try this

    df.rename(columns={ df.columns[1]: &quot;your value&quot; }, inplace = True)

You can do this:

    df.rename(columns={ df.columns[1]: &quot;whatever&quot; })

I am trying to understand few things about Docker:

 1. How can I find the network my container is in ?
 2. Can I dynamically detach my container and attach on an other network ? How?
 3. If I have two containers running, how to check if the two are in the
    same network ? Can I ping one from other ?

 

Docker : How to find the network my container is in?

I have installed a Docker stable version, and it took forever to start. 
Until now I have not seen the notification showing Docker is running. 
I can only see the Docker icon at the taskbar, showing Docker is starting. 

I am running on Windows 10 Pro, Intel Core 2 Duo E8500, supporting virtualization. 


Docker forever in &quot;Docker is starting..&quot; at Windows task

I was just wondering if I can rename column names by their positions.
I know how to rename them by their actual names using:

`df.rename(columns = {})` 

How do I do it if I do not know the column names and know only their positions?

Pandas rename column by position?

I was just wondering if I can rename column names by their positions.
I know how to rename them by their actual names using:
<code>df.rename(columns = {})</code>
How do I do it if I do not know the column names and know only their positions?

I want to remove dataset folder from dataset3 folder. But the following code is not removing dataset. 
First I want to check if dataset already exist in dataset then remove dataset. &lt;br/&gt;
Can some one please point out my mistake in following code?

    for files in os.listdir(&quot;dataset3&quot;):
	    if os.path.exists(&quot;dataset&quot;):
		    os.system(&quot;rm -rf &quot;+&quot;dataset&quot;)

How to check existence of a folder and then remove it?

I am trying to make a very simple `Subquery` that uses `OuterRef` (not for practical purposes, but just to get it working), but I keep running into the same error.

`posts/models.py` code


    from django.db import models

    class Tag(models.Model):
        name = models.CharField(max_length=120)
        def __str__(self):
            return self.name

    class Post(models.Model):
        title = models.CharField(max_length=120)
        tags = models.ManyToManyField(Tag)
        def __str__(self):
            return self.title

`manage.py shell` code

    &gt;&gt;&gt; from django.db.models import OuterRef, Subquery
    &gt;&gt;&gt; from posts.models import Tag, Post
    &gt;&gt;&gt; tag1 = Tag.objects.create(name=&#39;tag1&#39;)
    &gt;&gt;&gt; post1 = Post.objects.create(title=&#39;post1&#39;)
    &gt;&gt;&gt; post1.tags.add(tag1)
    &gt;&gt;&gt; Tag.objects.filter(post=post1.pk)
    &lt;QuerySet [&lt;Tag: tag1&gt;]&gt;
    &gt;&gt;&gt; tags_list = Tag.objects.filter(post=OuterRef(&#39;pk&#39;))
    &gt;&gt;&gt; Post.objects.annotate(count=Subquery(tags_list.count()))

The last two lines should give me number of tags for each Post object. And here I keep getting the same error:

    ValueError: This queryset contains a reference to an outer query and may only be used in a subquery.

Simple Subquery with OuterRef

I have a massive dataframe, and I&#39;m getting the error:

`TypeError: (&quot;Empty &#39;DataFrame&#39;: no numeric data to plot&quot;, &#39;occurred at index 159220&#39;)`

I&#39;ve already dropped nulls, and checked dtypes for the DataFrame so I have no guess as to why it&#39;s failing on that row.

How do I print out just that row (at index 159220) of the data frame?

Thanks

How to print a specific row of a pandas DataFrame?

Just received the Sentry error `TypeError context must be a dict rather than Context.` on one of my forms.  I know it has something to do with Django 1.11, but I am not sure what to change to fix it.

**Offending line**

`message = get_template(&#39;email_forms/direct_donation_form_email.html&#39;).render(Context(ctx))`

**Entire View**

    def donation_application(request):
        if request.method == &#39;POST&#39;:
            form = DirectDonationForm(data=request.POST)
            if form.is_valid():
                stripe.api_key = settings.STRIPE_SECRET_KEY
                name = request.POST.get(&#39;name&#39;, &#39;&#39;)
                address = request.POST.get(&#39;address&#39;, &#39;&#39;)
                city = request.POST.get(&#39;city&#39;, &#39;&#39;)
                state = request.POST.get(&#39;state&#39;, &#39;&#39;)
                zip = request.POST.get(&#39;zip&#39;, &#39;&#39;)
                phone_number = request.POST.get(&#39;phone_number&#39;, &#39;&#39;)
                support = request.POST.get(&#39;support&#39;, &#39;&#39;)
                agree = request.POST.get(&#39;agree&#39;, &#39;&#39;)
                email_address = request.POST.get(&#39;email_address&#39;, &#39;&#39;)
                number = request.POST.get(&#39;number&#39;, &#39;&#39;)
                cvc = request.POST.get(&#39;cvc&#39;, &#39;&#39;)
                exp = request.POST.get(&#39;exp&#39;, &#39;&#39;)
                # token = form.cleaned_data[&#39;stripe_token&#39;],
                # exp_m = int(request.POST.get(&#39;exp_month&#39;, &#39;&#39;))
                # exp_y = int(request.POST.get(&#39;exp_year&#39;, &#39;&#39;))
    
                exp_month = exp[0:2]
                exp_year = exp[5:9]
    
                subject = &#39;New Donation&#39;
                from_email = settings.DEFAULT_FROM_EMAIL
                recipient_list = [&#39;deniselarkins@/////\\\\\.com&#39;,
                                  &#39;charles@/////\\\\\.net&#39;,
                                  &#39;marcmunic@/////\\\\\.com&#39;,
                                  ]
    
                token = stripe.Token.create(
                    card={
                        &#39;number&#39;: number,
                        &#39;exp_month&#39;: exp_month,
                        &#39;exp_year&#39;: exp_year,
                        &#39;cvc&#39;: cvc
                    },
                )
    
                customer = stripe.Customer.create(
                    email=email_address,
                    source=token,
                )
    
                total_support = decimal.Decimal(support) / 100
                total_charge = decimal.Decimal(int(support)) / 100
    
                # Charge the user&#39;s card:
                charge = stripe.Charge.create(
                    amount=total_charge,
                    currency=&#39;usd&#39;,
                    description=&#39;Donation&#39;,
                    customer=customer.id
                )
    
                ctx = {
                    &#39;name&#39;: name,
                    &#39;address&#39;: address,
                    &#39;city&#39;: city,
                    &#39;state&#39;: state,
                    &#39;zip&#39;: zip,
                    &#39;phone_number&#39;: phone_number,
                    &#39;email_address&#39;: email_address,
                    &#39;agree&#39;: agree,
                    &#39;charge&#39;: charge,
                    &#39;customer&#39;: customer,
                    &#39;total_support&#39;: total_support,
                    &#39;total_charge&#39;: total_charge
                }
    
                message = get_template(&#39;email_forms/direct_donation_form_email.html&#39;).render(Context(ctx))
                msg = EmailMessage(subject, message, from_email=from_email, to=recipient_list)
                msg.content_subtype = &#39;html&#39;
                msg.send(fail_silently=True)
    
                return redirect(
                    &#39;/contribute/donation-support-thank-you/?name=&#39; + name +
                    &#39;&amp;address=&#39; + address +
                    &#39;&amp;state=&#39; + state +
                    &#39;&amp;city=&#39; + city +
                    &#39;&amp;zip=&#39; + zip +
                    &#39;&amp;phone_number=&#39; + phone_number +
                    &#39;&amp;email_address=&#39; + email_address +
                    &#39;&amp;total_support=&#39; + str(total_support) +
                    &#39;&amp;total_charge=&#39; + str(total_charge)
                )
        context = {
            &#39;title&#39;: &#39;Donation Pledge&#39;,
        }
    
        return render(request, &#39;contribute/_donation-application.html&#39;, context)

Django 1.11 TypeError context must be a dict rather than Context

I have read through the Beam documentation and also looked through Python documentation but haven&#39;t found a good explanation of the syntax being used in most of the example Apache Beam code. 

Can anyone explain what the `_` , `|` , and `&gt;&gt;` are doing in the below code? Also is the text in quotes ie &#39;ReadTrainingData&#39; meaningful or could it be exchanged with any other label? In other words how is that label being used?

    train_data = pipeline | &#39;ReadTrainingData&#39; &gt;&gt; _ReadData(training_data)
    evaluate_data = pipeline | &#39;ReadEvalData&#39; &gt;&gt; _ReadData(eval_data)

    input_metadata = dataset_metadata.DatasetMetadata(schema=input_schema)

    _ = (input_metadata
    | &#39;WriteInputMetadata&#39; &gt;&gt; tft_beam_io.WriteMetadata(
           os.path.join(output_dir, path_constants.RAW_METADATA_DIR),
           pipeline=pipeline))

    preprocessing_fn = reddit.make_preprocessing_fn(frequency_threshold)
    (train_dataset, train_metadata), transform_fn = (
      (train_data, input_metadata)
      | &#39;AnalyzeAndTransform&#39; &gt;&gt; tft.AnalyzeAndTransformDataset(
          preprocessing_fn))

Explain Apache Beam python syntax

Given this dataframe, how to select only those rows that have &quot;Col2&quot; equal to `NaN`?

    df = pd.DataFrame([range(3), [0, np.NaN, 0], [0, 0, np.NaN], range(3), range(3)], columns=[&quot;Col1&quot;, &quot;Col2&quot;, &quot;Col3&quot;])
    
which looks like:

       0   1   2
    0  0   1   2
    1  0 NaN   0
    2  0   0 NaN
    3  0   1   2
    4  0   1   2

The result should be this one:

       0   1   2
    1  0 NaN   0

How to select rows with NaN in particular column?

If I do 

    mt = mobile.PattLen.value_counts()   # sort True by default

I get

    4    2831
    3    2555 
    5    1561
    [...]

If I do
 
    mt = mobile.PattLen.value_counts(sort=False) 

I get

    8    225
    9    120
    2   1234 
    [...]

What I am trying to do is get the output in 2, 3, 4 ascending order (the left numeric column).  Can I change value_counts somehow or do I need to use a different function. 
    



    

changing sort in value_counts

I&#39;ve been trying to run my code in AWS Lambda which imports pandas. So here is what I&#39;ve done.
I have a python file which contains a simple code as follows(This file has the lambda handler)

    import json
    print(&#39;Loading function&#39;)
    import pandas as pd
    def lambda_handler(event, context):
        return &quot;Welcome to Pandas usage in AWS Lambda&quot;


1. I have zipped this python file along with numpy, pandas and pytz libraries as a deployment package (Did all these in Amazon EC2 linux machine) 
2. Then uploaded the package into S3
3. Created a lambda function(runtime=python3.6) and uploaded the deployment package from S3

But when I test the lambda function in AWS Lambda, I get the below error:

    Unable to import module &#39;lambda_function&#39;: Missing required dependencies [&#39;numpy&#39;]

I already have numpy in the zipped package but still I get this error. I tried to follow the hints given at https://stackoverflow.com/questions/36054976/pandas-aws-lambda but no luck.

Did anyone ran into the same issue. Would appreciate any hint or suggestions to solve this problem.

Thanks


Pandas in AWS lambda gives numpy error

Let&#39;s take a simple function that takes a str and returns a dataframe:

    import pandas as pd
    def csv_to_df(path):
        return pd.read_csv(path, skiprows=1, sep=&#39;\t&#39;, comment=&#39;#&#39;)

***What is the recommended pythonic way of adding type hints to this function?***

If I ask python for the type of a DataFrame it returns `pandas.core.frame.DataFrame`.
The following won&#39;t work though, as it&#39;ll tell me that pandas is not defined.

     def csv_to_df(path: str) -&gt; pandas.core.frame.DataFrame:
         return pd.read_csv(path, skiprows=1, sep=&#39;\t&#39;, comment=&#39;#&#39;)

Content Type	Original Author	Original Content on Stackoverflow
Question	Jun Jang	View Question on Stackoverflow
Solution 1 - Python	Exprator	View Answer on Stackoverflow
Solution 2 - Python	John Zwinck	View Answer on Stackoverflow

Pandas rename column by position?

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

Docker forever in "Docker is starting.." at Windows task

Docker : How to find the network my container is in?

Attributions