In [38]:

import altair as alt
import pandas as pd
from vega_datasets import data

In [3]:

df = pd.DataFrame({
    'Name': ['Big M*c', 'Lg Supreme Pizza', '12" Veggie Delite', "500ml Coke"],
    'Calories': [540, 350, 460, 210],
    'Fat': [28, 17, 6, 0],
    'Sugar': [9, 2, 12, 53]
})

In [16]:

alt.Chart(
    df,
    padding=20,
    background='#fff'
).mark_bar(
).encode(
    x='Name',
    y='Calories'
).properties(
    width=150,
    height=200
)

Out[16]:

In [12]:

alt.Chart(
    df,
    padding=20,
    background='#fff'
).mark_circle(
).encode(
    x='Fat',
    y='Sugar',
    size='Calories'
).properties(
    width=200,
    height=00
)

Out[12]:

In [37]:

base = alt.Chart(
    df,
).encode(
    x='Name'
).properties(
    width=150,
    height=200
)

cal = base.mark_bar(
).encode(
    y=alt.Y('Calories', axis=alt.Axis(orient='left')),
)

sugar = base.mark_line(
    color='orange'
).encode(
    y=alt.Y('Sugar', axis=alt.Axis(orient='right')),
)

(cal + sugar).resolve_scale(
    y='independent'
).configure(
    padding=20,
    background='#fff'
)

Out[37]:

In [39]:

source = data.movies.url

alt.Chart(
    source,
    padding=20,
    background='#fff'
).mark_bar(
).encode(
    alt.X("IMDB_Rating:Q", bin=True),
    y='count()',
)

Out[39]:

In [ ]:

source = data.movies.url

alt.Chart(
    source,
    padding=20,
    background='#fff'
).mark_bar(
).encode(
    alt.X("IMDB_Rating:Q", bin=True),
    y='average(Worldwide_Gross):Q',
)

In [ ]: