# First, silence all warnings to keep things tidy
import warnings
warnings.filterwarnings("ignore")

# Now import the essentials for plotting
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# Data setup
# Let us load a simple time series: airline-passengers data
url = "https://raw.githubusercontent.com/jbrownlee/Datasets/master/airline-passengers.csv"
df = pd.read_csv(url)

# Check the data shape and the top rows
print("Data shape:", df.shape)
df.head()

# Let us make a quick line plot of the data
plt.figure(figsize=(8,4))
sns.lineplot(x="Month", y="Passengers", data=df)
plt.title("Airline Passengers Over Time")
plt.show()

# Let us try a built-in Seaborn theme: 'darkgrid'
sns.set_theme(style="darkgrid")
plt.figure(figsize=(8,4))
sns.lineplot(x="Month", y="Passengers", data=df)
plt.title("With Darkgrid Theme")
plt.show()

# Quickly explore all standard themes
styles = ["white", "dark", "whitegrid", "darkgrid", "ticks"]
for s in styles:
    sns.set_style(s)
    plt.figure(figsize=(5,2))
    sns.lineplot(x="Month", y="Passengers", data=df)
    plt.title(f"Style: {s}")
    plt.tight_layout()
    plt.show()
    

# Use Seaborn's set_palette to change the color set
sns.set_theme(style="whitegrid")
palettes = ["deep", "muted", "pastel", "bright", "dark", "colorblind"]
for p in palettes:
    sns.set_palette(p)
    plt.figure(figsize=(6,2))
    sns.lineplot(x="Month", y="Passengers", data=df, linewidth=2)
    plt.title(f"Palette: {p}")
    plt.tight_layout()
    plt.show()
    

# You can even create a custom palette from any colors you like!
custom = ["#f54272", "#4268f5", "#42f5a7"]
sns.set_palette(custom)
plt.figure(figsize=(8,4))
sns.lineplot(x="Month", y="Passengers", data=df, linewidth=2)
plt.title("Line Plot with a Custom Color Palette")
plt.show()

# Change font type and scale for a larger, friendlier look
sns.set_theme(font="Comic Sans MS", font_scale=1.2)
plt.figure(figsize=(8,4))
sns.lineplot(x="Month", y="Passengers", data=df, linewidth=2)
plt.title("Comic Sans for a Fun Vibe")
plt.show()

# Remove chart spines for a minimalist look
sns.set_style("white")
sns.set_palette("pastel")
plt.figure(figsize=(8,4))
ax = sns.lineplot(x="Month", y="Passengers", data=df, linewidth=2)
sns.despine()
plt.title("Minimalist Style: No Chart Spines")
plt.show()

# Change label rotation and font for better reading
plt.figure(figsize=(8,4))
ax = sns.lineplot(x="Month", y="Passengers", data=df, linewidth=2, color="#4268f5")
ax.set_xticklabels(df["Month"], rotation=45, ha="right", fontsize=10)
ax.set_xlabel("Month", fontsize=12, fontweight="bold")
ax.set_ylabel("Passengers", fontsize=12, fontweight="bold")
plt.title("Angle and Style for Clear Axis Labels")
plt.tight_layout()
plt.show()

# Save your custom chart as a high-quality image
plt.figure(figsize=(8,4))
sns.set_theme(style="whitegrid", palette="deep")
sns.lineplot(x="Month", y="Passengers", data=df, linewidth=2)
plt.title("Ready to Share!")
plt.tight_layout()
plt.savefig("my_custom_passenger_plot.png", dpi=150)
plt.show()
print("Saved as my_custom_passenger_plot.png!")

# Mini-project: Compare two years with custom aesthetics
# Task: Highlight changes by picking two years and custom styling
df["Year"] = df["Month"].str[:4]
years = ["1958", "1959"]
plt.figure(figsize=(8,4))
sns.lineplot(
    x="Month", y="Passengers", hue="Year",
    data=df[df["Year"].isin(years)],
    palette=["#ff7675", "#00b894"], linewidth=2)
plt.title("Passengers: 1958 vs. 1959 (Custom Colors)")
plt.xticks(rotation=40)
plt.tight_layout()
plt.show()

# Extra tip: Use 'context' to tune charts for slides or papers
for context in ["notebook", "paper", "talk", "poster"]:
    sns.set_context(context)
    plt.figure(figsize=(6,2))
    sns.lineplot(x="Month", y="Passengers", data=df)
    plt.title(f"Seaborn context: {context}")
    plt.tight_layout()
    plt.show()
    

# Final challenge: Try your own theme ideas!
style = input("Enter a Seaborn style (white, dark, whitegrid, darkgrid, ticks): ")
palette = input("Enter a Seaborn palette (deep, muted, pastel, bright, dark, colorblind): ")
font = input("Enter your favorite font (try Arial, Times New Roman): ")
sns.set_theme(style=style, palette=palette, font=font)
plt.figure(figsize=(8,4))
sns.lineplot(x="Month", y="Passengers", data=df, linewidth=2)
plt.title(f"Your Custom Theme: {style}, {palette}, {font}")
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()