#5 Visualization & Project Work

 👍 — here’s a more detailed Module 6: Visualization & Project Work code set for your mini course.

This module focuses on Matplotlib, Seaborn, and optional GeoPandas for civil engineering visualization.

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🔹 1. Stress–Strain Curve (Lab Data Visualization)

import matplotlib.pyplot as plt

# Sample lab data
stress = [0, 50, 100, 150, 200, 250, 280]
strain = [0, 0.001, 0.002, 0.0032, 0.0042, 0.005, 0.006]

plt.figure(figsize=(6,4))
plt.plot(strain, stress, marker='o', color='b', label="Stress-Strain")
plt.xlabel("Strain")
plt.ylabel("Stress (N/mm²)")
plt.title("Stress-Strain Curve")
plt.grid(True)
plt.legend()
plt.show()

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🔹 2. Rainfall vs. Runoff Relationship

import numpy as np

rainfall = [20, 40, 60, 80, 100, 120]  # mm
runoff = [5, 15, 28, 40, 60, 85]       # mm

plt.figure(figsize=(6,4))
plt.scatter(rainfall, runoff, color='green', label="Observed Data")
plt.plot(rainfall, runoff, linestyle="--", color="black")
plt.xlabel("Rainfall (mm)")
plt.ylabel("Runoff (mm)")
plt.title("Rainfall vs Runoff")
plt.legend()
plt.grid(True)
plt.show()

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🔹 3. Bar Bending Schedule (BBS) Automation

import pandas as pd

# Example BBS data (Beam reinforcement)
data = {
    "Bar Mark": ["B1", "B2", "B3"],
    "Diameter (mm)": [12, 16, 20],
    "Length (m)": [6, 8, 12],
    "No. of Bars": [10, 8, 6]
}

bbs = pd.DataFrame(data)
bbs["Total Length (m)"] = bbs["Length (m)"] * bbs["No. of Bars"]
bbs["Weight (kg)"] = bbs["Total Length (m)"] * bbs["Diameter (mm)"] * 0.006165  # IS formula

print("Bar Bending Schedule:\n")
print(bbs)

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🔹 4. Traffic Flow Line Graph

time = np.arange(0, 11)  # minutes
vehicles = [50, 55, 60, 70, 85, 90, 95, 92, 88, 85, 80]

plt.figure(figsize=(6,4))
plt.plot(time, vehicles, marker="o", color="red")
plt.xlabel("Time (minutes)")
plt.ylabel("Number of Vehicles")
plt.title("Traffic Flow Simulation")
plt.grid(True)
plt.show()

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🔹 5. Optional: Plotting Survey/GIS Data (GeoPandas)

# Uncomment if geopandas is installed
# import geopandas as gpd
# world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# world[world.name == "India"].plot()
# plt.title("India Map - Example for Civil GIS Work")
# plt.show()

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✅ With these codes, students can visualize structural, hydrological, and transportation data.