Anaconda command prompt is just like command prompt, but it makes sure that you are able to use anaconda and conda commands from the prompt, without having to change directories or your path. 

When you start Anaconda command prompt, you&#39;ll notice that it adds/(&quot;prepends&quot;) a bunch of locations to your PATH. These locations contain commands and scripts that you can run. So as long as you&#39;re in the Anaconda command prompt, you know you can use these commands.

During the installation of Anaconda there is a choice to add these to the PATH by default, and if checked you can also use these commands on the regular command prompt. But the anaconda prompt will always work. 

As far as updating conda, if it doesn&#39;t work in command prompt, you can do 

    conda update conda

in Anaconda command prompt. 

When you use anaconda command prompt it opened at conda directory (path where all the conda commands run) 

like when I was installing pip3 install prettytable on command prompt it successfully installed but not replicate in jupyter notebook.
But when install it using anaconda prompt it replicates intantly

Here is the difference:

`PATH-TO` behind is the path to `Anaconda3`

Afer adding the following `env` to `Windows command prompt`, it will be the same as `Anaconda prompt`:
```
set CONDA_DEFAULT_ENV=base
set CONDA_PREFIX=PATH-TO\Anaconda3
set CONDA_EXE=%CONDA_PREFIX%\Scripts\conda.exe
set CONDA_PROMPT_MODIFIER=(base) 
set CONDA_PYTHON_EXE=%CONDA_PREFIX%\python.exe
set CONDA_SHLVL=1
set Path=%CONDA_PREFIX%;%CONDA_PREFIX%\Library\mingw-w64\bin;%CONDA_PREFIX%\Library\usr\bin;%CONDA_PREFIX%\Library\bin;%CONDA_PREFIX%\Scripts;%CONDA_PREFIX%\bin;%CONDA_PREFIX%\condabin;%Path%
```


I&#39;m currently developing an iOS application for a client. The submission review process to the store can often be a lengthy process and is relatively new to me. 

My client wants to do a beta test using **TestFlight** as well as submitting the app to the app store afterwards, through **XCode** and **Itunes Connect**.


Scouring Apple&#39;s documentation I can&#39;t seem to get a good idea of following:


- **If I want to update an existing application on the store do I have to go through the review process again in full?**&lt;br&gt;&lt;br&gt;

- **If I have my app approved for beta testing release through TestFlight, is this taken into consideration when submitting the app for review to the store?**&lt;br&gt;&lt;br&gt;

- **If I want to test a new build through TestFlight, do I need to go through the beta review process again in full?**&lt;br&gt;&lt;br&gt;

- **If an app is approved on the app store, does it automatically pass the beta review?**&lt;br&gt; 
(This sounds counterintuitive considering you don&#39;t want to do a beta test after releasing to the store but in a scenario where you may want to do a closed release of an update for testing while a live version is up on the store)


iOS app submission and beta review process

&gt; The information below may be superfluous if you are trying to understand the error message. Please start off by reading [the answer](https://stackoverflow.com/a/37968229/6292000)
 by **@user707650**.

Using MatPlotLib, I wanted a generalizable script that creates the following from my data. 

A window containing ***a*** subplots arranged so that there are ***b*** subplots per column. I want to be able to change the values of ***a*** and ***b***. 

If I have data for ***2a*** subplots, I want 2 windows, each with the previously described &quot;***a*** subplots arranged according to ***b*** subplots per column&quot;.

The x and y data I am plotting are floats stored in np.arrays and are structured as follows:

 - The x data is always the same for all plots and is of length 5.

         &#39;x_vector&#39;: [0.000, 0.005, 0.010, 0.020, 0.030, 0.040]

 - The y data of all plots are stored in **y_vector** where the data for the first plot is stored at indexes 0 through 5. The data for the second plot is stored at indexes 6 through 11. The third plot gets 12-18, the fourth 19-24, and so on.

In total, for this dataset, I have 91 plots (i.e. 91*6 = 546 values stored in y_vector). 

**Attempt:**

    import matplotlib.pyplot as plt
    
    # Options:
    plots_tot = 14 # Total number of plots. In reality there is going to be 7*13 = 91 plots.
    location_of_ydata = 6 # The values for the n:th plot can be found in the y_vector at index &#39;n*6&#39; through &#39;n*6 + 6&#39;.
    plots_window = 7 # Total number of plots per window.
    rows = 2 # Number of rows, i.e. number of subplots per column.
    
    # Calculating number of columns:
    prim_cols = plots_window / rows
    extra_cols = 0
    if plots_window % rows &gt; 0:
    	extra_cols = 1
    cols = prim_cols + extra_cols
    
    print &#39;cols:&#39;, cols
    print &#39;rows:&#39;, rows
    
    # Plotting:
    n=0
    x=0
    fig, ax = plt.subplots(rows, cols)
    while x &lt;= plots_tot:
    	ax[x].plot(x_vector, y_vector[n:(n+location_of_ydata)], &#39;ro&#39;)
    	if x % plots_window == plots_window - 1:
    		plt.show() # New window for every 7 plots.
    	n = n+location_of_ydata
    	x = x+1

**I get the following error:**

    cols: 4
    rows: 2
    Traceback (most recent call last):
      File &quot;Script.py&quot;, line 222, in &lt;module&gt;
        ax[x].plot(x_vector, y_vector[n:(n+location_of_ydata)], &#39;ro&#39;)
    AttributeError: &#39;numpy.ndarray&#39; object has no attribute &#39;plot&#39;

Axes from plt.subplots() is a &quot;numpy.ndarray&quot; object and has no attribute &quot;plot&quot;

I installed anaconda into my computer using python. After I install the software, I found there is one program called anaconda prompt.

What is the difference between anaconda prompt and command prompt? If I want to update the package, which one I should use or either one. Like (conda update conda)

Thank you

difference between command prompt and anaconda prompt

I installed anaconda into my computer using python. After I install the software, I found there is one program called anaconda prompt.
What is the difference between anaconda prompt and command prompt? If I want to update the package, which one I should use or either one. Like (conda update conda)
Thank you

Given the following data frame:

    import pandas as pd
    import numpy as np
    df=pd.DataFrame({&#39;A&#39;:[&#39;A&#39;,&#39;A&#39;,&#39;A&#39;,&#39;B&#39;,&#39;B&#39;,&#39;B&#39;],
                    &#39;B&#39;:[&#39;a&#39;,&#39;a&#39;,&#39;b&#39;,&#39;a&#39;,&#39;a&#39;,&#39;a&#39;],
                    })
    df

     	A 	B
    0 	A 	a 
    1 	A 	a 
    2 	A 	b 
    3 	B 	a 
    4 	B 	a 
    5 	B 	a

I&#39;d like to create column &#39;C&#39;, which numbers the rows within each group in columns A and B like this:

     	A 	B   C
    0 	A 	a 	1
    1 	A 	a 	2
    2 	A 	b 	1
    3 	B 	a   1
    4 	B 	a   2
    5 	B 	a   3

I&#39;ve tried this so far:

    df[&#39;C&#39;]=df.groupby([&#39;A&#39;,&#39;B&#39;])[&#39;B&#39;].transform(&#39;rank&#39;)

...but it doesn&#39;t work!

Pandas number rows within group in increasing order

I have installed tensorflow in my ubuntu 16.04 using the second answer [here][1] with ubuntu&#39;s builtin apt cuda installation.

Now my question is how can I test if tensorflow is really using gpu? I have a gtx 960m gpu. When I `import tensorflow` this is the output

    I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally
    I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally
    I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally
    I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally
    I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally

Is this output enough to check if tensorflow is using gpu ? 
  [1]: https://devtalk.nvidia.com/default/topic/936429/-solved-tensorflow-with-gpu-in-anaconda-env-ubuntu-16-04-cuda-7-5-cudnn-/

How to tell if tensorflow is using gpu acceleration from inside python shell?

Is there any function in numpy to group this array down below by the first column?

I couldn&#39;t find any good answer over the internet..

    &gt;&gt;&gt; a
    array([[  1, 275],
           [  1, 441],
           [  1, 494],
           [  1, 593],
           [  2, 679],
           [  2, 533],
           [  2, 686],
           [  3, 559],
           [  3, 219],
           [  3, 455],
           [  4, 605],
           [  4, 468],
           [  4, 692],
           [  4, 613]])

Wanted output:

    array([[[275, 441, 494, 593]],
           [[679, 533, 686]],
           [[559, 219, 455]],
           [[605, 468, 692, 613]]], dtype=object)


Is there any numpy group by function?

I&#39;m using `linear_model.LinearRegression` from scikit-learn as a predictive model. It works and it&#39;s perfect. I have a problem to evaluate the predicted results using the `accuracy_score` metric.

This is my true Data :

    array([1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0])

**My predicted Data:**

    array([ 0.07094605,  0.1994941 ,  0.19270157,  0.13379635,  0.04654469,
        0.09212494,  0.19952108,  0.12884365,  0.15685076, -0.01274453,
        0.32167554,  0.32167554, -0.10023553,  0.09819648, -0.06755516,
        0.25390082,  0.17248324])

**My code:**

    accuracy_score(y_true, y_pred, normalize=False)

**Error message:** 

    ValueError: Can&#39;t handle mix of binary and continuous target



Accuracy Score ValueError: Can&#39;t Handle mix of binary and continuous target

When you use ***[BeautifulSoup][1]*** to scrape a certain part of a website, you can use 

 - `soup.find()` and `soup.findAll()` or
 - `soup.select()`.

Is there a difference between the `.find()` and the `.select()` methods?
(e.g. In performance or flexibility, etc.) Or are they the same?


  [1]: https://www.crummy.com/software/BeautifulSoup/bs4/doc/

Beautifulsoup : Difference between .find() and .select()

How can I remove the current process/application which is already assigned to a port?

For example: `localhost:8080`



How do I kill the process currently using a port on localhost in Windows?

I want to create an anaconda python environment with **all** of the packages that Continuum includes in its default Anaconda installer. Based on some internet search I used the following command:

    conda create -n env_full python=3

However, only handful of packages would be installed. Please see the screen shot.[![enter image description here][1]][1]


  [1]: http://i.stack.imgur.com/XMOrV.png

Kindly guide me to use correct commands.

Right now I am trying to do this on a desktop computer, but I would like to apply the same principles to the cluster facility.

create anaconda python environment with all packages

I am a ruby programmer trying to learn python. I am pretty familiar with pyenv since it is like a copy and paste from rbenv. Pyenv helps allow to have more than one version of python in a system and also to isolate the python without touching sensitive parts of system.

I suppose every python installation comes with pip package. What I still don&#39;t understand is, there are many good python libs out there that suggest to use this virtualenv and anaconda. I can even find a virtualenv plugin for pyenv. 

Now I am getting confused with the purpose of these two pyenv and virtualenv.
worse inside pyenv there is a virtualenv plugin.

My questions are:

 - what is the difference between pyenv and virtualenv?
 - Is there any difference in using  pip command inside both pyenv and virtualenv?
 - what does this pyenv virutalenv do?

Your explanation with example will be highly appreciated.



What is the difference between pyenv, virtualenv, anaconda?

When I run `!pip install geocoder` in Jupyter Notebook I get the same output as running `pip install geocoder` in the terminal but the geocoder package is not available when I try to import it.

I&#39;m using Ubuntu 14.04, Anaconda 4.0.0 and pip 8.1.2

**Installing geocoder:**

    !pip install geocoder

    The directory &#39;/home/ubuntu/.cache/pip/http&#39; or its parent directory is not owned by the current user and the cache has been disabled. Please check the permissions and owner of that directory. If executing pip with sudo, you may want sudo&#39;s -H flag.
    The directory &#39;/home/ubuntu/.cache/pip&#39; or its parent directory is not owned by the current user and caching wheels has been disabled. check the permissions and owner of that directory. If executing pip with sudo, you may want sudo&#39;s -H flag.
    Collecting geocoder
      Downloading geocoder-1.15.1-py2.py3-none-any.whl (195kB)
        100% |████████████████████████████████| 204kB 3.2MB/s 
    Requirement already satisfied (use --upgrade to upgrade): requests in /usr/local/lib/python2.7/dist-packages (from geocoder)
    Requirement already satisfied (use --upgrade to upgrade): ratelim in /usr/local/lib/python2.7/dist-packages (from geocoder)
    Requirement already satisfied (use --upgrade to upgrade): six in /usr/local/lib/python2.7/dist-packages (from geocoder)
    Requirement already satisfied (use --upgrade to upgrade): click in /usr/local/lib/python2.7/dist-packages (from geocoder)
    Requirement already satisfied (use --upgrade to upgrade): decorator in /usr/local/lib/python2.7/dist-packages/decorator-4.0.10-py2.7.egg (from ratelim-&gt;geocoder)
    Installing collected packages: geocoder
    Successfully installed geocoder-1.15.1

**Then try to import it:**

    import geocoder

    ---------------------------------------------------------------------------
    ImportError                               Traceback (most recent call last)
    &lt;ipython-input-4-603a981d39f2&gt; in &lt;module&gt;()
    ----&gt; 1 import geocoder
    
    ImportError: No module named geocoder

I also tried shutting down the notebook and restarting it without any luck.

**Edit:** I found that using the terminal installs the geocoder package in `/home/ubuntu/.local/lib/python2.7/site-packages` and using a notebook installs it in `/usr/local/lib/python2.7/dist-packages` which is not in the path. `sys.path.append(&#39;/usr/local/lib/python2.7/dist-packages&#39;)` solves the problem for the current session.

So how can I permanently modify the path or tell pip where to install geocoder?

Installing a pip package from within a Jupyter Notebook not working

I want to install the &#39;rope&#39; package in my current active environment using conda. Currently, the following &#39;rope&#39; versions are available:

    (data_downloader)user@user-ThinkPad ~/code/data_downloader $ conda search rope
    Using Anaconda Cloud api site https://api.anaconda.org
    Fetching package metadata: ....
    cached-property              1.2.0                    py27_0  defaults        
                                 1.2.0                    py34_0  defaults        
                                 1.2.0                    py35_0  defaults        
                                 1.3.0                    py27_0  defaults        
                                 1.3.0                    py34_0  defaults        
                                 1.3.0                    py35_0  defaults        
    rope                         0.9.4                    py26_0  defaults        
                                 0.9.4                    py27_0  defaults        
                                 0.9.4                    py33_0  defaults        
                                 0.9.4                    py34_0  defaults        
                                 0.9.4                    py26_1  defaults        
                                 0.9.4                    py27_1  defaults        
                                 0.9.4                    py33_1  defaults        
                                 0.9.4                    py34_1  defaults        
                              .  0.9.4                    py35_1  defaults        


I would like to install the following one:

                             1.3.0                    py35_0  defaults        

I&#39;ve tried all sorts of permutations of &#39;conda install&#39; which I&#39;m not going to list here because none of them are correct.

I am also not sure what the *py35_0* is (I&#39;m assuming this is the version of the python against which the package was built?) and I also don&#39;t know what &#39;defaults&#39; means?

anaconda/conda - install a specific package version

When I try to uninstall `pandas` from my `conda` virtual env, I see that it tries to uninstall more packages as well:


    $ conda uninstall pandas
    Using Anaconda Cloud api site https://api.anaconda.org
    Fetching package metadata: ....
    Solving package specifications: .........
    
    Package plan for package removal in environment /Users/amelio/anaconda/envs/py35:
    
    The following packages will be downloaded:
    
        package                    |            build
        ---------------------------|-----------------
        dask-0.7.6                 |           py35_0         276 KB
    
    The following packages will be REMOVED:
    
        blaze:       0.10.1-py35_0
        odo:         0.5.0-py35_1
        pandas:      0.18.1-np111py35_0
        seaborn:     0.7.0-py35_0
        statsmodels: 0.6.1-np111py35_1
    
    The following packages will be DOWNGRADED:
    
        dask:        0.10.1-py35_0      --&gt; 0.7.6-py35_0
    
    Proceed ([y]/n)?

I would like to uninstall `pandas` **only** and not have anything else downgraded. 

I understand that there these packages have **dependencies** to `pandas` and even to **specific versions** of pandas, but is this even possible at all with `conda`?

## Partial motivation

My understanding is that it [isn&#39;t that easy][1] to install a package from GitHub using `conda`. At least it isn&#39;t as easy as using a one-liner as one can do with `pip`. 

Since I want to use the version in `master`, my plan is to uninstall the `conda` version and use `pip` to install `pandas` from master on the official repo GitHub.

How can I do this?

  [1]: https://stackoverflow.com/questions/19042389/conda-installing-upgrading-directly-from-github

Content Type	Original Author	Original Content on Stackoverflow
Question	Michael Li	View Question on Stackoverflow
Solution 1 - Python	Dylan Orzel	View Answer on Stackoverflow
Solution 2 - Python	Himanshu kumar Singh	View Answer on Stackoverflow
Solution 3 - Python	caot	View Answer on Stackoverflow

difference between command prompt and anaconda prompt

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

Solution 3 - Python

Axes from plt.subplots() is a "numpy.ndarray" object and has no attribute "plot"

iOS app submission and beta review process

Attributions