| jupyter |
|
|---|
Plotly Express is a terse, consistent, high-level wrapper around Plotly.py for rapid data exploration and figure generation.
This notebook demonstrates various plotly_express features. Reference documentation and a step by step walkthrough notebook are also available.
You can also read our Medium announcement article for more information on this library.
importplotly_expressaspxprint(px.data.iris.__doc__)
iris=px.data.iris()tips=px.data.tips()
gapminder=px.data.gapminder()
election=px.data.election()
wind=px.data.wind()
carshare=px.data.carshare()px.scatter(iris, x="sepal_width", y="sepal_length")px.scatter(iris, x="sepal_width", y="sepal_length", color="species")px.scatter(iris, x="sepal_width", y="sepal_length", color="species", marginal_y="rug", marginal_x="histogram")px.scatter(iris, x="sepal_width", y="sepal_length", color="species", marginal_y="violin",
marginal_x="box", trendline="ols")iris["e"] =iris["sepal_width"]/100px.scatter(iris, x="sepal_width", y="sepal_length", color="species", error_x="e", error_y="e")deliris["e"]px.scatter(tips, x="total_bill", y="tip", facet_row="time", facet_col="day", color="smoker", trendline="ols",
category_orders={"day": ["Thur", "Fri", "Sat", "Sun"], "time": ["Lunch", "Dinner"]})px.scatter_matrix(iris)px.scatter_matrix(iris, dimensions=["sepal_width", "sepal_length", "petal_width", "petal_length"], color="species")px.parallel_coordinates(iris, color="species_id", labels={"species_id": "Species",
"sepal_width": "Sepal Width", "sepal_length": "Sepal Length",
"petal_width": "Petal Width", "petal_length": "Petal Length", },
color_continuous_scale=px.colors.diverging.Tealrose, color_continuous_midpoint=2)px.parallel_categories(tips, color="size", color_continuous_scale=px.colors.sequential.Inferno)px.scatter(tips, x="total_bill", y="tip", color="size", facet_col="sex",
color_continuous_scale=px.colors.sequential.Viridis, render_mode="webgl")px.scatter(gapminder.query("year==2007"), x="gdpPercap", y="lifeExp", size="pop", color="continent",
hover_name="country", log_x=True, size_max=60)px.scatter(gapminder, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country",
size="pop", color="continent", hover_name="country", facet_col="continent",
log_x=True, size_max=45, range_x=[100,100000], range_y=[25,90])px.line(gapminder, x="year", y="lifeExp", color="continent", line_group="country", hover_name="country",
line_shape="spline", render_mode="svg")px.area(gapminder, x="year", y="pop", color="continent", line_group="country")px.density_contour(iris, x="sepal_width", y="sepal_length")px.density_contour(iris, x="sepal_width", y="sepal_length", color="species", marginal_x="rug", marginal_y="histogram")px.density_heatmap(iris, x="sepal_width", y="sepal_length", marginal_x="rug", marginal_y="histogram")px.bar(tips, x="sex", y="total_bill", color="smoker", barmode="group")px.bar(tips, x="sex", y="total_bill", color="smoker", barmode="group", facet_row="time", facet_col="day",
category_orders={"day": ["Thur", "Fri", "Sat", "Sun"], "time": ["Lunch", "Dinner"]})px.histogram(tips, x="total_bill", y="tip", color="sex", marginal="rug", hover_data=tips.columns)px.histogram(tips, x="sex", y="tip", histfunc="avg", color="smoker", barmode="group",
facet_row="time", facet_col="day", category_orders={"day": ["Thur", "Fri", "Sat", "Sun"],
"time": ["Lunch", "Dinner"]})px.strip(tips, x="total_bill", y="time", orientation="h", color="smoker")px.box(tips, x="day", y="total_bill", color="smoker", notched=True)px.violin(tips, y="tip", x="smoker", color="sex", box=True, points="all", hover_data=tips.columns)px.scatter_ternary(election, a="Joly", b="Coderre", c="Bergeron", color="winner", size="total", hover_name="district",
size_max=15, color_discrete_map= {"Joly": "blue", "Bergeron": "green", "Coderre":"red"} )px.line_ternary(election, a="Joly", b="Coderre", c="Bergeron", color="winner", line_dash="winner")px.scatter_3d(election, x="Joly", y="Coderre", z="Bergeron", color="winner", size="total", hover_name="district",
symbol="result", color_discrete_map= {"Joly": "blue", "Bergeron": "green", "Coderre":"red"})px.line_3d(election, x="Joly", y="Coderre", z="Bergeron", color="winner", line_dash="winner")px.scatter_polar(wind, r="frequency", theta="direction", color="strength", symbol="strength",
color_discrete_sequence=px.colors.sequential.Plasma[-2::-1])px.line_polar(wind, r="frequency", theta="direction", color="strength", line_close=True,
color_discrete_sequence=px.colors.sequential.Plasma[-2::-1])px.bar_polar(wind, r="frequency", theta="direction", color="strength", template="plotly_dark",
color_discrete_sequence=px.colors.sequential.Plasma[-2::-1])px.set_mapbox_access_token(open(".mapbox_token").read())
px.scatter_mapbox(carshare, lat="centroid_lat", lon="centroid_lon", color="peak_hour", size="car_hours",
color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=10)px.set_mapbox_access_token(open(".mapbox_token").read())
px.line_mapbox(carshare, lat="centroid_lat", lon="centroid_lon", color="peak_hour")px.scatter_geo(gapminder, locations="iso_alpha", color="continent", hover_name="country", size="pop",
animation_frame="year", projection="natural earth")px.line_geo(gapminder.query("year==2007"), locations="iso_alpha", color="continent", projection="orthographic")px.choropleth(gapminder, locations="iso_alpha", color="lifeExp", hover_name="country", animation_frame="year",
color_continuous_scale=px.colors.sequential.Plasma, range_color=[20,80])px.colors.qualitative.swatches()px.colors.sequential.swatches()px.colors.diverging.swatches()px.colors.cyclical.swatches()px.colors.colorbrewer.swatches()px.colors.cmocean.swatches()px.colors.carto.swatches()Phew, you've made it this far! If you want to use Plotly Express yourself, just pip install plotly_express to install it and head on over to our reference documentation or just copy-paste from the examples above!
print(px.__version__)