[Term Entry] Python Plotly - graph_objects: .Carpet() (#6404)

* [Term Entry] Python Plotly - graph_objects: .Carpet()

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Author: mamtawardhani

content/plotly/concepts/graph-objects/terms/carpet/carpet.md

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+---
+Title: '.Carpet()'
+Description: 'Creates carpet plots to visualize interactions between multiple variables in a two-dimensional plot.'
+Subjects:
+  - 'Data Science'
+  - 'Data Visualization'
+Tags:
+  - 'Data'
+  - 'Graphs'
+  - 'Plotly'
+  - 'Python'
+  - 'Variables'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+A **carpet plot** is a specialized visualization in Plotly that shows the interaction between two or more independent variables and one or more dependent variables in a two-dimensional plot. Carpet plots distinguish themselves from other plots by enabling more accurate interpolation of data points. They are created using the **`.Carpet()`** method of the `graph_objects` class.
+
+Carpet plots are particularly useful in engineering, scientific research, and data analysis where visualizing relationships between multiple variables is necessary. They can serve as a foundation for other traces like scattercarpet and contourcarpet, which can specify a carpet plot on which they lie.
+
+## Syntax
+
+```pseudo
+plotly.graph_objects.Carpet(a=None, aaxis=None, b=None, baxis=None, carpet=None, cheaterslope=None, color=None, x=None, y=None, ...)
+```
+
+**Parameters:**
+
+- `a`: An array containing values of the first parameter value
+- `b`: A two-dimensional array of y coordinates at each carpet point
+- `x`: A two-dimensional array of x coordinates at each carpet point. If omitted, the plot is a cheater plot with xaxis hidden by default
+- `y`: A two-dimensional array of y coordinates at each carpet point
+- `aaxis`: Sets the a-axis properties (can be provided as a dictionary)
+- `baxis`: Sets the b-axis properties (can be provided as a dictionary)
+- `carpet`: An identifier for this carpet, so that scattercarpet and contourcarpet traces can specify which carpet plot they lie on
+- `cheaterslope`: The shift applied to each successive row of data in creating a cheater plot (used when x is omitted)
+- `color`: Sets the default color for all elements
+
+**Return value:**
+
+Returns a carpet object that can be added to a figure created with [`plotly.graph_objects.Figure()`](https://www.codecademy.com/resources/docs/plotly/graph-objects/figure).
+
+## Example 1: Carpet Plot with `a` and `b` Parameters
+
+To create a comprehensive carpet plot, the syntax should include `a` and `b` parameter values which define the coordinate system:
+
+```py
+import plotly.graph_objects as go
+
+fig = go.Figure(go.Carpet(
+    a = [4, 4, 4, 4.5, 4.5, 4.5, 5, 5, 5, 6, 6, 6],
+    b = [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3],
+    y = [2, 3.5, 4, 3, 4.5, 5, 5.5, 6.5, 7.5, 8, 8.5, 10]
+))
+
+fig.show()
+```
+
+![A carpet plot generated out of the given a, b and y values](https://raw.githubusercontent.com/Codecademy/docs/main/media/carpet_output1.png)
+
+In this example, `a` and `b` arrays are included that define the coordinate system for our carpet plot. The values in these arrays correspond to the positions of the data points, creating a grid-like structure.
+
+## Example 2: Styling Carpet Plots for Better Visualization
+
+The carpet plot can be styled using axis properties to make it more visually appealing and easier to interpret:
+
+```py
+import plotly.graph_objects as go
+
+fig = go.Figure(go.Carpet(
+    a = [4, 4, 4, 4.5, 4.5, 4.5, 5, 5, 5, 6, 6, 6],
+    b = [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3],
+    y = [2, 3.5, 4, 3, 4.5, 5, 5.5, 6.5, 7.5, 8, 8.5, 10],
+    aaxis = dict(
+        tickprefix = 'a = ',
+        ticksuffix = 'm',
+        smoothing = 1,
+        minorgridcount = 9,
+    ),
+    baxis = dict(
+        tickprefix = 'b = ',
+        ticksuffix = 'Pa',
+        smoothing = 1,
+        minorgridcount = 9,
+    )
+))
+
+fig.update_layout(
+    plot_bgcolor = 'black',
+    paper_bgcolor = 'black',
+    font_color = 'white'
+)
+
+fig.show()
+```
+
+![A carpet plot styled using the properties](https://raw.githubusercontent.com/Codecademy/docs/main/media/carpet_output2.png)
+
+​This example enhances the carpet plot by adding custom styling to the `a` and `b` axes. Tick prefixes and suffixes are included to indicate units, the smoothing parameter is adjusted, and minor grid lines are added. Additionally, the background colors are modified for better contrast.
+
+## Example 3: Advanced Carpet Plot with Cheatertype and Custom Layout
+
+For more complex data relationships, different cheatertype values can be used and the layout can be adjusted to better represent the data:
+
+```py
+import plotly.graph_objects as go
+
+fig = go.Figure(go.Carpet(
+    a = [4, 4.5, 5, 6],
+    b = [1, 2, 3],
+    y = [[2, 3, 5.5, 8],
+         [3.5, 4.5, 6.5, 8.5],
+         [4, 5, 7.5, 10]],
+    cheaterslope = -5,
+    aaxis = dict(cheatertype = 'index'),
+    baxis = dict(cheatertype = 'value')
+))
+
+fig.show()
+```
+
+![A carpet plot created using a cheatertype value](https://raw.githubusercontent.com/Codecademy/docs/main/media/carpet_output3.png)
+
+This example demonstrates using a more advanced configuration where:
+
+1. The `y` parameter is provided as an array of arrays, representing a 2D grid
+2. We set `cheaterslope` to -5, which changes how rows are shifted
+3. The `cheatertype` property is set differently for the a and b axes
+
+The `cheatertype` parameter controls how axes are constructed. When set to `'index'`, the axis uses the index position of values, while 'value' uses the actual values.
+
+> **Note:** The layout of cheater plots depends upon the cheaterslope and axis cheatertype parameters, which can be adjusted to achieve the desired visual representation.
+
+Carpet plots provide a powerful way to visualize and analyze multi-dimensional data on a two-dimensional surface, especially for applications in engineering, physics, and advanced data analysis.