Chapter 61: Plot Graphics
Plot Graphics one of the most useful and beautiful skills in programming, data science, mathematics, science, business, journalism… basically almost every field that deals with numbers.
I’m going to explain this like your favorite patient teacher who wants you to really understand — not just memorize names or copy-paste code. We will go slowly, use everyday language, draw mental pictures, show real examples, and build everything from the very beginning.
No rushing. No assuming you already know something. Let’s start from zero.
What is “Plot Graphics” really?
Plot graphics (or just plotting) means turning numbers into pictures so that humans can quickly see patterns, trends, relationships, comparisons, or stories that are hidden inside raw lists of numbers.
In simple words:
You have boring lists/tables of numbers → You draw a visual (graph/chart/diagram) → Suddenly the story jumps out at you.
Real-life examples everyone understands:
| Situation | Numbers you have | What you plot (picture) | What the picture instantly tells you |
|---|---|---|---|
| Temperature every hour | 22, 21, 20, 21, 23, 26, 28, 27, 25 °C | Line going down then up | It was cold at night, hottest around 4–5 pm |
| Your phone screen time per day | Mon: 3.2 h, Tue: 4.1 h, Wed: 2.8 h, … | Bar chart (one bar per day) | You use phone most on weekends |
| Exam scores of 30 students | 45, 52, 68, 92, 77, 61, … | Histogram (bars showing how many got each range) | Most students scored 60–80, very few above 90 |
| Sales vs advertising spend | Month 1: ₹50k sales / ₹10k ads, Month 2: … | Scatter plot (dots) | More advertising → more sales (or maybe not!) |
| Population of countries | India 1.4B, China 1.4B, USA 340M, … | Bar chart sorted by size | India & China are much larger than everyone else |
Plot graphics = turning invisible number relationships into visible stories.
2. The two most important axes (X and Y) – forever rule
Every basic plot has two lines called axes:
- X-axis (horizontal line) → usually the cause, input, or thing you control Examples: time, age, price, month, advertising budget, distance traveled
- Y-axis (vertical line) → usually the effect, output, or thing that changes because of X Examples: temperature, height, sales, exam score, likes on post, fuel used
Forever rule (write this down):
X-axis = “What I change / what happens first” Y-axis = “What happens as a result”
Real examples:
- X = hours studied → Y = exam score
- X = day of week → Y = ice cream sales
- X = advertising money spent → Y = customers who bought
3. Most common types of plots (with everyday names)
| Everyday name | Technical name | What it looks like | Best used when… | Real-life example |
|---|---|---|---|---|
| Line graph / Line plot | Line chart | Dots connected by lines | Change over time, continuous data | Temperature over 24 hours, stock price over months |
| Bar chart / Column chart | Bar chart | Tall rectangles (bars) | Compare categories / groups | Sales by product, votes per candidate |
| Pie chart | Pie chart | Circle divided into slices | Show parts of a whole (percentages) | How you spend your day (sleep 30%, study 40%…) |
| Scatter plot / Dot plot | Scatter chart | Individual dots (usually no lines) | Show relationship between two measurements | Height vs weight of students, ad spend vs sales |
| Area chart | Area chart | Line + filled area underneath | Show total amount + change over time | Total money saved per month (cumulative) |
| Histogram | Histogram | Bars showing how many values fall in each range | Show distribution (how spread out values are) | Exam scores — how many students got 60–70, 70–80… |
4. Your very first plotting example (Python + Matplotlib)
Let’s start with the simplest possible plot — temperature during the morning.
|
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 |
# Step 1: Import the plotting tool (library) import matplotlib.pyplot as plt # Step 2: Prepare two lists of numbers (X and Y) hours = [6, 7, 8, 9, 10, 11, 12] # morning hours temps = [18, 19, 21, 24, 27, 29, 30] # temperature in °C # Step 3: Tell Python: "draw lines connecting these points" plt.plot(hours, temps, marker='o', color='orange', linewidth=2) # Step 4: Add titles & labels (so anyone understands the picture) plt.title("Temperature Rise in the Morning") plt.xlabel("Time (hours)") plt.ylabel("Temperature (°C)") # Step 5: Make it look nice + show it plt.grid(True) # add grid lines (optional but helpful) plt.show() # open the graph window |
What this code actually does (in everyday English):
- We have two lists: time (X) and temperature (Y)
- plt.plot() connects the points with orange lines and puts a dot (‘o’) at each hour
- We give the graph a title and label the axes → now anyone can read it
- plt.show() opens a window with the beautiful picture
What the picture tells you instantly: Temperature was ~18°C at 6 AM and rose steadily to 30°C by noon.
5. Your first 3 tiny practice tasks (do them tonight – 10–15 minutes)
Task 1 – Your phone usage Make two lists: hours = [8,9,10,11,12,13,14,15,16,17,18,19,20,21,22] usage = [0.2,0.4,0.8,1.5,2.1,2.8,3.4,3.9,3.5,2.9,2.4,1.8,1.2,0.7,0.3] # hours of screen time
Plot it → title = “My Phone Screen Time Today”
Task 2 – Bar chart of favorite subjects subjects = [‘Math’, ‘Science’, ‘English’, ‘History’, ‘Art’] likes = [18, 15, 22, 9, 12]
Use plt.bar(subjects, likes) instead of plt.plot
Task 3 – Make it pretty Take Task 1 again Add these lines before plt.show():
|
0 1 2 3 4 5 6 7 8 |
plt.plot(hours, usage, color='purple', marker='o', linestyle='--', linewidth=2.5) plt.grid(True, linestyle='--', alpha=0.7) plt.title("My Phone Usage Pattern", fontsize=16, fontweight='bold') |
Paste your code or screenshot here if you want feedback — I’ll review it like we’re sitting together improving it.
Which part still feels a bit unclear?
- What X-axis vs Y-axis really means in everyday language?
- Why we need titles and axis labels?
- Difference between line plot vs bar chart?
- How to read the “story” from the shape of the graph?
- Something else?
Tell me honestly — we’ll slow down and fix exactly the piece that’s confusing.
Plotting is one of the most powerful skills you can learn — once you master it, you can understand data, science, money, health, sports, social media… everything better and faster.
You’re doing great — let’s keep going! 🚀
