dumbbell-plots.md

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jupytext kernelspec language_info plotly notebook_metadata_filter text_representation all extension format_name format_version jupytext_version .md markdown 1.3 1.14.1 display_name language name Python 3 (ipykernel) python python3 codemirror_mode file_extension mimetype name nbconvert_exporter pygments_lexer version name version ipython 3 .py text/x-python python python ipython3 3.8.0 description display_as language layout name order page_type permalink thumbnail How to create dumbbell plots in Python with Plotly. basic python base Dumbbell Plots 19 example_index python/dumbbell-plots/ thumbnail/dumbbell-plot.jpg

Basic Dumbbell Plot

Dumbbell plots are useful for demonstrating change between two sets of data points, for example, the population change for a selection of countries for two different years.

In this example, we compare life expectancy in 1952 with life expectancy in 2002 for countries in Europe.

import plotly.graph_objects as go
from plotly import data

import pandas as pd

df = data.gapminder()
df = df.loc[(df.continent == "Europe") & (df.year.isin([1952, 2002]))]

countries = (
    df.loc[(df.continent == "Europe") & (df.year.isin([2002]))]
    .sort_values(by=["lifeExp"], ascending=True)["country"]
    .unique()
)

data = {"line_x": [], "line_y": [], "1952": [], "2002": [], "colors": [], "years": [], "countries": []}

for country in countries:
    data["1952"].extend([df.loc[(df.year == 1952) & (df.country == country)]["lifeExp"].values[0]])
    data["2002"].extend([df.loc[(df.year == 2002) & (df.country == country)]["lifeExp"].values[0]])
    data["line_x"].extend(
        [
            df.loc[(df.year == 1952) & (df.country == country)]["lifeExp"].values[0],
            df.loc[(df.year == 2002) & (df.country == country)]["lifeExp"].values[0],
            None,
        ]
    )
    data["line_y"].extend([country, country, None]),

fig = go.Figure(
    data=[
        go.Scatter(
            x=data["line_x"],
            y=data["line_y"],
            mode="lines",
            showlegend=False,
            marker=dict(
                color="grey"
            )
        ),
        go.Scatter(
            x=data["1952"],
            y=countries,
            mode="markers",
            name="1952",
            marker=dict(
                color="green",
                size=10
            )

        ),
        go.Scatter(
            x=data["2002"],
            y=countries,
            mode="markers",
            name="2002",
            marker=dict(
                color="blue",
                size=10
            )
        ),
    ]
)

fig.update_layout(
    title=dict(text="Life Expectancy in Europe: 1952 and 2002"),
    height=1000,
    legend_itemclick=False
)

fig.show()

Dumbbell Plot with Arrow Markers

Note: The arrow, angleref, and standoff properties used on the marker in this example are new in 5.11

In this example, we add arrow markers to the plot. The first trace adds the lines connecting the data points and arrow markers. The second trace adds circle markers. On the first trace, we use standoff=8 to position the arrow marker back from the data point. For the arrow marker to point directly at the circle marker, this value should be half the circle marker size, which is hardcoded to 16 here.

import pandas as pd
import plotly.graph_objects as go
from plotly import data

df = data.gapminder()
df = df.loc[(df.continent == "Europe") & (df.year.isin([1952, 2002]))]

countries = (
    df.loc[(df.continent == "Europe") & (df.year.isin([2002]))]
    .sort_values(by=["lifeExp"], ascending=True)["country"]
    .unique()
)

data = {"line_x": [], "line_y": [], "1952": [], "2002": [], "colors": [], "years": [], "countries": []}

for country in countries:
    data["1952"].extend([df.loc[(df.year == 1952) & (df.country == country)]["lifeExp"].values[0]])
    data["2002"].extend([df.loc[(df.year == 2002) & (df.country == country)]["lifeExp"].values[0]])
    data["line_x"].extend(
        [
            df.loc[(df.year == 1952) & (df.country == country)]["lifeExp"].values[0],
            df.loc[(df.year == 2002) & (df.country == country)]["lifeExp"].values[0],
            None,
        ]
    )
    data["line_y"].extend([country, country, None]),

fig = go.Figure(
    data=[
        go.Scatter(
            x=data["line_x"],
            y=data["line_y"],
            mode="markers+lines",
            showlegend=False,
            marker=dict(
                symbol="arrow",
                color="black",
                size=16,
                angleref="previous",
                standoff=8
            )
        ),
        go.Scatter(
            x=data["1952"],
            y=countries,
            name="1952",
            mode="markers",
            marker=dict(
                color="silver",
                size=16,
            )
        ),
        go.Scatter(
            x=data["2002"],
            y=countries,
            name="2002",
            mode="markers",
            marker=dict(
                color="lightskyblue",
                size=16,
            ),
        ),
    ]
)

fig.update_layout(
    title=dict(text="Life Expectancy in Europe: 1952 and 2002"),
    height=1000,
    legend_itemclick=False
)


fig.show()