@@ -49,6 +49,7 @@ How do I create plots in pandas?
4949I want a quick visual check of the data.
5050
5151.. ipython :: python
52+ :okwarning:
5253
5354 @savefig 04_airqual_quick.png
5455 air_quality.plot()
@@ -78,6 +79,7 @@ I want to plot only the columns of the data table with the data from Paris.
7879 plt.clf()
7980
8081 .. ipython :: python
82+ :okwarning:
8183
8284 @savefig 04_airqual_paris.png
8385 air_quality[" station_paris" ].plot()
@@ -101,6 +103,7 @@ method. Hence, the :meth:`~DataFrame.plot` method works on both ``Series`` and
101103I want to visually compare the :math: `NO_2 ` values measured in London versus Paris.
102104
103105.. ipython :: python
106+ :okwarning:
104107
105108 @savefig 04_airqual_scatter.png
106109 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
133136method is applicable on the air quality example data:
134137
135138.. ipython :: python
139+ :okwarning:
136140
137141 @savefig 04_airqual_boxplot.png
138142 air_quality.plot.box()
@@ -157,6 +161,7 @@ For an introduction to plots other than the default line plot, see the user guid
157161I want each of the columns in a separate subplot.
158162
159163.. ipython :: python
164+ :okwarning:
160165
161166 @savefig 04_airqual_area_subplot.png
162167 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
190195I want to further customize, extend or save the resulting plot.
191196
192197.. ipython :: python
198+ :okwarning:
193199
194200 fig, axs = plt.subplots(figsize = (12 , 4 ))
195201 air_quality.plot.area(ax = axs)
@@ -200,6 +206,7 @@ I want to further customize, extend or save the resulting plot.
200206
201207 .. ipython :: python
202208 :suppress:
209+ :okwarning:
203210
204211 import os
205212
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