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Update doc/python/performance.md
Co-authored-by: Emily KL <4672118+emilykl@users.noreply.github.com>
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‎doc/python/performance.md‎

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@@ -46,7 +46,7 @@ Plotly Express natively supports [pandas, Polars, PyArrow, and Modin dataframes]
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*New in Plotly.py version 6*
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You can improve the performance of generating Plotly figures that use a large number of data points by using NumPy arrays and other objects that Plotly can convert to NumPy arrays, such as Pandas and Polars Series.
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You can improve the performance of generating Plotly figures that use a large number of data points by passing data as NumPy arrays, or in a format that Plotly can convert easily to NumPy arrays, such as Pandas and Polars Series or DataFrames. These formats will usually show better performance than passing data as a Python list.
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Plotly.py uses Plotly.js for rendering, which supports typed arrays. In Plotly.py, NumPy array and NumPy-convertible arrays are base64 encoded before being passed to Plotly.js for rendering.
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