DOC: Added plt.show() at the end of each necessary block (pandas-dev#45772)

Reworded and moved title to the top of the page

Author: ehallam

doc/source/getting_started/intro_tutorials/04_plotting.rst

@@ -2,10 +2,16 @@
 
 {{ header }}
 
-.. ipython:: python
+How do I create plots in pandas?
+----------------------------------
+
+.. image:: ../../_static/schemas/04_plot_overview.svg
+   :align: center
+
+.. ipython::
 
-    import pandas as pd
-    import matplotlib.pyplot as plt
+    In [1]: import pandas as pd
+       ...: import matplotlib.pyplot as plt
 
 .. raw:: html
 
@@ -20,10 +26,10 @@
 
 .. include:: includes/air_quality_no2.rst
 
-.. ipython:: python
+.. ipython::
 
-    air_quality = pd.read_csv("data/air_quality_no2.csv", index_col=0, parse_dates=True)
-    air_quality.head()
+    In [1]: air_quality = pd.read_csv("data/air_quality_no2.csv", index_col=0, parse_dates=True)
+       ...: air_quality.head()
 
 .. note::
     The usage of the ``index_col`` and ``parse_dates`` parameters of the ``read_csv`` function to define the first (0th) column as
@@ -35,23 +41,18 @@
     </ul>
     </div>
 
-How to create plots in pandas?
-------------------------------
-
-.. image:: ../../_static/schemas/04_plot_overview.svg
-   :align: center
-
 .. raw:: html
 
     <ul class="task-bullet">
         <li>
 
 I want a quick visual check of the data.
 
-.. ipython:: python
+.. ipython::
 
     @savefig 04_airqual_quick.png
-    air_quality.plot()
+    In [1]: air_quality.plot()
+       ...: plt.show()
 
 With a ``DataFrame``, pandas creates by default one line plot for each of
 the columns with numeric data.
@@ -69,9 +70,18 @@ the columns with numeric data.
 I want to plot only the columns of the data table with the data from Paris.
 
 .. ipython:: python
+   :suppress:
+
+    # We need to clear the figure here as, within doc generation, the plot
+    # accumulates data on each plot(). This is not needed when running
+    # in a notebook, so is suppressed from output.
+    plt.clf()
+
+.. ipython::
 
     @savefig 04_airqual_paris.png
-    air_quality["station_paris"].plot()
+    In [1]: air_quality["station_paris"].plot()
+       ...: plt.show()
 
 To plot a specific column, use the selection method of the
 :ref:`subset data tutorial <10min_tut_03_subset>` in combination with the :meth:`~DataFrame.plot`
@@ -90,11 +100,11 @@ method. Hence, the :meth:`~DataFrame.plot` method works on both ``Series`` and
 
 I want to visually compare the :math:`NO_2` values measured in London versus Paris.
 
-.. ipython:: python
+.. ipython::
 
     @savefig 04_airqual_scatter.png
-    air_quality.plot.scatter(x="station_london", y="station_paris", alpha=0.5)
-
+    In [1]: air_quality.plot.scatter(x="station_london", y="station_paris", alpha=0.5)
+       ...: plt.show()
 .. raw:: html
 
         </li>
@@ -121,10 +131,11 @@ One of the options is :meth:`DataFrame.plot.box`, which refers to a
 `boxplot <https://en.wikipedia.org/wiki/Box_plot>`__. The ``box``
 method is applicable on the air quality example data:
 
-.. ipython:: python
+.. ipython::
 
     @savefig 04_airqual_boxplot.png
-    air_quality.plot.box()
+    In [1]: air_quality.plot.box()
+       ...: plt.show()
 
 .. raw:: html
 
@@ -144,10 +155,11 @@ For an introduction to plots other than the default line plot, see the user guid
 
 I want each of the columns in a separate subplot.
 
-.. ipython:: python
+.. ipython::
 
     @savefig 04_airqual_area_subplot.png
-    axs = air_quality.plot.area(figsize=(12, 4), subplots=True)
+    In [1]: axs = air_quality.plot.area(figsize=(12, 4), subplots=True)
+       ...: plt.show()
 
 Separate subplots for each of the data columns are supported by the ``subplots`` argument
 of the ``plot`` functions. The builtin options available in each of the pandas plot
@@ -176,13 +188,14 @@ Some more formatting options are explained in the user guide section on :ref:`pl
 
 I want to further customize, extend or save the resulting plot.
 
-.. ipython:: python
+.. ipython::
 
-    fig, axs = plt.subplots(figsize=(12, 4))
-    air_quality.plot.area(ax=axs)
     @savefig 04_airqual_customized.png
-    axs.set_ylabel("NO$_2$ concentration")
-    fig.savefig("no2_concentrations.png")
+    In [1]: fig, axs = plt.subplots(figsize=(12, 4))
+       ...: air_quality.plot.area(ax=axs)
+       ...: axs.set_ylabel("NO$_2$ concentration")
+       ...: fig.savefig("no2_concentrations.png")
+       ...: plt.show()
 
 .. ipython:: python
    :suppress: