matplotlib · tacaswell · Jun 30, 2022 · Jun 29, 2022 · Jun 29, 2022
diff --git a/examples/showcase/bachelors_degrees_by_gender.py b/examples/showcase/bachelors_degrees_by_gender.py
diff --git a/examples/showcase/stock_prices.py b/examples/showcase/stock_prices.py
@@ -0,0 +1,119 @@
+"""
+==========================
+Stock prices over 32 years
+==========================
+
+.. redirect-from:: /gallery/showcase/bachelors_degrees_by_gender
+
+A graph of multiple time series that demonstrates custom styling of plot frame,
+tick lines, tick labels, and line graph properties. It also uses custom
+placement of text labels along the right edge as an alternative to a
+conventional legend.
+
+Note: The third-party mpl style dufte_ produces similar-looking plots with less
+code.
+
+.. _dufte: https://github.com/nschloe/dufte
+"""
+
+import numpy as np
+import matplotlib.transforms as mtransforms
+import matplotlib.pyplot as plt
+from matplotlib.cbook import get_sample_data
+
+
+def convertdate(x):
+    return np.datetime64(x, 'D')
+
+
+fname = get_sample_data('Stocks.csv', asfileobj=False)
+stock_data = np.genfromtxt(fname, encoding='utf-8', delimiter=',',
+                           names=True, dtype=None, converters={0: convertdate},
+                           skip_header=1)
+
+
+fig, ax = plt.subplots(1, 1, figsize=(6, 8), layout='constrained')
+
+# These are the colors that will be used in the plot
+ax.set_prop_cycle(color=[
+    '#1f77b4', '#aec7e8', '#ff7f0e', '#ffbb78', '#2ca02c', '#98df8a',
+    '#d62728', '#ff9896', '#9467bd', '#c5b0d5', '#8c564b', '#c49c94',
+    '#e377c2', '#f7b6d2', '#7f7f7f', '#c7c7c7', '#bcbd22', '#dbdb8d',
+    '#17becf', '#9edae5'])
+
+stocks_name = ['IBM', 'Apple', 'Microsoft', 'Xerox', 'Amazon', 'Dell',
+               'Alphabet', 'Adobe', 'S&P 500', 'NASDAQ']
+stocks_ticker = ['IBM', 'AAPL', 'MSFT', 'XRX', 'AMZN', 'DELL', 'GOOGL',
+                 'ADBE', 'GSPC', 'IXIC']
+
+# Manually adjust the label positions vertically (units are points = 1/72 inch)
+y_offsets = {k: 0 for k in stocks_ticker}
+y_offsets['IBM'] = 5
+y_offsets['AAPL'] = -5
+y_offsets['AMZN'] = -6
+
+for nn, column in enumerate(stocks_ticker):
+    # Plot each line separately with its own color.
+    # don't include any data with NaN.
+    good = np.nonzero(np.isfinite(stock_data[column]))
+    line, = ax.plot(stock_data['Date'][good], stock_data[column][good], lw=2.5)
+
+    # Add a text label to the right end of every line. Most of the code below
+    # is adding specific offsets y position because some labels overlapped.
+    y_pos = stock_data[column][-1]
+
+    # Use an offset transform, in points, for any text that needs to be nudged
+    # up or down.
+    offset = y_offsets[column] / 72
+    trans = mtransforms.ScaledTranslation(0, offset, fig.dpi_scale_trans)
+    trans = ax.transData + trans
+
+    # Again, make sure that all labels are large enough to be easily read
+    # by the viewer.
+    ax.text(np.datetime64('2022-10-01'), y_pos, stocks_name[nn],
+            color=line.get_color(), transform=trans)
+
+ax.set_xlim(np.datetime64('1989-06-01'), np.datetime64('2023-01-01'))
+
+fig.suptitle("Technology company stocks prices dollars (1990-2022)",
+             ha="center")
+
+# Remove the plot frame lines. They are unnecessary here.
+ax.spines[:].set_visible(False)
+
+# Ensure that the axis ticks only show up on the bottom and left of the plot.
+# Ticks on the right and top of the plot are generally unnecessary.
+ax.xaxis.tick_bottom()
+ax.yaxis.tick_left()
+ax.set_yscale('log')
+
+# Provide tick lines across the plot to help your viewers trace along
+# the axis ticks. Make sure that the lines are light and small so they
+# don't obscure the primary data lines.
+ax.grid(True, 'major', 'both', ls='--', lw=.5, c='k', alpha=.3)
+
+# Remove the tick marks; they are unnecessary with the tick lines we just
+# plotted. Make sure your axis ticks are large enough to be easily read.
+# You don't want your viewers squinting to read your plot.
+ax.tick_params(axis='both', which='both', labelsize='large',
+               bottom=False, top=False, labelbottom=True,
+               left=False, right=False, labelleft=True)
+
+# Finally, save the figure as a PNG.
+# You can also save it as a PDF, JPEG, etc.
+# Just change the file extension in this call.
+# fig.savefig('percent-bachelors-degrees-women-usa.png', bbox_inches='tight')
+plt.show()
+
+#############################################################################
+#
+# .. admonition:: References
+#
+#    The use of the following functions, methods, classes and modules is shown
+#    in this example:
+#
+#    - `matplotlib.pyplot.subplots`
+#    - `matplotlib.axes.Axes.text`
+#    - `matplotlib.axis.XAxis.tick_bottom`
+#    - `matplotlib.axis.YAxis.tick_left`
+#    - `matplotlib.artist.Artist.set_visible`