"""
Ranged Dot Plot
-----------------
This example shows a ranged dot plot to convey changing life expectancy for the five most populous countries (between 1955 and 2000).
"""
# category: other charts
import altair as alt
from vega_datasets import data

source = data.countries.url

chart = alt.Chart(
    data=source
).transform_filter(
    filter={"field": 'country',
            "oneOf": ["China", "India", "United States", "Indonesia", "Brazil"]}
).transform_filter(
    filter={'field': 'year',
            "oneOf": [1955, 2000]}
)

line = chart.mark_line(color='#db646f').encode(
    x='life_expect:Q',
    y='country:N',
    detail='country:N'
)
# Add points for life expectancy in 1955 & 2000
points = chart.mark_point(
    size=100,
    opacity=1,
    filled=True
).encode(
    x='life_expect:Q',
    y='country:N',
    color=alt.Color('year:O',
        scale=alt.Scale(
            domain=[1955, 2000],
            range=['#e6959c', '#911a24']
        )
    )
).interactive()

(line + points)

"""
Ranged Dot Plot
---------------
This example shows a ranged dot plot to convey changing life expectancy for the five most populous countries (between 1955 and 2000).
"""
# category: other charts
import altair as alt
from vega_datasets import data

source = data.countries.url

chart = alt.Chart(
    data=source
).transform_filter(
    filter={"field": 'country',
            "oneOf": ["China", "India", "United States", "Indonesia", "Brazil"]}
).transform_filter(
    filter={'field': 'year',
            "oneOf": [1955, 2000]}
)

line = chart.mark_line(color='#db646f').encode(
    x='life_expect:Q',
    y='country:N',
    detail='country:N'
)
# Add points for life expectancy in 1955 & 2000
points = chart.mark_point(
    size=100,
    opacity=1,
    filled=True
).encode(
    x='life_expect:Q',
    y='country:N',
    color=alt.Color('year:O',
        scale=alt.Scale(
            domain=[1955, 2000],
            range=['#e6959c', '#911a24']
        )
    )
).interactive()

(line + points)

Update ranged_dot_plot.py