You can scale up the fonts in your call to `sns.set()`.

    import numpy as np
    import matplotlib.pyplot as plt
    import seaborn as sns
    x = np.random.normal(size=37)
    y = np.random.lognormal(size=37)

    # defaults
    sns.set()
    fig, ax = plt.subplots()
    ax.plot(x, y, marker=&#39;s&#39;, linestyle=&#39;none&#39;, label=&#39;small&#39;)
    ax.legend(loc=&#39;upper left&#39;, bbox_to_anchor=(0, 1.1))

![enter image description here][1]

    sns.set(font_scale=5)  # crazy big
    fig, ax = plt.subplots()
    ax.plot(x, y, marker=&#39;s&#39;, linestyle=&#39;none&#39;, label=&#39;big&#39;)
    ax.legend(loc=&#39;upper left&#39;, bbox_to_anchor=(0, 1.3))

![enter image description here][2]


  [1]: http://i.stack.imgur.com/CoDsp.png
  [2]: http://i.stack.imgur.com/IbDLE.png

The `FacetGrid` plot does produce pretty small labels. While @paul-h has described the use of `sns.set` as a way to the change the font scaling, it may not be the optimal solution since it will change the `font_scale` setting for all plots.

You could use the [`seaborn.plotting_context`][1] to change the settings for just the current plot:

    with sns.plotting_context(font_scale=1.5):
        sns.factorplot(x, y ...)


  [1]: http://stanford.edu/~mwaskom/software/seaborn/generated/seaborn.plotting_context.html

I&#39;ve made small modifications to @paul-H code, such that you can set the font size for the x/y axes and legend independently. Hope it helps:

    import numpy as np
    import matplotlib.pyplot as plt
    import seaborn as sns
    x = np.random.normal(size=37)
    y = np.random.lognormal(size=37)

    # defaults                                                                                                         
    sns.set()
    fig, ax = plt.subplots()
    ax.plot(x, y, marker=&#39;s&#39;, linestyle=&#39;none&#39;, label=&#39;small&#39;)
    ax.legend(loc=&#39;upper left&#39;, fontsize=20,bbox_to_anchor=(0, 1.1))
    ax.set_xlabel(&#39;X_axi&#39;,fontsize=20);
    ax.set_ylabel(&#39;Y_axis&#39;,fontsize=20);

    plt.show()

This is the output:

[![enter image description here][1]][1]


  [1]: https://i.stack.imgur.com/nTcas.png

For the legend, you can use this 

    plt.setp(g._legend.get_title(), fontsize=20)

Where g is your facetgrid object returned after you call the function making it. 




I&#39;m using **Asp.Net-Identity-2** and I&#39;m trying to verify email verification code using the below method. But I am getting an **&quot;Invalid Token&quot;** error message. 

 - My Application&#39;s User Manager is like this:
    
        public class AppUserManager : UserManager&lt;AppUser&gt;
        {
            public AppUserManager(IUserStore&lt;AppUser&gt; store) : base(store) { }

            public static AppUserManager Create(IdentityFactoryOptions&lt;AppUserManager&gt; options, IOwinContext context)
            {
                AppIdentityDbContext db = context.Get&lt;AppIdentityDbContext&gt;();
                AppUserManager manager = new AppUserManager(new UserStore&lt;AppUser&gt;(db));

                manager.PasswordValidator = new PasswordValidator { 
                    RequiredLength = 6,
                    RequireNonLetterOrDigit = false,
                    RequireDigit = false,
                    RequireLowercase = true,
                    RequireUppercase = true
                };

                manager.UserValidator = new UserValidator&lt;AppUser&gt;(manager)
                {
                    AllowOnlyAlphanumericUserNames = true,
                    RequireUniqueEmail = true
                };

                var dataProtectionProvider = options.DataProtectionProvider;

                //token life span is 3 hours
                if (dataProtectionProvider != null)
                {
                    manager.UserTokenProvider =
                       new DataProtectorTokenProvider&lt;AppUser&gt;
                          (dataProtectionProvider.Create(&quot;ConfirmationToken&quot;))
                       {
                           TokenLifespan = TimeSpan.FromHours(3)
                       };
                }

                manager.EmailService = new EmailService();

                return manager;
            } //Create
          } //class
        } //namespace


 - My Action to generate the token is (and even if I check the token here, I get &quot;Invalid token&quot; message):

        [AllowAnonymous]
        [HttpPost]
        [ValidateAntiForgeryToken]
        public ActionResult ForgotPassword(string email)
        {
            if (ModelState.IsValid)
            {
                AppUser user = UserManager.FindByEmail(email);
                if (user == null || !(UserManager.IsEmailConfirmed(user.Id)))
                {
                    // Returning without warning anything wrong...
                    return View(&quot;../Home/Index&quot;);

                } //if

                string code = UserManager.GeneratePasswordResetToken(user.Id);
                string callbackUrl = Url.Action(&quot;ResetPassword&quot;, &quot;Admin&quot;, new { Id = user.Id, code = HttpUtility.UrlEncode(code) }, protocol: Request.Url.Scheme);

                UserManager.SendEmail(user.Id, &quot;Reset password Link&quot;, &quot;Use the following  link to reset your password: &lt;a href=\&quot;&quot; + callbackUrl + &quot;\&quot;&gt;link&lt;/a&gt;&quot;);

                //This 2 lines I use tho debugger propose. The result is: &quot;Invalid token&quot; (???)
                IdentityResult result;
                result = UserManager.ConfirmEmail(user.Id, code);
            }

            // If we got this far, something failed, redisplay form
            return View();
            
        } //ForgotPassword

 - My Action to check the token is (here, I always get &quot;Invalid Token&quot; when I check the result):

        [AllowAnonymous]
        public async Task&lt;ActionResult&gt; ResetPassword(string id, string code)
        {

            if (id == null || code == null)
            {
                return View(&quot;Error&quot;, new string[] { &quot;Invalid params to reset password.&quot; });
            }
            
            IdentityResult result;
            
            try
            {
                result = await UserManager.ConfirmEmailAsync(id, code);
            }
            catch (InvalidOperationException ioe)
            {
                // ConfirmEmailAsync throws when the id is not found.
                return View(&quot;Error&quot;, new string[] { &quot;Error to reset password:&lt;br/&gt;&lt;br/&gt;&lt;li&gt;&quot; + ioe.Message + &quot;&lt;/li&gt;&quot; });
            }

            if (result.Succeeded)
            {
                AppUser objUser = await UserManager.FindByIdAsync(id);
                ResetPasswordModel model = new ResetPasswordModel();
                
                model.Id = objUser.Id;
                model.Name = objUser.UserName;
                model.Email = objUser.Email;

                return View(model);
            }

            // If we got this far, something failed.
            string strErrorMsg = &quot;&quot;;
            foreach(string strError in result.Errors)
            {
                strErrorMsg += &quot;&lt;li&gt;&quot; + strError + &quot;&lt;/li&gt;&quot;;
            } //foreach

            return View(&quot;Error&quot;, new string[] { strErrorMsg });

        } //ForgotPasswordConfirmation


I don&#39;t know what could be missing or what&#39;s wrong...

Asp.NET Identity 2 giving &quot;Invalid Token&quot; error

I&#39;ve stumbled over &quot;*https://stackoverflow.com/questions/1268504/why-is-the-template-argument-deduction-not-working-here*&quot; recently and the answers can be summed up to &quot;It&#39;s a nondeduced context&quot;. 

Specifically, the first one says it&#39;s such a thing and then redirects to the standard for &quot;details&quot;, while the second one quotes the standard, which is cryptic to say the least.

Can someone please explain to mere mortals, like myself, what a *nondeduced context* is, when does it occur, and why does it occur?

What is a nondeduced context?

I have plotted my data with `factorplot` in `seaborn` and get `facetgrid` object, but still cannot understand how the following attributes could be set in such a plot:

 1. Legend size: when I plot lots of variables, I get very small legends, with small fonts.
 2. Font sizes of y and x labels (a similar problem as above)

How can I change the font size using seaborn FacetGrid?

<p>I have plotted my data with <code>factorplot</code> in <code>seaborn</code> and get <code>facetgrid</code> object, but still cannot understand how the following attributes could be set in such a plot:</p>
<ol>
<li>Legend size: when I plot lots of variables, I get very small legends, with small fonts.</li>
<li>Font sizes of y and x labels (a similar problem as above)</li>
</ol>


Why can&#39;t I iterate twice over the same [iterator](https://docs.python.org/3/glossary.html#term-iterator)?

    # data is an iterator.
    
    for row in data:
        print(&quot;doing this one time&quot;)
    
    for row in data:
        print(&quot;doing this two times&quot;)

This prints `&quot;doing this one time&quot;` a few times, since `data` is non-empty. However, it does *not* print `&quot;doing this two times&quot;`. Why does iterating over `data` work the first time, but not the second time?

Why can&#39;t I iterate twice over the same data?

Python has a confusing history of tools that can be used to package and describe projects: these include `distutils` in the Standard Library, `distribute`, `distutils2`, and `setuptools` (and maybe more). It appears that `distribute` and `distutils2` were discontinued in favor of `setuptools`, which leaves two competing standards.

To my understanding `setuptools` offers far more options (e.g. declaring dependencies, tests, etc.) than `distutils`, however it is not included in the Python standard library (yet?).

The *Python Packaging User Guide*[[1]] recommends now:

&gt; Use `setuptools` to define projects and create Source Distributions.

And explains:

&gt; Although you can use pure `distutils` for many projects, it does not support defining dependencies      on other projects and is missing several convenience utilities for automatically populating package  metadata correctly that are provided by `setuptools`. Being outside the standard library, setuptools  also offers a more consistent feature set across different versions of Python, and (unlike `distutils`), `setuptools` will be updated to produce the upcoming “Metadata 2.0” standard formats on all supported versions.
&gt;
&gt;Even for projects that do choose to use `distutils`, when pip installs such projects directly from source (rather than installing from a prebuilt wheel file), it will actually build your project using `setuptools` instead.

However, looking into various project&#39;s *setup.py* files reveals that this does not seem to be an actual standard. Many packages still use `distutils` and those that support `setuptools` often mix `setuptools` with `distutils` e.g. by doing a fallback import:

    try:
        from setuptools import setup
    except ImportError:
        from distutils.core import setup

Followed by an attempt to find a way to write a setup that can be installed by both `setuptools` and `distutils`. This often includes various ways of error-prone dependency checking, since `distutils` does not support dependencies in the setup function.

Why are people still making the extra effort to support `distutils` - is the fact that `setuptools` is not in the standard library the only reason? What are the advantages of `distutils` and are there any drawbacks of writing *setup.py* files that only support `setuptools`. 

[1]:https://packaging.python.org/guides/tool-recommendations/

setuptools vs. distutils: why is distutils still a thing?

I installed `Pillow`, and after I want to do:

    from PIL import Image

I get the following error:

    Traceback (most recent call last):
      File &quot;&lt;console&gt;&quot;, line 1, in &lt;module&gt;
      File &quot;/usr/local/lib/python2.7/dist-packages/PIL/Image.py&quot;, line 61, in &lt;module&gt;
    ImportError: cannot import name _imaging

However, if I import these separately, everything is fine, ie:

    import _imaging
    import Image

Do you know what the problem might be?


ImportError: cannot import name _imaging

How do I check if a string can be parsed to a date?

 - Jan 19, 1990
 - January 19, 1990
 - Jan 19,1990
 - 01/19/1990
 - 01/19/90
 - 1990
 - Jan 1990
 - January1990

These are all valid dates. If there&#39;s any concern regarding the lack of space in between stuff in item #3 and the last item above, that can be easily remedied via automatically inserting a space in between letters/characters and numbers, if so needed.

But first, the basics:

I tried putting it in an `if statement`:

    if datetime.strptime(item, &#39;%Y&#39;) or datetime.strptime(item, &#39;%b %d %y&#39;) or datetime.strptime(item, &#39;%b %d %Y&#39;)  or datetime.strptime(item, &#39;%B %d %y&#39;) or datetime.strptime(item, &#39;%B %d %Y&#39;):

But that&#39;s in a try-except block, and keeps returning something like this:

    16343 time data &#39;JUNE1890&#39; does not match format &#39;%Y&#39;

Unless, it met the first condition in the `if` statement.

To clarify, I don&#39;t actually need the value of the date - I just want to know if it is. Ideally, it would&#39;ve been something like this:

    if item is date:
        print date
    else:
        print &quot;Not a date&quot;

Is there any way to do this?

Check if string has date, any format

I have read in a number of threads that Python `pickle`/`cPickle` cannot pickle lambda functions. However the following code works, using Python 2.7.6:
 
    import cPickle as pickle

    if __name__ == &quot;__main__&quot;:
        s = pickle.dumps(lambda x, y: x+y)
        f = pickle.loads(s)
        assert f(3,4) == 7

So what is going on? Or, rather, what is the limit of pickling lambdas?

[EDIT]
I think i know why this code runs. I forgot (sorry!) i am running stackless python, which has a form of micro-threads called tasklets executing a function. These tasklets can be halted, pickled, unpickled and continued, so i guess (asked on the stackless mailing list) that it also provides a way to pickle function bodies.

Can Python pickle lambda functions?

After performing a `groupby.sum()` on a `DataFrame` I&#39;m having some trouble trying to create my intended plot.

![grouped dataframe with multi-index][1]


```python
import pandas as pd
import numpy as np

np.random.seed(365)
rows = 100
data = {&#39;Month&#39;: np.random.choice([&#39;2014-01&#39;, &#39;2014-02&#39;, &#39;2014-03&#39;, &#39;2014-04&#39;], size=rows),
        &#39;Code&#39;: np.random.choice([&#39;A&#39;, &#39;B&#39;, &#39;C&#39;], size=rows),
        &#39;ColA&#39;: np.random.randint(5, 125, size=rows),
        &#39;ColB&#39;: np.random.randint(0, 51, size=rows),}
df = pd.DataFrame(data)

     Month Code  ColA  ColB
0  2014-03    C    59    47
1  2014-01    A    24     9
2  2014-02    C    77    50

dfg = df.groupby([&#39;Code&#39;, &#39;Month&#39;]).sum()

              ColA  ColB
Code Month              
A    2014-01   124   102
     2014-02   398   282
     2014-03   474   198
     2014-04   830   237
B    2014-01   477   300
     2014-02   591   167
     2014-03   522   192
     2014-04   367   169
C    2014-01   412   180
     2014-02   275   205
     2014-03   795   291
     2014-04   901   309
```


How can I create a subplot (`kind=&#39;bar&#39;`) for each `Code`, where the x-axis is the `Month` and the bars are `ColA` and `ColB`?

  [1]: http://i.stack.imgur.com/y9L5u.png

Pandas Plotting with Multi-Index

I am trying to use seaborn, because of its distplot function. But I prefer the default matplotlib settings. When I import seaborn, it changes automatically the appearance of my figure.

How can I use seaborn functions without changing the look of the plots?

How can I use seaborn without changing the matplotlib defaults?

I have this data frame `diamonds` which is composed of variables like `(carat, price, color)`, and I want to draw a scatter plot of `price` to `carat` for each `color`, which means different `color` has different color in the plot.

This is easy in `R` with `ggplot`:

    ggplot(aes(x=carat, y=price, color=color),  #by setting color=color, ggplot automatically draw in different colors
           data=diamonds) + geom_point(stat=&#39;summary&#39;, fun.y=median)

![enter image description here][1]

I wonder how could this be done in Python using `matplotlib` ?

PS:

I know about auxiliary plotting packages, such as `seaborn` and `ggplot for python`, and I don&#39;t prefer them, just want to find out if it is possible to do the job using `matplotlib` alone, ;P


  [1]: http://i.stack.imgur.com/HW43K.png

plot different color for different categorical levels using matplotlib

    %pylab inline
    
    import pandas as pd
    import numpy as np
    import matplotlib as mpl
    import seaborn as sns
    
    typessns = pd.DataFrame.from_csv(&#39;C:/data/testesns.csv&#39;, index_col=False, sep=&#39;;&#39;)
    
    mpl.rc(&quot;figure&quot;, figsize=(45, 10))
    sns.factorplot(&quot;MONTH&quot;, &quot;VALUE&quot;, hue=&quot;REGION&quot;, data=typessns, kind=&quot;box&quot;, palette=&quot;OrRd&quot;);


![enter image description here][1]

I always get a small size figure, no matter what size I &#39;ve specified in figsize...
How to fix it?


  [1]: http://i.stack.imgur.com/yQuim.png

How to change figuresize using seaborn factorplot

I have a simple factorplot

    import seaborn as sns
    g = sns.factorplot(&quot;name&quot;, &quot;miss_ratio&quot;, &quot;policy&quot;, dodge=.2, 
        linestyles=[&quot;none&quot;, &quot;none&quot;, &quot;none&quot;, &quot;none&quot;], data=df[df[&quot;level&quot;] == 2])


![enter image description here][1]

  [1]: http://i.stack.imgur.com/gg7aD.png

The problem is that the x labels all run together, making them unreadable. How do you rotate the text so that the labels are readable?

Content Type	Original Author	Original Content on Stackoverflow
Question	james pardon	View Question on Stackoverflow
Solution 1 - Python	Paul H	View Answer on Stackoverflow
Solution 2 - Python	achennu	View Answer on Stackoverflow
Solution 3 - Python	Sergio Cobo	View Answer on Stackoverflow
Solution 4 - Python	Hielke Walinga	View Answer on Stackoverflow

How can I change the font size using seaborn FacetGrid?

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

Solution 3 - Python

Solution 4 - Python

What is a nondeduced context?

Asp.NET Identity 2 giving "Invalid Token" error

Attributions