[Term Entry] Python matplotlib - pyplot: stackplot()

* Add stackplot term entry documentation

- Add comprehensive stackplot.md documentation for matplotlib.pyplot.stackplot()
- Include syntax, parameters, examples, and FAQ sections
- Add stackplot-example.png image demonstrating sales data visualization
- Follow Codecademy template standards with proper YAML front matter

* Revise stackplot documentation for clarity and detail

Updated the documentation for the stackplot function in Matplotlib. Changes include improved title and description, parameter details, and examples.

* Add image for codebyte example output

- Added stackplot-codebyte-example.png showing the visual output of the codebyte example
- Added descriptive text and user note about static vs interactive output
- Addresses maintainer feedback on initial pull request

* Remove unused stackplot-codebyte-example.png image

This image was leftover from when the codebyte section was converted to a standard example. It's no longer referenced in the documentation and represents a duplicate output image for Example 1.

* Minor changes

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Author: AutoHmn13

content/matplotlib/concepts/pyplot/terms/stackplot/stackplot.md

@@ -0,0 +1,103 @@
+---
+Title: '.stackplot()'
+Description: 'Creates a stacked area plot to show how multiple datasets contribute cumulatively over time or categories.'
+Subjects:
+  - 'Data Science'
+  - 'Data Visualization'
+Tags:
+  - 'Charts'
+  - 'Matplotlib'
+  - 'Stacks'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+The **`.stackplot()`** method in Matplotlib creates stacked area plots (also known as stacked area charts) that display multiple datasets as vertically stacked areas. Each area represents the cumulative contribution of different categories to a total, making it ideal for visualizing proportional relationships as those relationships change over time.
+
+## Syntax
+
+```pseudo
+matplotlib.pyplot.stackplot(x, *args, labels=(), colors=None, hatch=None, baseline='zero', data=None, **kwargs)
+```
+
+**Parameters:**
+
+- `x`: Array-like. The x-coordinates of the data points.
+- `*args`: One or more array-like sequences representing the y-values for each stack layer.
+- `labels`: List of strings, optional. Labels for each stack layer (used in legends).
+- `colors`: List of colors or color specifications for each stack layer.
+- `hatch`: String or sequence, optional. Hatching patterns applied to the filled areas.
+- `baseline`: String, defines the baseline for stacking:
+  - `'zero'` (default): Stack from y = 0.
+  - `'sym'`: Symmetric stacking around zero.
+  - `'wiggle'`: Minimizes slope changes between layers.
+  - `'weighted_wiggle'`: Weighted version of the wiggle baseline.
+- `data`: Object with labeled data (e.g., dict or DataFrame). Optional data source.
+- `**kwargs`: Additional keyword arguments passed to `PolyCollection` (e.g., `alpha` for transparency).
+
+**Return value:**
+
+Returns a list of `PolyCollection` objects, one for each stack layer.
+
+## Example 1: Visualizing Monthly Sales by Category
+
+This example shows a stacked area chart of sales data across product categories over time:
+
+```py
+import matplotlib.pyplot as plt
+
+# Sample data
+months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
+electronics = [20, 25, 30, 28, 35, 40]
+clothing = [15, 18, 22, 25, 20, 30]
+books = [10, 12, 15, 18, 22, 25]
+
+# Create stacked area plot
+plt.stackplot(months, electronics, clothing, books,
+  labels=['Electronics', 'Clothing', 'Books'],
+  colors=['#ff9999', '#66b3ff', '#99ff99'],
+  alpha=0.8)
+
+plt.xlabel('Month')
+plt.ylabel('Sales (in thousands)')
+plt.title('Monthly Sales by Category')
+plt.legend(loc='upper left')
+plt.show()
+```
+
+This creates a stacked area chart where each colored area represents a product category's contribution to total sales:
+
+![Stackplot Example](https://raw.githubusercontent.com/Codecademy/docs/main/media/stackplot-example.png)
+
+## Example 2: Stacked Areas with Multiple Series
+
+This example demonstrates stacking multiple data series using numeric values:
+
+```py
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Create sample data
+x = [1, 2, 3, 4, 5]
+y1 = [1, 2, 3, 2, 1]
+y2 = [2, 3, 2, 4, 3]
+y3 = [1, 1, 2, 1, 2]
+
+# Create stackplot
+plt.stackplot(x, y1, y2, y3,
+  labels=['Series A', 'Series B', 'Series C'],
+  colors=['lightcoral', 'lightblue', 'lightgreen'],
+  alpha=0.8)
+
+plt.xlabel('X Values')
+plt.ylabel('Y Values')
+plt.title('Basic Stackplot Example')
+plt.legend(loc='upper left')
+plt.grid(True, alpha=0.3)
+plt.show()
+```
+
+This creates a basic stacked area plot with three data series, demonstrating the fundamental structure of stackplot visualizations:
+
+![Stackplot Example 2](https://raw.githubusercontent.com/Codecademy/docs/main/media/stackplot-example-2.png)