Creating Beautiful Charts with Altair: Scatter, Line, Bar, Box, Area, and Pie Plots in Python

Altair is a Python library for data visualization that follows the Vega-Lite grammar and offers a clean, consistent API for creating attractive charts.

1. Scatter Plot

import altair as alt
from vega_datasets import data
# Load dataset
cars = data.cars()
# Create scatter plot
scatter_plot = alt.Chart(cars).mark_circle().encode(
    x='Horsepower',
    y='Miles_per_Gallon',
    color='Origin',
    tooltip=['Name', 'Horsepower', 'Miles_per_Gallon']
).properties(
    width=500,
    height=400
)
scatter_plot

2. Line Chart

import altair as alt
from vega_datasets import data
# Load dataset
stocks = data.stocks()
# Create line chart
line_plot = alt.Chart(stocks).mark_line().encode(
    x='date:T',
    y='price:Q',
    color='symbol:N'
).properties(
    width=600,
    height=400
)
line_plot

3. Bar Chart

import altair as alt
from vega_datasets import data
# Load dataset
barley = data.barley()
# Create bar chart
bar_plot = alt.Chart(barley).mark_bar().encode(
    x='variety:N',
    y='mean(yield):Q',
    color='site:N'
).properties(
    width=500,
    height=400
)
bar_plot

4. Box Plot

import altair as alt
from vega_datasets import data
# Load dataset
iris = data.iris()
# Create box plot
box_plot = alt.Chart(iris).mark_boxplot().encode(
    x='species:N',
    y='petalWidth:Q'
).properties(
    width=400,
    height=300
)
box_plot

5. Area Chart

import altair as alt
from vega_datasets import data
# Load dataset
stocks = data.stocks()
# Create area chart
area_plot = alt.Chart(stocks).mark_area().encode(
    x='date:T',
    y='price:Q',
    color='symbol:N'
).properties(
    width=600,
    height=400
)
area_plot

6. Column Chart (Duplicate of Bar Chart)

import altair as alt
from vega_datasets import data
# Load dataset
barley = data.barley()
# Create column chart
bar_plot = alt.Chart(barley).mark_bar().encode(
    x='variety:N',
    y='mean(yield):Q',
    color='site:N'
).properties(
    width=500,
    height=400
)
bar_plot

7. Pie Chart

import altair as alt
from vega_datasets import data
# Load dataset
cars = data.cars()
# Compute counts per manufacturer
manufacturers = cars['Origin'].value_counts().reset_index()
manufacturers.columns = ['Origin', 'Count']
# Create pie chart
pie_chart = alt.Chart(manufacturers).mark_arc().encode(
    theta='Count:Q',
    color='Origin:N',
    tooltip=['Origin', 'Count']
).properties(
    width=400,
    height=400
)
pie_chart

These examples show the basic methods for creating area, column, and pie charts with Altair. You can adjust and modify them according to your data and requirements. Altair offers rich visualization options, allowing customization of styles, colors, labels, and supports interactive exploration and dynamic updates for flexible and engaging data visualizations.

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