Guides

First Charts with matplotlib and seaborn (Line, Bar, Hist)

By Ravindra Bagale, Data Science & Data Analytics trainer · LinkedIn · Published: 1 October 2026 · Last updated: 3 October 2026

Read this guide in: English · मराठी · हिंदी

Your first bar, line and histogram charts turn tables into stories. Use matplotlib and seaborn. Shop example: Mumbai bar at 120, Pune at 70. No machine learning.

question → aggregate → bar/line/hist → label → one message

Language: English · मराठी · हिंदी

What do I need before this guide?

• A clean-enough DataFrame and a clear question.
• Packages: matplotlib, seaborn (from the install guide).
• Course: Line and hist.

Before and after (look at the tables first)

Before: numbers only. After: bar story — Mumbai taller at 120.

matplotlib vs seaborn (beginner map)

1. matplotlib — foundational plotting; Figure and Axes.
2. seaborn — faster statistical charts on pandas data.
3. Use both; do not fight religion wars in week one.

Course: Figure and Axes, seaborn vs matplotlib.

Bar chart — shop sales

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.DataFrame({"city": ["Mumbai", "Pune"], "sales": [120, 70]})

sns.barplot(data=df, x="city", y="sales")
plt.title("Shop sales by city")
plt.ylabel("Sales")
plt.show()

What you see: Mumbai bar higher. What you say: “Mumbai leads at 120 vs Pune 70.”

Course: countplot and barplot.

Line chart — daily trend (suppose)

Suppose daily Online sales: day1 40, day2 50, day3 100 (week total story later).

daily = pd.DataFrame({"day": [1, 2, 3], "sales": [40, 50, 100]})
plt.plot(daily["day"], daily["sales"], marker="o")
plt.title("Online sales trend")
plt.xlabel("Day")
plt.ylabel("Sales")
plt.show()

Why line: order in time matters. Bars compare categories; lines show movement.

Histogram — Instagram-like likes

likes = pd.Series([80, 40, 70, 30, 90, 20])
plt.hist(likes, bins=5)
plt.title("Distribution of post likes")
plt.xlabel("Likes")
plt.ylabel("Count of posts")
plt.show()

What you see: how likes spread — not who won. Different question → different chart.

Match chart to question

Course: Match chart to question.

Storytelling rules (classroom)

1. One main message per chart.
2. Label axes; include units if needed.
3. Avoid chart junk — neon grids that hide the point.
4. Aggregate before plotting when each row is a line item.

Course: Avoid chart junk, One-page manager story.

Axis formatting (simple)

1. Readable tick labels.
2. Rotate city names if they collide.
3. Start bar baselines at zero for sales counts unless you have a rare, documented reason.

Course: Axis formatting simple.

seaborn quick start extras

1. sns.countplot — count rows per category.
2. hue — split bars by channel.
3. boxplot — later, for spread vs outliers.

Course: seaborn quick start, hue and boxplot.

End-to-end mini story

1. Question: which city leads shop sales?
2. Table: Mumbai 120, Pune 70.
3. Chart: bar.
4. Sentence: “Mumbai leads this extract at 120.”
5. Optional next: filter Online only and redraw.