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POStop pandas plot from doing new x-axis layout
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  1. POStop pandas plot from doing new x-axis layout
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    copied!<p>I have a problem of an automatic x-axis rescaling happening when I do the following:</p> <ol> <li>plot column 1</li> <li>plot column 1 where column 2 is notnull, but with different style.</li> </ol> <p>The second plot keeps rescaling the x-axis for me, losing the overview of the full column 1 plot. I have detailed what happened in this notebook: <a href="http://nbviewer.ipython.org/5596249" rel="nofollow">http://nbviewer.ipython.org/5596249</a></p> <p>Is there a way to keep the x-axis from rescaling at the 2nd plot? I have tried x_compat=True but that does not seem to do anything for me. </p> <p>Versions: pd: 0.11.0, MPL: 1.2.0</p> <p>[Edit] Here's the ipython output:</p> <pre><code>In [1]: import pandas as pd In [2]: pd.__version__ Out[2]: '0.12.0.dev-f354548' In [3]: dr = pd.date_range('now', periods=10) In [4]: df = pd.DataFrame(randn(10,2), index=dr) In [5]: df Out[5]: 0 1 2013-05-17 17:55:43 -0.440814 0.246620 2013-05-18 17:55:43 -0.732045 -0.896267 2013-05-19 17:55:43 1.131248 1.213163 2013-05-20 17:55:43 0.478372 0.624647 2013-05-21 17:55:43 1.425489 0.396689 2013-05-22 17:55:43 -0.881991 0.322917 2013-05-23 17:55:43 -1.047584 0.154040 2013-05-24 17:55:43 -0.327258 0.944843 2013-05-25 17:55:43 -0.013396 1.045499 2013-05-26 17:55:43 -0.035380 -0.611224 In [6]: df[1][:5]=nan In [7]: df Out[7]: 0 1 2013-05-17 17:55:43 -0.440814 NaN 2013-05-18 17:55:43 -0.732045 NaN 2013-05-19 17:55:43 1.131248 NaN 2013-05-20 17:55:43 0.478372 NaN 2013-05-21 17:55:43 1.425489 NaN 2013-05-22 17:55:43 -0.881991 0.322917 2013-05-23 17:55:43 -1.047584 0.154040 2013-05-24 17:55:43 -0.327258 0.944843 2013-05-25 17:55:43 -0.013396 1.045499 2013-05-26 17:55:43 -0.035380 -0.611224 In [8]: df[0].plot() Out[8]: &lt;matplotlib.axes.AxesSubplot at 0x116dbff50&gt; In [9]: df[1].plot() Out[9]: &lt;matplotlib.axes.AxesSubplot at 0x116dbff50&gt; In [10]: # the above did not rescale the x-axis, even so the plottable range of [1] is smaller In [11]: clf() In [12]: df['selector'] = df[1].notnull() In [13]: df Out[13]: 0 1 selector 2013-05-17 17:55:43 -0.440814 NaN False 2013-05-18 17:55:43 -0.732045 NaN False 2013-05-19 17:55:43 1.131248 NaN False 2013-05-20 17:55:43 0.478372 NaN False 2013-05-21 17:55:43 1.425489 NaN False 2013-05-22 17:55:43 -0.881991 0.322917 True 2013-05-23 17:55:43 -1.047584 0.154040 True 2013-05-24 17:55:43 -0.327258 0.944843 True 2013-05-25 17:55:43 -0.013396 1.045499 True 2013-05-26 17:55:43 -0.035380 -0.611224 True In [14]: df[0].plot() Out[14]: &lt;matplotlib.axes.AxesSubplot at 0x111288250&gt; In [15]: df[df.selector][0].plot(style='r*', markersize=5) Out[15]: &lt;matplotlib.axes.AxesSubplot at 0x111288250&gt; In [16]: # the above rescaled the x-axis </code></pre> <p>and here's just the code:</p> <pre><code>import pandas as pd pd.__version__ dr = pd.date_range('now',periods=10) df = pd.DataFrame(randn(10,2),index=dr) df[1][:5]=nan # This way it works: df[0].plot() df[1].plot() df['selector'] = df[1].notnull() df[0].plot() # This way the x-axis is being rescaled. How can I fix it at the previous setting? df[df.selector][0].plot(style='r*') </code></pre>
 

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