In your case, you&#39;re actually wanting to disable the offset.  Using scientific notation is a separate setting from showing things in terms of an offset value.

However, `ax.ticklabel_format(useOffset=False)` should have worked (though you&#39;ve listed it as one of the things that didn&#39;t).

For example:

    fig, ax = plt.subplots()
    ax.plot(range(2003,2012,1),range(200300,201200,100))
    ax.ticklabel_format(useOffset=False)
    plt.show()

![enter image description here][1]

If you want to disable both the offset and scientific notaion, you&#39;d use `ax.ticklabel_format(useOffset=False, style=&#39;plain&#39;)`.

---

Difference between &quot;offset&quot; and &quot;scientific notation&quot;
-----------------------------------------------------

In matplotlib axis formatting, &quot;scientific notation&quot; refers to a _multiplier_ for the numbers show, while the &quot;offset&quot; is a separate term that is _added_.

Consider this example:

    import numpy as np
    import matplotlib.pyplot as plt
    
    x = np.linspace(1000, 1001, 100)
    y = np.linspace(1e-9, 1e9, 100)
    
    fig, ax = plt.subplots()
    ax.plot(x, y)
    plt.show()

The x-axis will have an offset (note the `+` sign) and the y-axis will use scientific notation (as a multiplier -- No plus sign).

![enter image description here][2]

We can disable either one separately.  The most convenient way is the `ax.ticklabel_format` method (or `plt.ticklabel_format`).

For example, if we call:
    
    ax.ticklabel_format(style=&#39;plain&#39;)

We&#39;ll disable the scientific notation on the y-axis:

![enter image description here][3]

And if we call

    ax.ticklabel_format(useOffset=False)

We&#39;ll disable the offset on the x-axis, but leave the y-axis scientific notation untouched:

![enter image description here][4]

Finally, we can disable both through:

    ax.ticklabel_format(useOffset=False, style=&#39;plain&#39;)

![enter image description here][5]


  [1]: http://i.stack.imgur.com/eqcZB.png
  [2]: http://i.stack.imgur.com/Mb5ys.png
  [3]: http://i.stack.imgur.com/SttQI.png
  [4]: http://i.stack.imgur.com/ggBLK.png
  [5]: http://i.stack.imgur.com/16vy2.png

When using R it&#39;s handy to load &quot;practice&quot; datasets using 

    data(iris)
or

    data(mtcars)

Is there something similar for Pandas? I know I can load using any other method, just curious if there&#39;s anything builtin.

Sample datasets in Pandas

I have a tableview which, when loaded, each cell could possibly return an NSError, which I have chosen to display in a UIAlertController.  Problem is I get this error in the console if multiple errors are returned.

&gt; Warning: Attempt to present UIAlertController: 0x14e64cb00  on MessagesMasterVC: 0x14e53d800 which is already presenting (null)

Ideally, I would ideally like to handle this in my UIAlertController extension method.

    class func simpleAlertWithMessage(message: String!) -&gt; UIAlertController {
		
		let alertController = UIAlertController(title: nil, message: message, preferredStyle: UIAlertControllerStyle.Alert)
		let cancel = UIAlertAction(title: &quot;Ok&quot;, style: .Cancel, handler: nil)
		
		alertController.addAction(cancel)
		return alertController
	}

Based on matt&#39;s answer, I changed the extension to a UIViewController extension, its much cleaner and saves lots of presentViewController code.

    	func showSimpleAlertWithMessage(message: String!) {
		
		let alertController = UIAlertController(title: nil, message: message, preferredStyle: UIAlertControllerStyle.Alert)
		let cancel = UIAlertAction(title: &quot;Ok&quot;, style: .Cancel, handler: nil)
		
		alertController.addAction(cancel)
		
		if self.presentedViewController == nil {
			self.presentViewController(alertController, animated: true, completion: nil)
		}
	}


What is the best way to check if a UIAlertController is already presenting?

I&#39;ve been trying to suppress scientific notation in pyplot for a few hours now.  After trying multiple solutions without success, I would like some help.

    plt.plot(range(2003,2012,1),range(200300,201200,100))
    # several solutions from other questions have not worked, including
    # plt.ticklabel_format(style=&#39;sci&#39;, axis=&#39;x&#39;, scilimits=(-1000000,1000000))
    # ax.get_xaxis().get_major_formatter().set_useOffset(False)
    plt.show()

![plot][1]

  [1]: http://i.stack.imgur.com/ueL08.png &quot;plot&quot;

prevent scientific notation in matplotlib.pyplot

I've been trying to suppress scientific notation in pyplot for a few hours now. After trying multiple solutions without success, I would like some help.
<pre><code class="hljs language-scss">plt.plot(range(2003,2012,1),range(200300,201200,100))
# several solutions from other questions have not worked, including
# plt.ticklabel_format(style='sci', axis='x', scilimits=(-1000000,1000000))
# ax.get_xaxis().get_major_formatter().set_useOffset(False)
plt.show()
</code></pre>
![plot][1]
[1]: <a href="http://i.stack.imgur.com/ueL08.png" target="_blank" rel="noopener noreferrer">http://i.stack.imgur.com/ueL08.png</a> "plot"

Python&#39;s [`curve_fit`][1] calculates the best-fit parameters for a function with a single independent variable, but is there a way, using `curve_fit` or something else, to fit for a function with multiple independent variables? For example:

    def func(x, y, a, b, c):
    	return log(a) + b*log(x) + c*log(y)

where x and y are the independent variable and we would like to fit for a, b, and c.
  [1]: http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html

Python curve_fit with multiple independent variables

In solid mechanics, I often use Python and write code that looks like the following:

    for i in range(3):
        for j in range(3):
            for k in range(3):
                for l in range(3):
                    # do stuff

I do this really often that I start to wonder whether there is a more concise way to do this. The drawback of the current code is: if I comply with `PEP8`, then I cannot exceed the 79-character-limit per line, and there is not too much space left, especially if this is again in a function of a class.




How can I make a for-loop pyramid more concise in Python?

I&#39;ve got Pycharm 4 running on my Linux (Ubuntu 14.04) machine.  In addition to the system python, I&#39;ve also got Anaconda installed.  Getting the two to play nicely together seems to be a bit of a problem... PyCharm provides some interesting integration for `virtualenv`s and `pip`, but the Anaconda Python distribution seems to prefer using its own `conda` tool for both activities.

Is there a relatively simple/painless way to be able to use `conda` in conjunction with PyCharm?  Not just as an alternative interpreter i.e. point PyCharm at the Anaconda Python binary for a project interpreter, but to be able to create, source/activate and deactivate virtual envs, add/remove packages in those virtual envs, etc. 

Or am I going to have to choose between using Anaconda (and having a more recent and up-to-date python than may come with the system), and being able to use PyCharm&#39;s features to their fullest extent?

Using (Ana)conda within PyCharm

I have been using the scikit-learn library. I&#39;m trying to use the Gaussian Naive Bayes Module under the scikit-learn library but I&#39;m running into the following error. TypeError: cannot perform reduce with flexible type

Below is the code snippet. 

    training = GaussianNB()
	training = training.fit(trainData, target)
	prediction = training.predict(testData)

This is target

    [&#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;ALL&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;, &#39;AML&#39;]


This is trainData

    [[&#39;-214&#39; &#39;-153&#39; &#39;-58&#39; ..., &#39;36&#39; &#39;191&#39; &#39;-37&#39;]
    [&#39;-139&#39; &#39;-73&#39; &#39;-1&#39; ..., &#39;11&#39; &#39;76&#39; &#39;-14&#39;]
    [&#39;-76&#39; &#39;-49&#39; &#39;-307&#39; ..., &#39;41&#39; &#39;228&#39; &#39;-41&#39;]
    ..., 
    [&#39;-32&#39; &#39;-49&#39; &#39;49&#39; ..., &#39;-26&#39; &#39;133&#39; &#39;-32&#39;]
    [&#39;-124&#39; &#39;-79&#39; &#39;-37&#39; ..., &#39;39&#39; &#39;298&#39; &#39;-3&#39;]
    [&#39;-135&#39; &#39;-186&#39; &#39;-70&#39; ..., &#39;-12&#39; &#39;790&#39; &#39;-10&#39;]]

Below is the stack trace

    Traceback (most recent call last):
    File &quot;prediction.py&quot;, line 90, in &lt;module&gt;
      gaussianNaiveBayes()
    File &quot;prediction.py&quot;, line 76, in gaussianNaiveBayes
      training = training.fit(trainData, target)
    File &quot;/Library/Python/2.7/site-packages/sklearn/naive_bayes.py&quot;, line 163, in fit
      self.theta_[i, :] = np.mean(Xi, axis=0)
    File &quot;/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/ core/fromnumeric.py&quot;, line 2716, in mean
      out=out, keepdims=keepdims)
    File &quot;/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/core/_methods.py&quot;, line 62, in _mean
      ret = um.add.reduce(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims)
    TypeError: cannot perform reduce with flexible type

TypeError: cannot perform reduce with flexible type

I&#39;d like to plot a single point on my graph, but it seems like they all need to plot as either a list or equation.

I need to plot like `ax.plot(x, y)` and a dot will be appeared at my `x`, `y` coordinates on my graph.


    import matplotlib.pyplot as plt
    from mpl_toolkits.axes_grid1 import host_subplot
    import mpl_toolkits.axisartist as AA
    import numpy
    fig = plt.figure()
	plt.xlabel(&#39;Width&#39;)
	plt.ylabel(&#39;Height&#39;)
	ax = fig.gca()
	ax.plot(105, 200)
	plt.grid()
	plt.show()

[![enter image description here][1]][1]


  [1]: https://i.stack.imgur.com/v9mYV.png

How to plot a single point in matplotlib

I would like to move some ticks&#39; labels horizontally along the x-axis,  without moving the corresponding ticks.

More specifically, when rotating labels with `plt.setp`, the centers of the labels&#39; text stay aligned with the ticks. I would like to shift those labels to the right, so that the near ends of the labels get aligned instead as suggested on the image below.

![enter image description here][1]

 
I am aware of [this post][2] and [this one][3], however the answers are interesting kludges rather than strict answers to the question.

my code:

    import matplotlib.pyplot as plt
    import numpy as np
    import datetime
    
    # my fake data
    dates = np.array([datetime.datetime(2000,1,1) + datetime.timedelta(days=i) for i in range(365*5)])
    data = np.sin(np.arange(365*5)/365.0*2*np.pi - 0.25*np.pi) + np.random.rand(365*5) /3
    
    # creates fig with 2 subplots
    fig = plt.figure(figsize=(10.0, 6.0))
    ax = plt.subplot2grid((2,1), (0, 0))
    ax2 = plt.subplot2grid((2,1), (1, 0))
    ## plot dates
    ax2.plot_date( dates, data )
    
    # rotates labels 
    plt.setp( ax2.xaxis.get_majorticklabels(), rotation=-45 ) 
    
    # try to shift labels to the right
    ax2.xaxis.get_majorticklabels()[2].set_y(-.1)
    ax2.xaxis.get_majorticklabels()[2].set_x(10**99)
    
    plt.show()

  Strangely enough, `set_y` behaves as expected, but even if I set `x` to a fantasillion, the labels would not move by one iota. 
(The use of `plot_date` may introduce additional confusion, but the same actually happens with `plot`.)


  [1]: http://i.stack.imgur.com/CESDj.png
  [2]: https://stackoverflow.com/q/16162514/4041970
  [3]: https://stackoverflow.com/q/24190858/4041970

How to move a tick label in matplotlib

Let 0 &lt;= x &lt;= 1. I have two columns `f` and `g` of length 5000 respectively. Now I plot:

    plt.plot(x, f, &#39;-&#39;)
    plt.plot(x, g, &#39;*&#39;)

I want to find the point &#39;x&#39; where the curve intersects. I don&#39;t want to find the intersection of f and g. 
I can do it simply with:

    set(f) &amp; set(g)


Intersection of two graphs in Python, find the x value

I got stuck on something that feels like should be relatively easy. The code I bring below is a sample based on a larger project I&#39;m working on. I saw no reason to post all the details, so please accept the data structures I bring as is.

Basically, I&#39;m creating a bar chart, and I just can figure out how to add value labels on the bars (in the center of the bar, or just above it). Been looking at samples around the web but with no success implementing on my own code. I believe the solution is either with &#39;text&#39; or &#39;annotate&#39;, but I:
a) don&#39;t know which one to use (and generally speaking, haven&#39;t figured out when to use which).
b) can&#39;t see to get either to present the value labels.
Would appreciate your help, my code below.
Thanks in advance!

    import numpy as np
    import pandas as pd
    import matplotlib.pyplot as plt
    pd.set_option(&#39;display.mpl_style&#39;, &#39;default&#39;) 
    %matplotlib inline
    
    # Bring some raw data.
    frequencies = [6, 16, 75, 160, 244, 260, 145, 73, 16, 4, 1]
    
    # In my original code I create a series and run on that, 
    # so for consistency I create a series from the list.
    freq_series = pd.Series.from_array(frequencies)
    
    x_labels = [108300.0, 110540.0, 112780.0, 115020.0, 117260.0, 119500.0, 
                121740.0, 123980.0, 126220.0, 128460.0, 130700.0]
    
    # Plot the figure.
    plt.figure(figsize=(12, 8))
    fig = freq_series.plot(kind=&#39;bar&#39;)
    fig.set_title(&#39;Amount Frequency&#39;)
    fig.set_xlabel(&#39;Amount ($)&#39;)
    fig.set_ylabel(&#39;Frequency&#39;)
    fig.set_xticklabels(x_labels)

Adding value labels on a matplotlib bar chart

I am trying to set the format to two decimal numbers in a matplotlib subplot environment. Unfortunately, I do not have any idea how to solve this task.

To prevent using scientific notation on the y-axis I used `ScalarFormatter(useOffset=False)` as you can see in my snippet below. I think my task should be solved by passing further options/arguments to the used formatter. However, I could not find any hint in matplotlib&#39;s documentation.

How can I set two decimal digits or none (both cases are needed)? I am not able to provide sample data, unfortunately.

---
-- SNIPPET --

    f, axarr = plt.subplots(3, sharex=True)

    data = conv_air
    x = range(0, len(data))

    axarr[0].scatter(x, data)
    axarr[0].set_ylabel(&#39;$T_\mathrm{air,2,2}$&#39;, size=FONT_SIZE)
    axarr[0].yaxis.set_major_locator(MaxNLocator(5))
    axarr[0].yaxis.set_major_formatter(ScalarFormatter(useOffset=False))
    axarr[0].tick_params(direction=&#39;out&#39;, labelsize=FONT_SIZE)
    axarr[0].grid(which=&#39;major&#39;, alpha=0.5)
    axarr[0].grid(which=&#39;minor&#39;, alpha=0.2)

    data = conv_dryer
    x = range(0, len(data))

    axarr[1].scatter(x, data)
    axarr[1].set_ylabel(&#39;$T_\mathrm{dryer,2,2}$&#39;, size=FONT_SIZE)
    axarr[1].yaxis.set_major_locator(MaxNLocator(5))
    axarr[1].yaxis.set_major_formatter(ScalarFormatter(useOffset=False))
    axarr[1].tick_params(direction=&#39;out&#39;, labelsize=FONT_SIZE)
    axarr[1].grid(which=&#39;major&#39;, alpha=0.5)
    axarr[1].grid(which=&#39;minor&#39;, alpha=0.2)

    data = conv_lambda
    x = range(0, len(data))

    axarr[2].scatter(x, data)
    axarr[2].set_xlabel(&#39;Iterationsschritte&#39;, size=FONT_SIZE)
    axarr[2].xaxis.set_major_locator(MaxNLocator(integer=True))
    axarr[2].set_ylabel(&#39;$\lambda$&#39;, size=FONT_SIZE)
    axarr[2].yaxis.set_major_formatter(ScalarFormatter(useOffset=False))
    axarr[2].yaxis.set_major_locator(MaxNLocator(5))
    axarr[2].tick_params(direction=&#39;out&#39;, labelsize=FONT_SIZE)
    axarr[2].grid(which=&#39;major&#39;, alpha=0.5)
    axarr[2].grid(which=&#39;minor&#39;, alpha=0.2)

Content Type	Original Author	Original Content on Stackoverflow
Question	Travis Osterman	View Question on Stackoverflow
Solution 1 - Python	Joe Kington	View Answer on Stackoverflow

prevent scientific notation in matplotlib.pyplot

Python Problem Overview

Python Solutions

Solution 1 - Python

Difference between "offset" and "scientific notation"

What is the best way to check if a UIAlertController is already presenting?

Sample datasets in Pandas

Attributions