import warnings
warnings.filterwarnings("ignore")

# We turn off warnings so your notebook stays clean.

# First steps with matplotlib
import matplotlib.pyplot as plt

# Let us make a simple line plot for practice.
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
plt.title("My First Plot")
plt.xlabel("X Axis")
plt.ylabel("Y Axis")
plt.show()

# Data setup
import pandas as pd

url = "https://raw.githubusercontent.com/jbrownlee/Datasets/master/daily-min-temperatures.csv"
data = pd.read_csv(url)
print("Data shape:", data.shape)
display(data.head())

# First look: plot the temperature time series
plt.figure(figsize=(10,4))
plt.plot(data["Date"], data["Temp"], color="royalblue")
plt.title("Daily Minimum Temperature (Melbourne, Australia)")
plt.xlabel("Date")
plt.ylabel("Temperature (Celsius)")
plt.tight_layout()
plt.show()

# Save a plot as PNG
plt.figure(figsize=(8,4))
plt.plot(data["Date"][:60], data["Temp"][:60], color="tomato")
plt.title("First 60 Days of Temperature")
plt.xlabel("Date")
plt.ylabel("Temperature (Celsius)")
plt.tight_layout()
plt.savefig("first_60_days.png")
plt.close()

# Save a plot as PDF (good for print)
plt.figure(figsize=(8,4))
plt.plot(data["Date"][120:180], data["Temp"][120:180], color="seagreen", marker="o")
plt.title("Days 121-180: Temperature")
plt.xlabel("Date")
plt.ylabel("Temperature (Celsius)")
plt.tight_layout()
plt.savefig("days_121_180.pdf")
plt.close()

# Increase image quality (dpi= dots per inch)
plt.figure(figsize=(10, 5))
plt.plot(data["Date"][:365], data["Temp"][:365], lw=2, color="mediumpurple")
plt.title("Year Overview (1981)")
plt.xlabel("Date")
plt.ylabel("Temperature (Celsius)")
plt.tight_layout()
plt.savefig("year_overview_highres.png", dpi=300)
plt.close()

# Save with a transparent background for slides
plt.figure(figsize=(8, 4))
plt.plot(data["Date"][:30], data["Temp"][:30], color="goldenrod", linewidth=3)
plt.title("First Month: Transparent Chart")
plt.xlabel("Date")
plt.ylabel("Temperature (Celsius)")
plt.tight_layout()
plt.savefig("first_month_transparent.png", transparent=True)
plt.close()

# Save specific figure only, not all plots
fig, ax = plt.subplots(figsize=(6,3))
ax.plot(data["Date"][20:40], data["Temp"][20:40], color="slateblue", marker="s")
ax.set_title("Dates 21-40")
ax.set_xlabel("Date")
ax.set_ylabel("Temperature (Celsius)")
fig.tight_layout()
fig.savefig("dates_21_40_custom.png")
plt.close(fig)  # Close only this plot, in case we have others.

# Add extra quality options: pad_inches, bbox_inches
plt.figure(figsize=(8,3))
plt.plot(data["Date"][10:60], data["Temp"][10:60], color="crimson")
plt.title("Zoomed In: Days 11-60")
plt.xlabel("Date", fontsize=12)
plt.ylabel("Temperature (Celsius)", fontsize=12)
plt.tight_layout()
plt.savefig("zoomed_in_cropped.png", bbox_inches="tight", pad_inches=0.2)
plt.close()

# Example of incorrect order
plt.figure()
plt.plot([1,2,3], [3,5,2])
plt.show()
plt.savefig("oops.png")  # This will not save your chart correctly!

# Accept file names from user
filename = input("What do you want to call your image file? (e.g. my_plot.png): ")
plt.figure(figsize=(6,3))
plt.plot(data["Date"][50:100], data["Temp"][50:100], color="navy")
plt.title("Days 51-100")
plt.tight_layout()
plt.savefig(filename)
plt.close()

# Save multiple plots easily in a loop
for i in range(3):
    plt.figure(figsize=(5,2))
    plt.plot(data["Date"][i*30:(i+1)*30], data["Temp"][i*30:(i+1)*30])
    plt.title(f"Month {i+1}")
    plt.tight_layout()
    fname = f"month_{i+1}.png"
    plt.savefig(fname, dpi=200)
    plt.close()
    

# Find the coldest week
coldest = data.nsmallest(7, "Temp")
plt.figure(figsize=(7,3))
plt.plot(coldest["Date"], coldest["Temp"], marker="o", linestyle="-", color="skyblue")
plt.title("Coldest 7 Days")
plt.xlabel("Date")
plt.ylabel("Temperature (Celsius)")
plt.grid(True, linestyle=":")
plt.tight_layout()
plt.savefig("coldest_week.png", dpi=250)
plt.close()

# Best practices: always set size, dpi, and save before plt.show()

plt.figure(figsize=(8,4), dpi=200)
plt.plot(data["Date"][300:330], data["Temp"][300:330], color="teal", marker="D")
plt.title("30 Days - Good Practice Example")
plt.xlabel("Date")
plt.ylabel("Temperature (Celsius)")
plt.tight_layout()
plt.savefig("good_practice_plot.png")
plt.show()

# Quick tip: Save in SVG for web or graphic design
plt.figure(figsize=(7,3))
plt.plot(data["Date"][200:240], data["Temp"][200:240], color="forestgreen")
plt.title("SVG Example Plot")
plt.xlabel("Date")
plt.ylabel("Temperature (Celsius)")
plt.tight_layout()
plt.savefig("svg_example.svg")
plt.close()