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Diff for: doc/python/interactive-html-export.md

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@@ -41,7 +41,7 @@ Plotly figures are interactive when viewed in a web browser: you can hover over
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<!-- #region -->
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### Saving to an HTML file
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Any figure can be saved an HTML file using the `write_html` method. These HTML files can be opened in any web browser to access the fully interactive figure.
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Any figure can be saved as an HTML file using the `write_html` method. These HTML files can be opened in any web browser to access the fully interactive figure.
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```python
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import plotly.express as px

Diff for: doc/python/plotly-express.md

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Plotly Express provides [more than 30 functions for creating different types of figures](https://plotly.com/python-api-reference/plotly.express.html). The API for these functions was carefully designed to be as consistent and easy to learn as possible, making it easy to switch from a scatter plot to a bar chart to a histogram to a sunburst chart throughout a data exploration session. *Scroll down for a gallery of Plotly Express plots, each made in a single function call.*
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Here is a talk from the [SciPy 2021 conference](https://www.scipy2021.scipy.org/) that gives a good introduction to Plotly Express and [Dash](https://dash.plotly.com/):
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```python hide_code=true
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%%html
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<div align="center">
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<iframe width="560" height="315"
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src="https://www.youtube.com/embed/FpCgG85g2Hw"
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title="Data Visualization as The First and Last Mile of Data Science: Plotly Express and Dash | SciPy 2021"
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frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
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</div>
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```
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Plotly Express currently includes the following functions:
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* **Basics**: [`scatter`](/python/line-and-scatter/), [`line`](/python/line-charts/), [`area`](/python/filled-area-plots/), [`bar`](/python/bar-charts/), [`funnel`](/python/funnel-charts/), [`timeline`](https://plotly.com/python/gantt/)
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import plotly.express as px
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df = px.data.medals_long()
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fig = px.bar(df, x="medal", y="count", color="nation",
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fig = px.bar(df, x="medal", y="count", color="nation",
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pattern_shape="nation", pattern_shape_sequence=[".", "x", "+"])
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fig.show()
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```

Diff for: doc/python/troubleshooting.md

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```bash
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$ conda uninstall plotly
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$ pip remove plotly
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$ pip uninstall plotly
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```
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> Problems can also arise if you have a file named `plotly.py` in the same directory as the code you are executing.

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