Plotly Express Basics

What is Plotly Express?

Plotly Express (px) is the easy way to use Plotly. One line = one chart.

Import

code.py

import plotly.express as px
import pandas as pd

Line Chart

code.py

df = pd.DataFrame({
    'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May'],
    'Sales': [100, 120, 115, 140, 160]
})

fig = px.line(df, x='Month', y='Sales', title='Monthly Sales')
fig.show()

Bar Chart

code.py

fig = px.bar(df, x='Month', y='Sales', title='Sales by Month')
fig.show()

Scatter Plot

code.py

df = pd.DataFrame({
    'Age': [25, 30, 35, 40, 45],
    'Salary': [40000, 50000, 60000, 70000, 80000]
})

fig = px.scatter(df, x='Age', y='Salary', title='Age vs Salary')
fig.show()

Color by Category

code.py

df = pd.DataFrame({
    'Age': [25, 30, 35, 40, 45, 50],
    'Salary': [40000, 50000, 60000, 70000, 80000, 90000],
    'Department': ['Sales', 'IT', 'Sales', 'IT', 'HR', 'HR']
})

fig = px.scatter(df, x='Age', y='Salary', color='Department')
fig.show()

Each department gets a different color!

Size by Value

code.py

df['Experience'] = [2, 5, 8, 12, 15, 20]

fig = px.scatter(df, x='Age', y='Salary',
                 color='Department', size='Experience')
fig.show()

Histogram

code.py

import numpy as np

data = np.random.normal(50, 10, 500)
fig = px.histogram(x=data, nbins=30, title='Distribution')
fig.show()

Box Plot

code.py

df = pd.DataFrame({
    'Department': ['Sales']*20 + ['IT']*20,
    'Salary': list(range(40000, 60000, 1000)) + list(range(60000, 80000, 1000))
})

fig = px.box(df, x='Department', y='Salary')
fig.show()

Pie Chart

code.py

df = pd.DataFrame({
    'Category': ['A', 'B', 'C', 'D'],
    'Value': [30, 25, 25, 20]
})

fig = px.pie(df, values='Value', names='Category', title='Distribution')
fig.show()

Common Parameters

Parameter	What it does
x	X-axis column
y	Y-axis column
color	Color by column
size	Size by column
title	Chart title
labels	Rename axes

Rename Axis Labels

code.py

fig = px.scatter(df, x='Age', y='Salary',
                 labels={'Age': 'Employee Age', 'Salary': 'Annual Salary'})
fig.show()

Key Points

px.line() for trends
px.bar() for comparisons
px.scatter() for relationships
px.histogram() for distributions
px.box() for spread
px.pie() for proportions
Use color and size for extra info

What's Next?

Learn to create interactive scatter plots with more features.