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Oct 18, 2020
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DOC: remove debug messages by adding semicolons #37206

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56 changes: 28 additions & 28 deletions doc/source/user_guide/visualization.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -64,7 +64,7 @@ On DataFrame, :meth:`~DataFrame.plot` is a convenience to plot all of the column

plt.figure();
@savefig frame_plot_basic.png
df.plot()
df.plot();

You can plot one column versus another using the ``x`` and ``y`` keywords in
:meth:`~DataFrame.plot`:
Expand Down Expand Up @@ -119,7 +119,7 @@ For example, a bar plot can be created the following way:
plt.figure();

@savefig bar_plot_ex.png
df.iloc[5].plot(kind="bar")
df.iloc[5].plot(kind="bar");

You can also create these other plots using the methods ``DataFrame.plot.<kind>`` instead of providing the ``kind`` keyword argument. This makes it easier to discover plot methods and the specific arguments they use:

Expand Down Expand Up @@ -180,7 +180,7 @@ bar plot:
df2 = pd.DataFrame(np.random.rand(10, 4), columns=["a", "b", "c", "d"])

@savefig bar_plot_multi_ex.png
df2.plot.bar()
df2.plot.bar();

To produce a stacked bar plot, pass ``stacked=True``:

Expand All @@ -193,7 +193,7 @@ To produce a stacked bar plot, pass ``stacked=True``:
.. ipython:: python

@savefig bar_plot_stacked_ex.png
df2.plot.bar(stacked=True)
df2.plot.bar(stacked=True);

To get horizontal bar plots, use the ``barh`` method:

Expand All @@ -206,7 +206,7 @@ To get horizontal bar plots, use the ``barh`` method:
.. ipython:: python

@savefig barh_plot_stacked_ex.png
df2.plot.barh(stacked=True)
df2.plot.barh(stacked=True);

.. _visualization.hist:

Expand Down Expand Up @@ -414,7 +414,7 @@ groupings. For instance,
df = pd.DataFrame(np.random.rand(10, 2), columns=["Col1", "Col2"])
df["X"] = pd.Series(["A", "A", "A", "A", "A", "B", "B", "B", "B", "B"])

plt.figure()
plt.figure();

@savefig box_plot_ex2.png
bp = df.boxplot(by="X")
Expand Down Expand Up @@ -518,7 +518,7 @@ When input data contains ``NaN``, it will be automatically filled by 0. If you w
df = pd.DataFrame(np.random.rand(10, 4), columns=["a", "b", "c", "d"])

@savefig area_plot_stacked.png
df.plot.area()
df.plot.area();

To produce an unstacked plot, pass ``stacked=False``. Alpha value is set to 0.5 unless otherwise specified:

Expand All @@ -531,7 +531,7 @@ To produce an unstacked plot, pass ``stacked=False``. Alpha value is set to 0.5
.. ipython:: python

@savefig area_plot_unstacked.png
df.plot.area(stacked=False)
df.plot.area(stacked=False);

.. _visualization.scatter:

Expand All @@ -554,7 +554,7 @@ These can be specified by the ``x`` and ``y`` keywords.
df = pd.DataFrame(np.random.rand(50, 4), columns=["a", "b", "c", "d"])

@savefig scatter_plot.png
df.plot.scatter(x="a", y="b")
df.plot.scatter(x="a", y="b");

To plot multiple column groups in a single axes, repeat ``plot`` method specifying target ``ax``.
It is recommended to specify ``color`` and ``label`` keywords to distinguish each groups.
Expand All @@ -563,7 +563,7 @@ It is recommended to specify ``color`` and ``label`` keywords to distinguish eac

ax = df.plot.scatter(x="a", y="b", color="DarkBlue", label="Group 1")
@savefig scatter_plot_repeated.png
df.plot.scatter(x="c", y="d", color="DarkGreen", label="Group 2", ax=ax)
df.plot.scatter(x="c", y="d", color="DarkGreen", label="Group 2", ax=ax);

.. ipython:: python
:suppress:
Expand All @@ -576,7 +576,7 @@ each point:
.. ipython:: python

@savefig scatter_plot_colored.png
df.plot.scatter(x="a", y="b", c="c", s=50)
df.plot.scatter(x="a", y="b", c="c", s=50);


.. ipython:: python
Expand All @@ -591,7 +591,7 @@ bubble chart using a column of the ``DataFrame`` as the bubble size.
.. ipython:: python

@savefig scatter_plot_bubble.png
df.plot.scatter(x="a", y="b", s=df["c"] * 200)
df.plot.scatter(x="a", y="b", s=df["c"] * 200);

.. ipython:: python
:suppress:
Expand Down Expand Up @@ -837,7 +837,7 @@ You can create a scatter plot matrix using the
df = pd.DataFrame(np.random.randn(1000, 4), columns=["a", "b", "c", "d"])

@savefig scatter_matrix_kde.png
scatter_matrix(df, alpha=0.2, figsize=(6, 6), diagonal="kde")
scatter_matrix(df, alpha=0.2, figsize=(6, 6), diagonal="kde");

.. ipython:: python
:suppress:
Expand Down Expand Up @@ -1086,7 +1086,7 @@ layout and formatting of the returned plot:

plt.figure();
@savefig series_plot_basic2.png
ts.plot(style="k--", label="Series")
ts.plot(style="k--", label="Series");

.. ipython:: python
:suppress:
Expand Down Expand Up @@ -1144,7 +1144,7 @@ it empty for ylabel.
df.plot();

@savefig plot_xlabel_ylabel.png
df.plot(xlabel="new x", ylabel="new y")
df.plot(xlabel="new x", ylabel="new y");

.. ipython:: python
:suppress:
Expand Down Expand Up @@ -1320,7 +1320,7 @@ with the ``subplots`` keyword:
.. ipython:: python

@savefig frame_plot_subplots.png
df.plot(subplots=True, figsize=(6, 6))
df.plot(subplots=True, figsize=(6, 6));

.. ipython:: python
:suppress:
Expand All @@ -1343,7 +1343,7 @@ or columns needed, given the other.
.. ipython:: python

@savefig frame_plot_subplots_layout.png
df.plot(subplots=True, layout=(2, 3), figsize=(6, 6), sharex=False)
df.plot(subplots=True, layout=(2, 3), figsize=(6, 6), sharex=False);

.. ipython:: python
:suppress:
Expand All @@ -1354,7 +1354,7 @@ The above example is identical to using:

.. ipython:: python

df.plot(subplots=True, layout=(2, -1), figsize=(6, 6), sharex=False)
df.plot(subplots=True, layout=(2, -1), figsize=(6, 6), sharex=False);

.. ipython:: python
:suppress:
Expand All @@ -1379,9 +1379,9 @@ otherwise you will see a warning.
target1 = [axes[0][0], axes[1][1], axes[2][2], axes[3][3]]
target2 = [axes[3][0], axes[2][1], axes[1][2], axes[0][3]]

df.plot(subplots=True, ax=target1, legend=False, sharex=False, sharey=False)
df.plot(subplots=True, ax=target1, legend=False, sharex=False, sharey=False);
@savefig frame_plot_subplots_multi_ax.png
(-df).plot(subplots=True, ax=target2, legend=False, sharex=False, sharey=False)
(-df).plot(subplots=True, ax=target2, legend=False, sharex=False, sharey=False);

.. ipython:: python
:suppress:
Expand Down Expand Up @@ -1409,15 +1409,15 @@ Another option is passing an ``ax`` argument to :meth:`Series.plot` to plot on a

fig, axes = plt.subplots(nrows=2, ncols=2)
plt.subplots_adjust(wspace=0.2, hspace=0.5)
df["A"].plot(ax=axes[0, 0])
axes[0, 0].set_title("A")
df["B"].plot(ax=axes[0, 1])
axes[0, 1].set_title("B")
df["C"].plot(ax=axes[1, 0])
axes[1, 0].set_title("C")
df["D"].plot(ax=axes[1, 1])
df["A"].plot(ax=axes[0, 0]);
axes[0, 0].set_title("A");
df["B"].plot(ax=axes[0, 1]);
axes[0, 1].set_title("B");
df["C"].plot(ax=axes[1, 0]);
axes[1, 0].set_title("C");
df["D"].plot(ax=axes[1, 1]);
@savefig series_plot_multi.png
axes[1, 1].set_title("D")
axes[1, 1].set_title("D");

.. ipython:: python
:suppress:
Expand Down