import matplotlib.pyplot as plt

table_data = [["Zane",7],
              ["Bob",10],
              ["Jim",37],
              ["Stacey",21]
              ]


# Prepare data for plotting
names = []
values = []

#'row' successively contains each row from the above list
for row in table_data:
    name = row[0] #Extracts Col 0 values with each iteration (Zane,Bone,Jim,Stacey)
    try:
        # row[1:] extracts from index 1 onward in the row i.e. 7,10,37,21
        numeric_values = [float(val) for val in row[1:]]
        total = sum(numeric_values)
        names.append(name)
        values.append(total)
    except ValueError:
        print(numeric_values,"is non-numeric")
        continue

# Plot scatter graph
plt.figure(figsize=(8, 6)) #size in inches
plt.scatter(names, values, color="blue", label="ScatterJT") #legend/data pt color, legend text
plt.plot(names, values, color="orange", label="LineJT", marker="X") #color: legend text, line
plt.title("Total Values by Name")
plt.xlabel("Name")
plt.ylabel("Total Value")
plt.legend() #Displays a legend with the text "ScatterJT", "LineJT"
plt.grid(True) #Adds lines to the horizontal & vertical grids
plt.tight_layout() #Adjust spacing so text doesn't overlap or get cut off



# ✅ Save to PDF BEFORE showing the plot
plt.savefig("friends.pdf", format="pdf", bbox_inches="tight", dpi=300)
print("Plot saved to friends.pdf")


"""
Co-Pilot explanation why this order is important
When you use plt.show() in Python, it displays the plot on your screen. But in some environments — especially IDEs like PyCharm, VS Code, or Jupyter notebooks — showing the plot can also finalize or reset it behind the scenes. That means:

The figure might be cleared or closed after it's shown.

If you try to save it after plt.show(), there might be nothing left to save — resulting in a blank or missing file.

🧠 Think of it like this:
Imagine you’re painting on a canvas.

plt.show() is like hanging the painting on the wall.

But in some studios, once it’s hung, the canvas gets wiped clean.

So if you try to save it afterward, you’re saving a blank canvas.
"""
# Now show the plot
plt.show()