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The Plotly Express API in general offers the following features::
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***A single entry point into `plotly`**: just `import plotly.express as px` and get access to [all the plotting functions](https://plotly.com/python-api-reference/plotly.express.html), plus [built-in demo datasets under `px.data`](https://plotly.com/python-api-reference/generated/plotly.data.html#module-plotly.data) and [built-in color scales and sequences under `px.color`](https://plotly.com/python-api-reference/generated/plotly.colors.html#module-plotly.colors)
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***Sensible, Overrideable Defaults**: PX functions will infer sensible defaults wherever possible, and will always let you override them.
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***Flexible Input Formats**: PX functions [accept input in a variety of formats](https://plotly.com/python/px-arguments/), from `list`s and `dict`s to [long-form or wide-form Pandas `DataFrame`s](https://plotly.com/python/wide-form/) to [`numpy` arrays and `xarrays`](https://plotly.com/python/imshow/) to [GeoPandas `GeoDataFrames`](https://plotly.com/python/maps/).
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***Styling Control**: PX functions [read styling information from the default figure template](https://plotly.com/python/styling-plotly-express/), and support commonly-needed [cosmetic controls like `category_orders` and `color_discrete_map`](https://plotly.com/python/styling-plotly-express/) to precisely control categorical variables.
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***Figure Labelling**: PX functions label axes, legends and colorbars based in the input `DataFrame` or `xarray`, and provide [extra control with the `labels` argument](https://plotly.com/python/styling-plotly-express/).
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***Hover-labels**: PX functions populate the hover-label using the labels mentioned above, and provide [extra control with the `hover_name` and `hover_data` arguments](https://plotly.com/python/hover-text-and-formatting/).
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***Uniform Color Handling**: PX functions automatically switch between [continuous](https://plotly.com/python/colorscales/) and [categorical color](https://plotly.com/python/discrete-color/) based on the input type.
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***Faceting**: the 2D-cartesian plotting functions support [row, column and wrapped facetting with `facet_row`, `facet_col` and `facet_col_wrap` arguments](https://plotly.com/python/facet-plots/).
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***Flexible Input Formats**: PX functions [accept input in a variety of formats](/python/px-arguments/), from `list`s and `dict`s to [long-form or wide-form Pandas `DataFrame`s](/python/wide-form/) to [`numpy` arrays and `xarrays`](/python/imshow/) to [GeoPandas `GeoDataFrames`](/python/maps/).
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***Styling Control**: PX functions [read styling information from the default figure template](/python/styling-plotly-express/), and support commonly-needed [cosmetic controls like `category_orders` and `color_discrete_map`](/python/styling-plotly-express/) to precisely control categorical variables.
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***Figure Labelling**: PX functions label axes, legends and colorbars based in the input `DataFrame` or `xarray`, and provide [extra control with the `labels` argument](/python/styling-plotly-express/).
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***Hover-labels**: PX functions populate the hover-label using the labels mentioned above, and provide [extra control with the `hover_name` and `hover_data` arguments](/python/hover-text-and-formatting/).
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***Uniform Color Handling**: PX functions automatically switch between [continuous](/python/colorscales/) and [categorical color](/python/discrete-color/) based on the input type.
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***Faceting**: the 2D-cartesian plotting functions support [row, column and wrapped facetting with `facet_row`, `facet_col` and `facet_col_wrap` arguments](/python/facet-plots/).
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***Marginal Plots**: the 2D-cartesian plotting functions support marginal distribution plots with the `marginal`, `marginal_x` and `marginal_y` arguments.
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***A Pandas backend**: the 2D-cartesian plotting functions are available as [a Pandas plotting backend](https://plotly.com/python/pandas-backend/) so you can call them via `df.plot()`.
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***Trendlines**: `px.scatter` supports [built-in trendlines with accessible model output](https://plotly.com/python/linear-fits/).
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***Animations**: many PX functions support [simple animation support via the `animation_frame` and `animation_group` arguments](https://plotly.com/python/animations/).
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***A Pandas backend**: the 2D-cartesian plotting functions are available as [a Pandas plotting backend](/python/pandas-backend/) so you can call them via `df.plot()`.
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***Trendlines**: `px.scatter` supports [built-in trendlines with accessible model output](/python/linear-fits/).
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***Animations**: many PX functions support [simple animation support via the `animation_frame` and `animation_group` arguments](/python/animations/).
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### Gallery
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The following set of figures is just a sampling of what can be done with Plotly Express.
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#### Scatter, Line, Area and Bar Charts
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Read more about [scatter plots](https://plotly.com/python/line-and-scatter/) and [discrete color](https://plotly.com/python/discrete-color/).
Read more about [parallel coordinates](https://plotly.com/python/parallel-coordinates-plot/) and [parallel categories](https://plotly.com/python/parallel-categories-diagram/), as well as [continuous color](https://plotly.com/python/colorscales/).
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Read more about [parallel coordinates](/python/parallel-coordinates-plot/) and [parallel categories](/python/parallel-categories-diagram/), as well as [continuous color](/python/colorscales/).
Read more about [density heatmaps, also known as 2D histograms](https://plotly.com/python/2D-Histogram/).
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Read more about [density heatmaps, also known as 2D histograms](/python/2D-Histogram/).
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```python
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import plotly.express as px
@@ -337,7 +301,7 @@ fig.show()
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### Images and Heatmaps
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Read more about [heatmaps and images](https://plotly.com/python/imshow/).
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Read more about [heatmaps and images](/python/imshow/).
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```python
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import plotly.express as px
@@ -360,26 +324,25 @@ fig.show()
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#### Maps
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Read more about [tile maps](https://plotly.com/python/mapbox-layers/) and [point](https://plotly.com/python/scattermapbox/) and [line](https://plotly.com/python/lines-on-mapbox/) maps.
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Read more about [tile maps](/python/mapbox-layers/) and [point](/python/scattermapbox/) and [line](/python/lines-on-mapbox/) maps.
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