Q.(Program 4-1: Plotting Temperature against Height) In a city, the maximum temperature of a day is recorded for three consecutive days. Plot the temperature values against the given dates as a line chart, given: date = ["25/12", "26/12", "27/12"] and temp = [8.5, 10.5, 6.8].

This is a code task — you are asked to write a Python program using Matplotlib that produces a specific line chart.

import matplotlib.pyplot as plt

date = ["25/12", "26/12", "27/12"]
temp = [8.5, 10.5, 6.8]

plt.plot(date, temp, marker='o', linestyle='-', color='b')
plt.xlabel("Date")
plt.ylabel("Temperature (°C)")
plt.title("Maximum Temperature over Three Days")
plt.grid(True)
plt.show()

Key lines explained:

• plt.plot(date, temp, marker='o', ...) — draws the line chart. The marker='o' puts a visible dot at each data point so the three values are individually identifiable. Without a marker, only the line would appear.
• plt.xlabel and plt.ylabel — label the axes exactly as the data suggests: dates on x, temperature on y. The unit (°C) is added for clarity.
• plt.grid(True) — optional but helpful for reading values off the chart; exam answers often expect it.

What the chart shows: …

Why Matplotlib for this task

Matplotlib is the standard plotting library in Python for creating static, interactive, and animated visualizations. For a simple line chart showing how temperature changes over time, pyplot.plot() is the right tool — it connects data points with straight lines, making trends immediately visible. The pyplot module gives you a MATLAB-like interface that's intuitive for beginners.

The core idea: you have two sequences of equal length — dates (x-axis) and temperatures (y-axis). plt.plot(x, y) creates the line, and then you add labels, a title, and display it.

The complete solution

import matplotlib.pyplot as plt

# Given data
date = ["25/12", "26/12", "27/12"]
temp = [8.5, 10.5, 6.8]

# Create the line chart
plt.plot(date, temp, marker='o', linestyle='-', color='b', label='Max Temperature')

# Add labels and title
plt.xlabel('Date')
plt.ylabel('Temperature (°C)')
plt.title('Maximum Temperature over Three Days')

# Add a grid for readability
plt.grid(True, linestyle='--', alpha=0.7)

# Add legend
plt.legend()

# Display the plot
plt.show()

Key lines explained

• plt.plot(date, temp, marker='o', ...) — The marker='o' adds circular markers at each data point so the exact values are visible. Without markers, only the connecting line appears, which can make individual readings hard to spot.
• plt.xlabel() and plt.ylabel() — Always label your axes. The y-axis label includes the unit (°C) because a number without a unit is meaningless in science.
• plt.grid(True) — A grid helps the reader estimate values visually. The alpha=0.7 makes it subtle so it doesn't overpower the data.
• plt.legend() — Even with one line, a legend is good practice. It becomes essential when you add more series later.

What the output shows

The chart displays: …