[Samuel Norman &quot;Sam&quot; Seaborn][1] is a fictional character portrayed by Rob Lowe on the television serial drama The West Wing.  

So, it&#39;s a joked initialism.


  [1]: https://en.wikipedia.org/wiki/Sam_Seaborn

I&#39;m working on a small command-line game in python where I am showing a progress bar using the tqdm module. I listen for user input using the msvcrt module to interrupt the progress. Once interrupted, the user can restart by entering &#39;restart&#39; into the command line prompt. The second time the progress bar is shown, instead of updating the same line with the progress, it creates a new line each time. 

How would I get it to show the progress on the same line? 

[![Progress bar issue][1]][1]

This code snippet illustrates my use of the progress bar.

    def transfer():
        for i in tqdm.tqdm(range(1000), desc=&quot;Transfer progress&quot;, ncols=100, bar_format=&#39;{l_bar}{bar}|&#39;):
            sleep(.1)
            if msvcrt.kbhit():
                if msvcrt.getwche() == &#39; &#39;:
                    interrupt()
                    break

    def interrupt():
        type(&quot;File transfer interrupted, to restart the transfer, type &#39;restart&#39;&quot;)



  [1]: https://i.stack.imgur.com/I3yC2.png

tqdm printing to newline

[FormGroup][1]:

&gt; A **FormGroup** aggregates the values of each child FormControl into one
&gt; object, with each control name as the key.

&lt;!-- language: lang-js --&gt;
    const form = new FormGroup({
      first: new FormControl(&#39;Nancy&#39;, Validators.minLength(2)),
      last: new FormControl(&#39;Drew&#39;)
    });

[FormArray][2]:

&gt; A **FormArray** aggregates the values of each child FormControl into an
&gt; array.

&lt;!-- language: lang-js --&gt;

    const arr = new FormArray([
      new FormControl(&#39;Nancy&#39;, Validators.minLength(2)),
      new FormControl(&#39;Drew&#39;)
    ]);

When should one be used over the other?

[1]: https://angular.io/api/forms/FormGroup
[2]: https://angular.io/api/forms/FormArray

When to use FormGroup vs. FormArray?

Why do you always import seaborn as `sns` and not with the letters of the name as `sbn`?

Is `sns` an acronym for something? 

Or is it some kind of joke?

**EDIT:**

As [cel](https://stackoverflow.com/users/2272172/cel) commented, someone put this as an issue [in github](https://github.com/mwaskom/seaborn/issues/229).   
There they do not answer the question but say that it is a joke related to the original name of the library.  
I was unsuccessful in trying to find that original name.

Seaborn - Why import as sns?

Why do you always import seaborn as <code>sns</code> and not with the letters of the name as <code>sbn</code>?
Is <code>sns</code> an acronym for something?
Or is it some kind of joke?
EDIT:
As <a href="https://stackoverflow.com/users/2272172/cel" target="_blank" rel="noopener noreferrer">cel</a> commented, someone put this as an issue <a href="https://github.com/mwaskom/seaborn/issues/229" target="_blank" rel="noopener noreferrer">in github</a>. 
There they do not answer the question but say that it is a joke related to the original name of the library. 
I was unsuccessful in trying to find that original name.

I use python 2.7, 3.5.2 and 3.6. Normally `pip3` is installed with python3.x. But ...

The code:

    where pip3

gives me:
    
    INFO: Could not find files for the given pattern(s).

How can I fix this?

How to install pip3 on Windows?

python 3.5.2

**code 1**

    import urllib
    s = urllib.parse.quote(&#39;&quot;&#39;)
    print(s) 

it gave this error: 

&gt; AttributeError: module &#39;urllib&#39; has no attribute &#39;parse&#39;

**code 2**

    from urllib.parse import quote  
    # import urllib
    # s = urllib.parse.quote(&#39;&quot;&#39;)
    s = quote(&#39;&quot;&#39;)
    print(s) 

it works...

**code3**

    from flask import Flask
    # from urllib.parse import quote  
    # s = quote(&#39;&quot;&#39;)
    import urllib
    s = urllib.parse.quote(&#39;&quot;&#39;)
    print(s) 
 it works,too. because of flask? 

Why I don&#39;t have the error anymore? is it a bug ?





AttributeError: module &#39;urllib&#39; has no attribute &#39;parse&#39;

## Problem

Is there any way in Airflow to create a workflow such that the number of tasks B.* is unknown until completion of Task A? I have looked at subdags but it looks like it can only work with a static set of tasks that have to be determined at Dag creation.

Would dag triggers work? And if so could you please provide an example.

I have an issue where it is impossible to know the number of task B&#39;s that will be needed to calculate Task C until Task A has been completed. Each Task B.* will take several hours to compute and cannot be combined.

                  |---&gt; Task B.1 --|
                  |---&gt; Task B.2 --|
     Task A ------|---&gt; Task B.3 --|-----&gt; Task C
                  |       ....     |
                  |---&gt; Task B.N --|
                   
## Idea #1

I don&#39;t like this solution because I have to create a blocking ExternalTaskSensor and all the Task B.* will take between 2-24 hours to complete. So I do not consider this a viable solution. Surely there is an easier way? Or was Airflow not designed for this?

    Dag 1
    Task A -&gt; TriggerDagRunOperator(Dag 2) -&gt; ExternalTaskSensor(Dag 2, Task Dummy B) -&gt; Task C

    Dag 2 (Dynamically created DAG though python_callable in TriggerDagrunOperator)
                   |-- Task B.1 --|
                   |-- Task B.2 --|
    Task Dummy A --|-- Task B.3 --|-----&gt; Task Dummy B
                   |     ....     |
                   |-- Task B.N --|

Edit 1:
-------

**As of now this question still does not have a great answer**. I have been contacted by several people looking for a solution. 

Proper way to create dynamic workflows in Airflow

I have a dataframe, which contains info about movies. It has a column called `genre`, which contains a list of genres it belongs to. For example:

    df[&#39;genre&#39;]
    
    ## returns 
    
    0       [&#39;comedy&#39;, &#39;sci-fi&#39;]
    1       [&#39;action&#39;, &#39;romance&#39;, &#39;comedy&#39;]
    2       [&#39;documentary&#39;]
    3       [&#39;crime&#39;,&#39;horror&#39;]
    ...

I want to know how can I query the dataframe, so it returns the movie belongs to a cerain genre?

For example, something may like `df[&#39;genre&#39;].contains(&#39;comedy&#39;)` returns 0 or 1.

I know for a list, I can do things like:

    &#39;comedy&#39; in  [&#39;comedy&#39;, &#39;sci-fi&#39;]

However, in pandas, I didn&#39;t find something similar, the only thing I know is `df[&#39;genre&#39;].str.contains()`, but it didn&#39;t work for the list type.

Python &amp; Pandas: How to query if a list-type column contains something?

How to group values of pandas dataframe and select the latest(by date) from each group? 

For example, given a dataframe sorted by date:

    	id     product   date
    0   220    6647     2014-09-01 
    1   220    6647     2014-09-03 
    2   220    6647     2014-10-16
    3   826    3380     2014-11-11
    4   826    3380     2014-12-09
    5   826    3380     2015-05-19
    6   901    4555     2014-09-01
    7   901    4555     2014-10-05
    8   901    4555     2014-11-01

grouping by id or product, and selecting the earliest gives:

    	id     product   date
    2   220    6647     2014-10-16
    5   826    3380     2015-05-19
    8   901    4555     2014-11-01

group by pandas dataframe and select latest in each group

If I have the following data and Seaborn Heatmap:
 
    import pandas as pd
    data = pd.DataFrame({&#39;x&#39;:(1,2,3,4),&#39;y&#39;:(1,2,3,4),&#39;z&#39;:(14,15,23,2)})
   
    sns.heatmap(data.pivot_table(index=&#39;y&#39;, columns=&#39;x&#39;, values=&#39;z&#39;))

How do I add a label to the colour bar?


How to add a label to Seaborn Heatmap color bar?

Seems pretty Googleable but haven&#39;t been able to find something online that works.

I&#39;ve tried both `sns.boxplot(&#39;Day&#39;, &#39;Count&#39;, data= gg).title(&#39;lalala&#39;)` and `sns.boxplot(&#39;Day&#39;, &#39;Count&#39;, data= gg).suptitle(&#39;lalala&#39;)`. None worked. I think it might be because I&#39;m also working with matplotlib.

How to add title to seaborn boxplot

For the plot

    sns.countplot(x=&quot;HostRamSize&quot;,data=df)

I got the following graph with x-axis label mixing together, how do I avoid this? Should I change the size of the graph to solve this problem?

[![enter image description here][1]][1]


  [1]: https://i.stack.imgur.com/8iYud.png

How to prevent overlapping x-axis labels in sns.countplot

I&#39;m looking to see how to do two things in Seaborn with using a bar chart to display values that are in the dataframe, but not in the graph

1) I&#39;m looking to display the values of one field in a dataframe while graphing another.  For example, below, I&#39;m graphing &#39;tip&#39;, but I would like to place the value of &#39;total_bill&#39; centered above each of the bars (i.e.325.88 above Friday, 
1778.40 above Saturday, etc.)

2) Is there a way to scale the colors of the bars, with the lowest value of &#39;total_bill&#39; having the lightest color (in this case Friday) and the highest value of &#39;total_bill&#39; having the darkest.  Obviously, I&#39;d stick with one color (i.e. blue) when I do the scaling.

Thanks! I&#39;m sure this is easy, but i&#39;m missing it..

**While I see that others think that this is a duplicate of another problem (or two), I am missing the part of how I use a value that is not in the graph as the basis for the label or the shading.  How do I say, use total_bill as the basis.  I&#39;m sorry, but I just can&#39;t figure it out based on those answers.**

Starting with the following code,

    import pandas as pd
    import seaborn as sns
    %matplotlib inline
    df=pd.read_csv(&quot;https://raw.githubusercontent.com/wesm/pydata-    book/master/ch08/tips.csv&quot;, sep=&#39;,&#39;)
    groupedvalues=df.groupby(&#39;day&#39;).sum().reset_index()
    g=sns.barplot(x=&#39;day&#39;,y=&#39;tip&#39;,data=groupedvalues)

I get the following result:

[![enter image description here][1]][1]

Interim Solution:


    for index, row in groupedvalues.iterrows():
        g.text(row.name,row.tip, round(row.total_bill,2), color=&#39;black&#39;, ha=&quot;center&quot;)

[![enter image description here][2]][2]

On the ***shading***, using the example below, I tried the following:

    import pandas as pd
    import seaborn as sns
    %matplotlib inline
    df=pd.read_csv(&quot;https://raw.githubusercontent.com/wesm/pydata-book/master/ch08/tips.csv&quot;, sep=&#39;,&#39;)
    groupedvalues=df.groupby(&#39;day&#39;).sum().reset_index()

    pal = sns.color_palette(&quot;Greens_d&quot;, len(data))
    rank = groupedvalues.argsort().argsort() 
    g=sns.barplot(x=&#39;day&#39;,y=&#39;tip&#39;,data=groupedvalues)

    for index, row in groupedvalues.iterrows():
        g.text(row.name,row.tip, round(row.total_bill,2), color=&#39;black&#39;, ha=&quot;center&quot;)
    
But that gave me the following error:

**AttributeError: &#39;DataFrame&#39; object has no attribute &#39;argsort&#39;**

So I tried a modification:

    import pandas as pd
    import seaborn as sns
    %matplotlib inline
    df=pd.read_csv(&quot;https://raw.githubusercontent.com/wesm/pydata-book/master/ch08/tips.csv&quot;, sep=&#39;,&#39;)
    groupedvalues=df.groupby(&#39;day&#39;).sum().reset_index()

    pal = sns.color_palette(&quot;Greens_d&quot;, len(data))
    rank=groupedvalues[&#39;total_bill&#39;].rank(ascending=True)
    g=sns.barplot(x=&#39;day&#39;,y=&#39;tip&#39;,data=groupedvalues,palette=np.array(pal[::-1])[rank])

and that leaves me with 

**IndexError: index 4 is out of bounds for axis 0 with size 4**
  [1]: https://i.stack.imgur.com/0GmTW.png
  [2]: https://i.stack.imgur.com/LGily.png

Seaborn Barplot - Displaying Values

I&#39;m have the following code which creates a table and a barplot via seaborn.

    #Building a dataframe grouped by the # of Engagement Types
    sales_type = sales.groupby(&#39;# of Engagement Types&#39;).sum()

    #Calculating the % of people who bought the course by # engagement types
    sales_type[&#39;% Sales per Participants&#39;] =  round(100*(sales_type[&#39;Sales&#39;] / sales_type[&#39;Had an Engagement&#39;]), 2)

    #Calculating the # of people who didn&#39;t have any engagements
    sales_type.set_value(index=0, col=&#39;Had an Engagement&#39;, value=sales[sales[&#39;Had an Engagement&#39;]==0].count()[&#39;Sales&#39;])

    #Calculating the % of sales for those who didn&#39;t have any engagements
    sales_type.set_value(index=0, col=&#39;% Sales per Participants&#39;,
                         value=round(100 * (sales_type.ix[0, &#39;Sales&#39;] / 
                                            sales[sales[&#39;Had an Engagement&#39;]==0].count()[&#39;Sales&#39;]),2))

    #Setting the graph image
    fig, (ax1) = plt.subplots(nrows=1, ncols=1, figsize=(12,4))
    sns.set_style(&quot;whitegrid&quot;)

    # Ploting the histagram for the % of total prospects
    ax1 = sns.barplot(x=sales_type.index,y=&#39;% Sales per Participants&#39;, data=sales_type ,ax=ax1)
    ax1.set(ylabel = &#39;%&#39;)
    ax1.set_title(&#39;% Sales per Participants By # of Engagement Types&#39;) 

    #present the table
    sales_type.xs([&#39;Had an Engagement&#39;, &#39;Sales&#39;,&#39;% Sales per Participants&#39;],axis=1).transpose()
    #sales_type

I&#39;m using the same code concept for other parameters I have with no issue. However, for one parameter I get an error: &quot;ValueError: Grouper for &#39;&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;&#39; not 1-dimensional&quot; for the line code:

    ax1 = sns.barplot(x=sales_type.index,y=&#39;% Sales per Participants&#39;, data=sales_type ,ax=ax1)

This error occurs although the dataframe doesn&#39;t have more than one dimension.

This is the head of the table:

                           Sales  Pre-Ordered / Ordered Book  \
    # of Engagement Types                                      
    0                        1.0                         0.0   
    1                       20.0                       496.0   
    2                       51.0                       434.0   
    3                       82.0                       248.0   
    4                       71.0                       153.0   
    5                       49.0                        97.0   
    6                        5.0                        24.0   
    
                           Opted In For / Clicked to Kindle  Viewed PLC  \
    # of Engagement Types                                                 
    0                                                   0.0           0   
    1                                               27034.0        5920   
    2                                                6953.0        6022   
    3                                                1990.0        1958   
    4                                                 714.0         746   
    5                                                 196.0         204   
    6                                                  24.0          24   
    
                           # of PLC Engagement  Viewed Webinar  \
    # of Engagement Types                                        
    0                                      0.0               0   
    1                                   6434.0            1484   
    2                                   7469.0            1521   
    3                                   2940.0            1450   
    4                                   1381.0             724   
    5                                    463.0             198   
    6                                     54.0              24   
    
                           # of Webinars (Live/Replay)  \
    # of Engagement Types                                
    0                                              0.0   
    1                                           1613.0   
    2                                           1730.0   
    3                                           1768.0   
    4                                           1018.0   
    5                                            355.0   
    6                                             45.0   
    
                           OCCC Facebook Group Member  Engaged in Cart-Open  \
    # of Engagement Types                                                     
    0                                             0.0                     0   
    1                                           148.0                   160   
    2                                           498.0                  1206   
    3                                           443.0                   967   
    4                                           356.0                   511   
    5                                           168.0                   177   
    6                                            24.0                    24   
    
                           # of Engagement at Cart Open  Had an Engagement  \
    # of Engagement Types                                                    
    0                                               0.0               3387   
    1                                             189.0              35242   
    2                                            1398.0               8317   
    3                                            1192.0               2352   
    4                                             735.0                801   
    5                                             269.0                208   
    6                                              40.0                 24   
    
                           Total # of Engagements  % Sales per Participants  
    # of Engagement Types                                                    
    0                                         0.0                      0.03  
    1                                     35914.0                      0.06  
    2                                     18482.0                      0.61  
    3                                      8581.0                      3.49  
    4                                      4357.0                      8.86  
    5                                      1548.0                     23.56  
    6                                       211.0                     20.83  

This is the full error:

    ---------------------------------------------------------------------------
    ValueError                                Traceback (most recent call last)
    &lt;ipython-input-211-f0185fe64c1a&gt; in &lt;module&gt;()
         12 sns.set_style(&quot;whitegrid&quot;)
         13 # Ploting the histagram for the % of total prospects
    ---&gt; 14 ax1 = sns.barplot(x=sales_type.index,y=&#39;% Sales per Participants&#39;, data=sales_type ,ax=ax1)
         15 ax1.set(ylabel = &#39;%&#39;)
         16 ax1.set_title(&#39;% Sales per Participants By # of Engagement Types&#39;)

    ValueError: Grouper for &#39;&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;&#39; not 1-dimensional

I&#39;ve tried to search the internet and Stack Overflow for this error, but got no results. Does anyone has an idea what&#39;s going on?


  [1]: https://i.stack.imgur.com/D62iN.png


Content Type	Original Author	Original Content on Stackoverflow
Question	Lucas	View Question on Stackoverflow
Solution 1 - Python	boardrider	View Answer on Stackoverflow

Seaborn - Why import as sns?

Python Problem Overview

Python Solutions

Solution 1 - Python

When to use FormGroup vs. FormArray?

tqdm printing to newline

Attributions