between `f` as defined by `open` and `f` as defined by `BytesIO`. In other words, what makes a &quot;In-memory binary stream&quot; and how is that different from what `open` does?


  [1]: https://docs.python.org/3/library/io.html

Difference between `open` and `io.BytesIO` in binary streams

I am using Python 2.7.12 in Ubuntu 16.04 LTS. I&#39;m learning how to use boto3 from the following link: https://boto3.readthedocs.io/en/latest/guide/quickstart.html#using-boto-3. My doubt is when to use resource, client, or session, and their respective functionality.

Difference in boto3 between resource, client, and session?

I am a newbie to keras, and when I tried to run my first keras program on my linux, something just didn&#39;t go as I wish.
Here is my python code:

    import numpy as np
    np.random.seed(123)
    from keras.models import Sequential
    from keras.layers import Dense, Dropout, Activation, Flatten
    from keras.layers import Convolution2D, MaxPooling2D
    from keras.utils import np_utils
    from keras.datasets import mnist
    (X_train,y_train),(X_test,y_test) = mnist.load_data()
    print X_train.shape
    from matplotlib import pyplot as plt
    plt.imshow(X_train[0])

The last sentence doesn&#39;t display anything. I copied those codes from a tutorial with out any modification. And there is nothing wrong with the backend of matplotlib on my computer. I have tested that through the code below.

    import matplotlib.pyplot as plt
    
    data = [[0, 0.25], [0.5, 0.75]]
    
    fig, ax = plt.subplots()
    im = ax.imshow(data, cmap=plt.get_cmap(&#39;hot&#39;), interpolation=&#39;nearest&#39;,
                   vmin=0, vmax=1)
    fig.colorbar(im)
    plt.show()

And then I got a image like that:
[![enter image description here][1]][1]


  [1]: https://i.stack.imgur.com/2r6Lw.png

&lt;br&gt;
Moreover, I can get X_train[0] printed and it seems nothing wrong.&lt;br&gt;
So what could be the reason for that? Why the imshow() function in my first code didn&#39;t display anything?

Why plt.imshow() doesn&#39;t display the image?

I found the following example on matplotlib:

    import numpy as np
    import matplotlib.pyplot as plt


    x1 = np.linspace(0.0, 5.0)
    x2 = np.linspace(0.0, 2.0)

    y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
    y2 = np.cos(2 * np.pi * x2)

    plt.subplot(2, 1, 1)
    plt.plot(x1, y1, &#39;ko-&#39;)
    plt.title(&#39;A tale of 2 subplots&#39;)
    plt.ylabel(&#39;Damped oscillation&#39;)


    plt.subplot(2, 1, 2)
    plt.plot(x2, y2, &#39;r.-&#39;)
    plt.xlabel(&#39;time (s)&#39;)
    plt.ylabel(&#39;Undamped&#39;)

    plt.show()


My question is: What do i need to change, to have the plots side-by-side?



How to make two plots side-by-side using Python?

Normally I use Dbeaver for windows and always export my result set like this:

- Run my query --&gt; select the result --&gt; export the result set --&gt; select export to clipboard --&gt; done

This step by step puts my result set in my clipboard and I can paste it wherever I want to work with it.

The problem is that now I am using dbeaver for mac and this guide is not working.
I can go on until the moment that I select my result set like in the image below:

![exporting data set][1]

But once I go further in the process, in the last step I get: [no query][2]


  [1]: https://i.stack.imgur.com/kD5VN.png
  [2]: https://i.stack.imgur.com/vvpqm.png


Note that in &quot;source&quot; it was suppose to show the query that originated the result set, but instead it says just &quot;select.

As a result it does&#39;t select my result or anything (besides being &quot;successful&quot;).

Normally my query would show up there automatically and I couldn&#39;t find any option that corrects this problem in the menus.

Export result set on Dbeaver to CSV

I am using python `csvkit` to compare 2 files like this:

    df1 = pd.read_csv(&#39;input1.csv&#39;, sep=&#39;,\s+&#39;, delimiter=&#39;,&#39;, encoding=&quot;utf-8&quot;)
    df2 = pd.read_csv(&#39;input2.csv&#39;, sep=&#39;,\s,&#39;, delimiter=&#39;,&#39;, encoding=&quot;utf-8&quot;)
    df3 = pd.merge(df1,df2, on=&#39;employee_id&#39;, how=&#39;right&#39;)
    df3.to_csv(&#39;output.csv&#39;, encoding=&#39;utf-8&#39;, index=False)

Currently I am running the file through a script before hand that strips spaces from the `employee_id` column.

An example of `employee_id`s:

    37 78973 3
    23787
    2 22 3
    123

Is there a way to get `csvkit` to do it and save me a step?

Pandas - Strip white space

I have created a MappingsBean class where all the columns of the CSV file are specified. Next I parse XML files and create a list of mappingbeans. Then I write that data into CSV file as report.

I am using following annotations:
        
    public class MappingsBean {

        @CsvBindByName(column = &quot;TradeID&quot;)
        @CsvBindByPosition(position = 0)
        private String tradeId;

        @CsvBindByName(column = &quot;GWML GUID&quot;, required = true)
        @CsvBindByPosition(position = 1)
        private String gwmlGUID;

        @CsvBindByName(column = &quot;MXML GUID&quot;, required = true)
        @CsvBindByPosition(position = 2)
        private String mxmlGUID;

        @CsvBindByName(column = &quot;GWML File&quot;)
        @CsvBindByPosition(position = 3)
        private String gwmlFile;

        @CsvBindByName(column = &quot;MxML File&quot;)
        @CsvBindByPosition(position = 4)
        private String mxmlFile;

        @CsvBindByName(column = &quot;MxML Counterparty&quot;)
        @CsvBindByPosition(position = 5)
        private String mxmlCounterParty;

        @CsvBindByName(column = &quot;GWML Counterparty&quot;)
        @CsvBindByPosition(position = 6)
        private String gwmlCounterParty;
    }

And then I use ```StatefulBeanToCsv``` class to write into CSV file:

    File reportFile = new File(reportOutputDir + &quot;/&quot; + REPORT_FILENAME);
    Writer writer = new PrintWriter(reportFile);
    StatefulBeanToCsv&lt;MappingsBean&gt; beanToCsv = new 
                                  StatefulBeanToCsvBuilder(writer).build();
    beanToCsv.write(makeFinalMappingBeanList());
    writer.close();
     
The problem with this approach is that if I use ```@CsvBindByPosition(position = 0)``` to control 
position then I am not able to generate column names. If I use ```@CsvBindByName(column = &quot;TradeID&quot;)``` then I am not able to set position of the columns.

Is there a way where I can use both annotations, so that I can create CSV files with column headers and also control column position? 

Regards,
Vikram Pathania
     

OpenCSV: How to create CSV file from POJO with custom column headers and custom column positions?

I am new to Python, I am trying to read csv file using below script.

    Past=pd.read_csv(&quot;C:/Users/Admin/Desktop/Python/Past.csv&quot;,encoding=&#39;utf-8&#39;)

But, getting error &quot;UnicodeDecodeError: &#39;utf-8&#39; codec can&#39;t decode byte 0x96 in position 35: invalid start byte&quot;, Please help me to know issue here, I used encoding in script thought it will resolve error.

UnicodeDecodeError: &#39;utf-8&#39; codec can&#39;t decode byte 0x96 in position 35: invalid start byte

I get **ValueError: cannot convert float NaN to integer** for following:

    df = pandas.read_csv(&#39;zoom11.csv&#39;)
    df[[&#39;x&#39;]] = df[[&#39;x&#39;]].astype(int)

 * The &quot;x&quot; is a column in the csv file, I cannot spot any *float NaN* in the file, and I don&#39;t understand the error or why I am getting it. 
 * When I read the column as String, then it has values like -1,0,1,...2000, all look very nice int numbers to me.
 * When I read the column as float, then this can be loaded. Then it shows values as -1.0,0.0 etc, still there are no any NaN-s
 * I tried with *error_bad_lines = False* and dtype parameter in read_csv to no avail. It just cancels loading with same exception.
 * The file is not small (10+ M rows), so cannot inspect it manually, when I extract a small header part, then there is no error, but it happens with full file. So it is something in the file, but cannot detect what.
 * Logically the csv should not have missing values, but even if there is some garbage then I would be ok to skip the rows. Or at least identify them, but I do not see way to scan through file and report conversion errors.

Update: Using the hints in comments/answers I got my data clean with this:

    # x contained NaN
    df = df[~df[&#39;x&#39;].isnull()]

    # Y contained some other garbage, so null check was not enough
    df = df[df[&#39;y&#39;].str.isnumeric()]
    
    # final conversion now worked
    df[[&#39;x&#39;]] = df[[&#39;x&#39;]].astype(int)
    df[[&#39;y&#39;]] = df[[&#39;y&#39;]].astype(int)


Content Type	Original Author	Original Content on Stackoverflow
Question	Zoya	View Question on Stackoverflow
Solution 1 - Python	Hossein	View Answer on Stackoverflow
Solution 2 - Python	Shujat Munawar	View Answer on Stackoverflow

python csv2libsvm.py: AttributeError: '_csv.reader' object has no attribute 'next'

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

"The provided key element does not match the schema" error when getting an item from DynamoDB

Chartjs Bar Chart showing old data when hovering

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