Surely you don&#39;t mean install _all_ available packages, right? Continuum&#39;s default channel alone has 635 of them, and there are countless others on other channels. 

I think @cel is right above to assume that you&#39;re specifically asking to install all of the packages that Continuum includes in its default Anaconda installer. If that&#39;s the case, then the simplest command is this:

    conda create -n env_full anaconda

This will install the latest version of the `anaconda` package set, as compiled for your default version of Python (the one you used to install Anaconda originally). If you&#39;d like to create an environment with a different version of Python, then just add that to the command line; e.g.

    conda create -n env_full anaconda python=2.7
    conda create -n env_full anaconda python=3.5


Anaconda ships with a root env, this is named as base. You can use this as it is  or clone a new environment from it.

if you just want a environment with all the packages for day to day then you can use the base enviornment itself.

you can list the all available conda env on your machine as follows

     conda info --env

you will see a enviornment name base, activate it to use it

     source activate base

You can verify all the packages available in the env with following command ( This work with any env created with conda)

     conda list -n base

As I said above if you want a different env then you can clone base using following command

    conda create --name &lt;env_name&gt; --clone base

wenn i use this command:
&gt; conda create -n env_full anaconda&gt;

I got the PackageNotFoundError. So i create the simple environemnt:
&gt; conda create -n env_full &gt;

and use the command to install all the anaconda default packages:
&gt; conda install anaconda


With the new version of Visual Studio Code, tabs are rendered by default. How do I disable / hide them as I really liked the previous behavior without any tabs?


How do I disable tabs in Visual Studio Code?

How to do the similar conditional one-line check in Elixir?

```lang-elixir
if (x &gt; 0) ? x : nil
```

Is this the only equivalent in elixir world?

```lang-elixir
if true, do: 1, else: 2
```

Simulate ternary operator in Elixir

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 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:
<pre><code class="hljs language-ini">conda create -n env_full python=3
</code></pre>
However, only handful of packages would be installed. Please see the screen shot.<a href="http://i.stack.imgur.com/XMOrV.png" target="_blank" rel="noopener noreferrer"><img src="http://i.stack.imgur.com/XMOrV.png" alt="enter image description here"></a>
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.

My dataframe has a `DOB` column (example format **`1/1/2016`**) which by default gets converted to Pandas dtype &#39;object&#39;.

Converting this to date format with `df[&#39;DOB&#39;] = pd.to_datetime(df[&#39;DOB&#39;])`, the date gets converted to: **`2016-01-26`** and its `dtype` is: `datetime64[ns]`.

Now I want to convert this date format to **`01/26/2016` or any other general date format**. How do I do it?

(Whatever the method I try, it always shows the date in `2016-01-26` format.)

How to change the datetime format in Pandas

I currently have this code. It works perfectly.

It loops through excel files in a folder,
removes the first 2 rows, then saves them as individual excel files,
and it also saves the files in the loop as an appended file.

Currently the appended file **overwrites** the existing file each time I run the code.

I need to append the new data to the bottom of the **already existing excel sheet** (&#39;master_data.xlsx)


    dfList = []
    path = &#39;C:\\Test\\TestRawFile&#39; 
    newpath = &#39;C:\\Path\\To\\New\\Folder&#39;
    
    for fn in os.listdir(path): 
      # Absolute file path
      file = os.path.join(path, fn)
      if os.path.isfile(file): 
        # Import the excel file and call it xlsx_file 
        xlsx_file = pd.ExcelFile(file) 
        # View the excel files sheet names 
        xlsx_file.sheet_names 
        # Load the xlsx files Data sheet as a dataframe 
        df = xlsx_file.parse(&#39;Sheet1&#39;,header= None) 
        df_NoHeader = df[2:] 
        data = df_NoHeader 
        # Save individual dataframe
        data.to_excel(os.path.join(newpath, fn))
    
        dfList.append(data) 
    
    appended_data = pd.concat(dfList)
    appended_data.to_excel(os.path.join(newpath, &#39;master_data.xlsx&#39;))


I thought this would be a simple task, but I guess not.
I think I need to bring in the master_data.xlsx file as a dataframe, then match the index up with the new appended data, and save it back out. Or maybe there is an easier way. Any Help is appreciated.


Append existing excel sheet with new dataframe using python pandas

The problem is that my train data could not be placed into RAM due to train data size. So I need a method which first builds one tree on whole train data set, calculate residuals build another tree and so on (like gradient boosted tree do). Obviously if I call `model = xgb.train(param, batch_dtrain, 2)` in some loop - it will not help, because in such case it just rebuilds whole model for each batch.

How can I implement incremental training for xgboost?

I have a date pyspark dataframe with a string column in the format of ```MM-dd-yyyy``` and I am attempting to convert this into a date column.  

I tried: 

```
df.select(to_date(df.STRING_COLUMN).alias(&#39;new_date&#39;)).show()
```

And I get a string of nulls. Can anyone help?

Convert pyspark string to date format

I am attempting to recreate the following plot from the book Introduction to Statistical learning using seaborn [![enter image description here][1]][1]

I specifically want to recreate this using seaborn&#39;s `lmplot` to create the first two plots and `boxplot` to create the second. The main problem is that lmplot creates a `facetgrid` according [to this answer][2] which forces me to hackily add another matplotlib axes for the boxplot. I was wondering if there was an easier way to achieve this. Below, I have to do quite a bit of manual manipulation to get the desired plot.

    seaborn_grid = sns.lmplot(&#39;value&#39;, &#39;wage&#39;, col=&#39;variable&#39;, hue=&#39;education&#39;, data=df_melt, sharex=False)
    seaborn_grid.fig.set_figwidth(8)
    
    left, bottom, width, height = seaborn_grid.fig.axes[0]._position.bounds
    left2, bottom2, width2, height2 = seaborn_grid.fig.axes[1]._position.bounds
    left_diff = left2 - left
    seaborn_grid.fig.add_axes((left2 + left_diff, bottom, width, height))
    
    sns.boxplot(&#39;education&#39;, &#39;wage&#39;, data=df_wage, ax = seaborn_grid.fig.axes[2])
    ax2 = seaborn_grid.fig.axes[2]
    ax2.set_yticklabels([])
    ax2.set_xticklabels(ax2.get_xmajorticklabels(), rotation=30)
    ax2.set_ylabel(&#39;&#39;)
    ax2.set_xlabel(&#39;&#39;);
    
    leg = seaborn_grid.fig.legends[0]
    leg.set_bbox_to_anchor([0, .1, 1.5,1])

Which yields[![enter image description here][3]][3]


Sample data for DataFrames: 

    df_melt = {&#39;education&#39;: {0: &#39;1. &lt; HS Grad&#39;,
      1: &#39;4. College Grad&#39;,
      2: &#39;3. Some College&#39;,
      3: &#39;4. College Grad&#39;,
      4: &#39;2. HS Grad&#39;},
     &#39;value&#39;: {0: 18, 1: 24, 2: 45, 3: 43, 4: 50},
     &#39;variable&#39;: {0: &#39;age&#39;, 1: &#39;age&#39;, 2: &#39;age&#39;, 3: &#39;age&#39;, 4: &#39;age&#39;},
     &#39;wage&#39;: {0: 75.043154017351497,
      1: 70.476019646944508,
      2: 130.982177377461,
      3: 154.68529299562999,
      4: 75.043154017351497}}

    df_wage={&#39;education&#39;: {0: &#39;1. &lt; HS Grad&#39;,
      1: &#39;4. College Grad&#39;,
      2: &#39;3. Some College&#39;,
      3: &#39;4. College Grad&#39;,
      4: &#39;2. HS Grad&#39;},
     &#39;wage&#39;: {0: 75.043154017351497,
      1: 70.476019646944508,
      2: 130.982177377461,
      3: 154.68529299562999,
      4: 75.043154017351497}}


  [1]: http://i.stack.imgur.com/FegIV.png
  [2]: https://stackoverflow.com/questions/23969619/plotting-with-seaborn-using-the-matplotlib-object-oriented-interface
  [3]: http://i.stack.imgur.com/tY2iI.png

Plotting multiple different plots in one figure using Seaborn

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

Conda uninstall one package and one package only

I tried the `conda search --outdated`, there are lots of outdated packages, for example the scipy is 0.17.1 but the latest is 0.18.0. However, when I do the `conda update --all`. It will not update any packages.

**update 1**

    conda update --all --alt-hint

    Fetching package metadata .......
    Solving package specifications: ..........
    
    # All requested packages already installed.
    # packages in environment at /home/user/opt/anaconda2:
    #

**update 2**

I can update those packages separately. I can do `conda update scipy`. But why I cannot update all of them in one go?
 

Content Type	Original Author	Original Content on Stackoverflow
Question	Neeraj Hanumante	View Question on Stackoverflow
Solution 1 - Python	Michael Grant	View Answer on Stackoverflow
Solution 2 - Python	DevC	View Answer on Stackoverflow
Solution 3 - Python	xiaoxin	View Answer on Stackoverflow

create anaconda python environment with all packages

Python Problem Overview

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Simulate ternary operator in Elixir

How do I disable tabs in Visual Studio Code?

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