@@ -49,6 +49,7 @@ How do I create plots in pandas?
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I want a quick visual check of the data.
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.. ipython :: python
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+ :okwarning:
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@savefig 04_airqual_quick.png
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air_quality.plot()
@@ -78,6 +79,7 @@ I want to plot only the columns of the data table with the data from Paris.
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plt.clf()
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.. ipython :: python
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+ :okwarning:
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@savefig 04_airqual_paris.png
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air_quality[" station_paris" ].plot()
@@ -101,6 +103,7 @@ method. Hence, the :meth:`~DataFrame.plot` method works on both ``Series`` and
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I want to visually compare the :math: `NO_2 ` values measured in London versus Paris.
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.. ipython :: python
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+ :okwarning:
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@savefig 04_airqual_scatter.png
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air_quality.plot.scatter(x = " station_london" , y = " station_paris" , alpha = 0.5 )
@@ -133,6 +136,7 @@ One of the options is :meth:`DataFrame.plot.box`, which refers to a
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method is applicable on the air quality example data:
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.. ipython :: python
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+ :okwarning:
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@savefig 04_airqual_boxplot.png
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air_quality.plot.box()
@@ -157,6 +161,7 @@ For an introduction to plots other than the default line plot, see the user guid
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I want each of the columns in a separate subplot.
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.. ipython :: python
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+ :okwarning:
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@savefig 04_airqual_area_subplot.png
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axs = air_quality.plot.area(figsize = (12 , 4 ), subplots = True )
@@ -190,6 +195,7 @@ Some more formatting options are explained in the user guide section on :ref:`pl
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I want to further customize, extend or save the resulting plot.
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.. ipython :: python
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+ :okwarning:
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fig, axs = plt.subplots(figsize = (12 , 4 ))
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air_quality.plot.area(ax = axs)
@@ -200,6 +206,7 @@ I want to further customize, extend or save the resulting plot.
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.. ipython :: python
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:suppress:
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+ :okwarning:
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import os
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