Interactive Bar Charts
When to reach for a bar chart
Bars are the right shape when you’re comparing totals across separate categories — cities, products, days of the week — where each category stands on its own (no implied continuity between them, unlike a line chart). Bar length is one of the easiest visual encodings for people to compare accurately, which is why bar charts are the safest default for “which is bigger?” questions.
Basic bar chart
import pandas as pd
import plotly.express as px
df = pd.DataFrame({
"city": ["Pune", "Delhi", "Mumbai", "Bengaluru"],
"sales": [120, 180, 90, 160],
})
fig = px.bar(df, x="city", y="sales", title="Sales by city")
fig.show()import pandas as pd
import plotly.express as px
df = pd.DataFrame({
"city": ["Pune", "Delhi", "Mumbai", "Bengaluru"],
"sales": [120, 180, 90, 160],
})
fig = px.bar(df, x="city", y="sales", title="Sales by city")
fig.show()Sorted bars
import pandas as pd
import plotly.express as px
df = pd.DataFrame({
"city": ["Pune", "Delhi", "Mumbai", "Bengaluru"],
"sales": [120, 180, 90, 160],
}).sort_values("sales", ascending=False)
fig = px.bar(df, x="city", y="sales", title="Sales by city (sorted)")
fig.show()import pandas as pd
import plotly.express as px
df = pd.DataFrame({
"city": ["Pune", "Delhi", "Mumbai", "Bengaluru"],
"sales": [120, 180, 90, 160],
}).sort_values("sales", ascending=False)
fig = px.bar(df, x="city", y="sales", title="Sales by city (sorted)")
fig.show()Sorting by value (instead of leaving categories alphabetical) turns the chart into a ranking at a glance — the reader doesn’t have to hunt for the tallest bar.
Horizontal bar
import plotly.express as px
fig = px.bar(df, x="sales", y="city", orientation="h", title="Sales by city")
fig.show()import plotly.express as px
fig = px.bar(df, x="sales", y="city", orientation="h", title="Sales by city")
fig.show()Horizontal bars are handy when category labels are long — they read left-to-right instead of getting squeezed or rotated on the x-axis.
Tips
- Sort by value when ranking matters more than alphabetical order.
- Use
color=color=to add a second grouping dimension (e.g. region) alongside category. - Keep the y-axis starting at zero — a truncated axis makes bar-height comparisons misleading.
flowchart LR
A["Mouse moves over chart"] --> B{"Cursor over a bar's area?"}
B -- "Yes" --> C["Highlight that bar
show tooltip: category + value"]
B -- "No" --> D["No highlight"]
Next
Continue to: Interactive Scatter Plots for exploring relationships between two variables.
🧪 Try It Yourself
Exercise 1 – Build a Bar Chart
Exercise 2 – Sort Before Plotting
Exercise 3 – Go Horizontal
If this helped you, consider buying me a coffee ☕
Buy me a coffeeWas this page helpful?
Let us know how we did
