Altair使用学习笔记

Altair的使用 学习

# !pip install vega
# !pip install vega_datasets

import altair as alt
alt.renderers.enable('notebook')

RendererRegistry.enable('notebook')

# load a simple dataset as a pandas DataFrame
from vega_datasets import data
cars = data.cars()

alt.Chart(cars).mark_point().encode(
    x='Horsepower',
    y='Miles_per_Gallon',
    color='Origin',
).interactive()

<vega.vegalite.VegaLite at 0x7f5166171a20>

​

from vega_datasets import data

df = data.seattle_weather()
df.head()

alt.Chart(df).mark_point().encode(
    alt.X('temp_max', title='Maximum Daily Temperature (C)'),
    alt.Y('temp_range:Q', title='Daily Temperature Range (C)'),
    alt.Color('weather'),
    alt.Size('precipitation', scale=alt.Scale(range=[1, 200]))
).transform_calculate(
    "temp_range", "datum.temp_max - datum.temp_min"
).properties(
    width=600,
    height=400
).interactive()

<vega.vegalite.VegaLite at 0x7f5137660048>

​

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

np.random.seed(42)
source = pd.DataFrame(np.cumsum(np.random.randn(100, 3), 0).round(2),
                    columns=['A', 'B', 'C'], index=pd.RangeIndex(100, name='x'))
source = source.reset_index().melt('x', var_name='category', value_name='y')

# Create a selection that chooses the nearest point & selects based on x-value
nearest = alt.selection(type='single', nearest=True, on='mouseover',
                        fields=['x'], empty='none')

# The basic line
line = alt.Chart(source).mark_line(interpolate='basis').encode(
    x='x:Q',
    y='y:Q',
    color='category:N'
)

# Transparent selectors across the chart. This is what tells us
# the x-value of the cursor
selectors = alt.Chart(source).mark_point().encode(
    x='x:Q',
    opacity=alt.value(0),
).add_selection(
    nearest
)

# Draw points on the line, and highlight based on selection
points = line.mark_point().encode(
    opacity=alt.condition(nearest, alt.value(1), alt.value(0))
)

# Draw text labels near the points, and highlight based on selection
text = line.mark_text(align='left', dx=5, dy=-5).encode(
    text=alt.condition(nearest, 'y:Q', alt.value(' '))
)

# Draw a rule at the location of the selection
rules = alt.Chart(source).mark_rule(color='gray').encode(
    x='x:Q',
).transform_filter(
    nearest
)

# Put the five layers into a chart and bind the data
alt.layer(
    line, selectors, points, rules, text
).properties(
    width=600, height=300
)

<vega.vegalite.VegaLite at 0x7f51374ab2e8>

​

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