选择详情

此示例展示了一个连接两种数据视图的选择：左侧面板包含每个对象一个点，右侧面板包含每个对象一条线。点击点或线都会在两种数据视图中选择相应的对象。

挑战在于如何以 Altair 可以处理的方式表达这种分层数据。我们通过将数据合并为“长格式”数据帧，并聚合最终绘图的相同元数据来实现这一点。

方法语法

import altair as alt
import pandas as pd
import numpy as np

np.random.seed(0)

n_objects = 20
n_times = 50

# Create one (x, y) pair of metadata per object
locations = pd.DataFrame({
    'id': range(n_objects),
    'x': np.random.randn(n_objects),
    'y': np.random.randn(n_objects)
})

# Create a 50-element time-series for each object
timeseries = pd.DataFrame(np.random.randn(n_times, n_objects).cumsum(0),
                          columns=locations['id'],
                          index=pd.RangeIndex(0, n_times, name='time'))

# Melt the wide-form timeseries into a long-form view
timeseries = timeseries.reset_index().melt('time')

# Merge the (x, y) metadata into the long-form view
timeseries['id'] = timeseries['id'].astype(int)  # make merge not complain
data = pd.merge(timeseries, locations, on='id')

# Data is prepared, now make a chart

selector = alt.selection_point(fields=['id'])
color = (
    alt.when(selector)
    .then(alt.Color("id:O").legend(None))
    .otherwise(alt.value("lightgray"))
)

base = alt.Chart(data).properties(
    width=250,
    height=250
).add_params(selector)

points = base.mark_point(filled=True, size=200).encode(
    x='mean(x)',
    y='mean(y)',
    color=color,
)

line = base.mark_line().encode(
    x='time',
    y=alt.Y('value').scale(domain=(-15, 15)),
    color=alt.Color('id:O').legend(None)
).transform_filter(
    selector
)

points | line

属性语法

import altair as alt
import pandas as pd
import numpy as np

np.random.seed(0)

n_objects = 20
n_times = 50

# Create one (x, y) pair of metadata per object
locations = pd.DataFrame({
    'id': range(n_objects),
    'x': np.random.randn(n_objects),
    'y': np.random.randn(n_objects)
})

# Create a 50-element time-series for each object
timeseries = pd.DataFrame(np.random.randn(n_times, n_objects).cumsum(0),
                          columns=locations['id'],
                          index=pd.RangeIndex(0, n_times, name='time'))

# Melt the wide-form timeseries into a long-form view
timeseries = timeseries.reset_index().melt('time')

# Merge the (x, y) metadata into the long-form view
timeseries['id'] = timeseries['id'].astype(int)  # make merge not complain
data = pd.merge(timeseries, locations, on='id')

# Data is prepared, now make a chart

selector = alt.selection_point(fields=['id'])
color = (
    alt.when(selector)
    .then(alt.Color("id:O", legend=None))
    .otherwise(alt.value("lightgray"))
)

base = alt.Chart(data).properties(
    width=250,
    height=250
).add_params(selector)

points = base.mark_point(filled=True, size=200).encode(
    x='mean(x)',
    y='mean(y)',
    color=color,
)

line = base.mark_line().encode(
    x='time',
    y=alt.Y('value', scale=alt.Scale(domain=(-15, 15))),
    color=alt.Color('id:O', legend=None)
).transform_filter(
    selector
)

points | line