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GITBOOK-54: Plotly
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docs/visualization/5.-plotly.md

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# 5. Plotly
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<figure><img src="../.gitbook/assets/image (40).png" alt="" width="269"><figcaption></figcaption></figure>
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<figure><img src="../.gitbook/assets/image (257).png" alt="" width="515"><figcaption></figcaption></figure>
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1. Select _**Plotly**_ in the _**Visualization**_ category.
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<figure><img src="../.gitbook/assets/image (258).png" alt="" width="563"><figcaption></figcaption></figure>
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<figure><img src="../.gitbook/assets/image (41).png" alt=""><figcaption></figcaption></figure>
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2. _**Import Package**_: Install the necessary packages(Plotly) for code execution.
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3. _**Import Library**_: Import the libraries required for code execution.
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4. _**Preview**_: Preview the chart that will be generated.
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5. _**Code**_ _**View**_: Preview the code that will be generated.
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6. _**Run**_: Execute the code.
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2. _**Import Package**_: Install the package you need to run your code (Plotly).
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3. _**Import Library**_: Import the libraries needed to run your code.
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4. _**Preview**_: You can preview the graph that will be generated.
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5. _**Code View**_: You can preview the code that will be generated.
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6. _**Run**_: Print and run the code.
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### Data
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<figure><img src="../.gitbook/assets/image (259).png" alt="" width="563"><figcaption></figcaption></figure>
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<figure><img src="../.gitbook/assets/image (42).png" alt=""><figcaption></figcaption></figure>
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1. _**Chart Type**_: Select the type of chart.
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2. _**Data**_: Choose the data to be represented in the chart. You can also select a specific column of a DataFrame through the _**Funnel Icon**_. _**Set X and Y Individually**_ allows selecting data from different DataFrames.
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3. _**Axis Value**_: Select the data to be used on each axis.
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&#x20; _**Values**_ (Pie Chart): Choose the data to represent the size of each section in a Pie Chart.
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&#x20; _**Names**_ (Pie Chart): Choose the data to represent the names of each section in a Pie Chart.
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&#x20; _**Parents**_ (Sunburst): The Sunburst chart represents hierarchical data in a circular form. Select the data indicating which parent section each segment belongs to.
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4. _**Color**_: Enable the use of color and choose the color of the graph.
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5. _**Sort**_: Specify the order of categories on the X-axis. Descending arranges columns from the highest to the lowest amount of data.
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6. _**User Option**_: Optionally provide additional desired options.
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1. _**Chart Type**_: Select the type of graph.
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2. _**Data**_: Select the data you want to graph. To select a specific column, use the funnel icon. If you want to set X and Y separately, check _**Set X and Y individually**._
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3. _**Axis Value**_: Select the data you want to use for each axis.
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1. _**Values (Pie Chart)**_: Select the data to represent the size of each section.
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2. _**Names (Pie Chart)**_: Select the data to represent the name of each section.
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3. _**Parents (Sunburst)**_: _Sunburst_ charts represent hierarchical data in a circle; select the data that represents the parent section to which each segment belongs.
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4. _**Color**_: You can check _**Use Color** to_ enable the use of color and select a color for the graph.
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5. _**Sort**_: Specify the order of the categories on the X-axis. Descending order sorts from the column with the most data to the column with the least.
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6. _**User Option**_: You can add additional code beyond the functionality provided by Visual Python.
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***
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### Info
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<figure><img src="../.gitbook/assets/image (260).png" alt="" width="563"><figcaption></figcaption></figure>
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<figure><img src="../.gitbook/assets/image (44).png" alt=""><figcaption></figcaption></figure>
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1. _**Title**_: Specify the title of the chart.
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2. _**Label**_: Specify the names of each axis.
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1. _**Title**_: Set a title for the figure.
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2. _**Label**_: Set a name for each axis.
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***
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### Code
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<figure><img src="../.gitbook/assets/image (261).png" alt="" width="563"><figcaption></figcaption></figure>
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<figure><img src="../.gitbook/assets/image (45).png" alt=""><figcaption></figcaption></figure>
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1. Additional code beyond the functionalities provided by Visual Python can be added.
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1. You can add additional code beyond what Visual Python provides.
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