Interactive Bar Charts

Basic Bar Chart

code.py

import plotly.express as px
import pandas as pd

df = pd.DataFrame({
    'Product': ['A', 'B', 'C', 'D'],
    'Sales': [100, 150, 80, 120]
})

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

Horizontal Bar Chart

code.py

fig = px.bar(df, x='Sales', y='Product', orientation='h')
fig.show()

Color by Category

code.py

df['Region'] = ['East', 'West', 'East', 'West']

fig = px.bar(df, x='Product', y='Sales', color='Region')
fig.show()

Grouped Bar Chart

code.py

df = pd.DataFrame({
    'Product': ['A', 'B', 'C', 'A', 'B', 'C'],
    'Sales': [100, 150, 80, 120, 140, 90],
    'Year': ['2023', '2023', '2023', '2024', '2024', '2024']
})

fig = px.bar(df, x='Product', y='Sales', color='Year', barmode='group')
fig.show()

Stacked Bar Chart

code.py

fig = px.bar(df, x='Product', y='Sales', color='Year', barmode='stack')
fig.show()

Add Text on Bars

code.py

fig = px.bar(df, x='Product', y='Sales', text='Sales')
fig.show()

Custom Text Position

code.py

fig = px.bar(df, x='Product', y='Sales', text='Sales')
fig.update_traces(textposition='outside')
fig.show()

Positions: 'inside', 'outside', 'auto', 'none'

Sort Bars

code.py

# Sort by value
df_sorted = df.sort_values('Sales', ascending=False)
fig = px.bar(df_sorted, x='Product', y='Sales')
fig.show()

Custom Colors

code.py

fig = px.bar(df, x='Product', y='Sales',
             color='Product',
             color_discrete_sequence=['red', 'blue', 'green', 'orange'])
fig.show()

Percentage Bar Chart

code.py

fig = px.bar(df, x='Product', y='Sales', color='Year',
             barmode='stack', barnorm='percent')
fig.show()

Shows percentages instead of values!

Faceted Bar Charts

code.py

df['Region'] = ['East', 'East', 'West', 'West', 'East', 'West']

fig = px.bar(df, x='Product', y='Sales', color='Year',
             facet_col='Region', barmode='group')
fig.show()

Complete Example

code.py

import plotly.express as px
import pandas as pd

df = pd.DataFrame({
    'Department': ['Sales', 'IT', 'HR', 'Marketing'],
    'Q1': [100, 80, 50, 70],
    'Q2': [120, 85, 55, 80],
    'Q3': [115, 90, 60, 75],
    'Q4': [140, 95, 65, 90]
})

# Reshape for Plotly
df_long = df.melt(id_vars='Department', var_name='Quarter', value_name='Revenue')

fig = px.bar(df_long, x='Department', y='Revenue',
             color='Quarter', barmode='group',
             title='Quarterly Revenue by Department',
             text='Revenue')

fig.update_traces(textposition='outside')
fig.show()

Key Points

px.bar() for bar charts
orientation='h' for horizontal
barmode='group' side by side
barmode='stack' stacked
text shows values on bars
barnorm='percent' for percentages
Use melt() to reshape data

What's Next?

Learn to create 3D visualizations with Plotly.