# Let\'s set up our environment
import warnings
warnings.filterwarnings("ignore")
 
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt

# These libraries will help us explore and plot our data

# Let\'s view Seaborn\'s built-in datasets
print(sns.get_dataset_names())

# Let\'s load the \"flights\" dataset
flights = sns.load_dataset("flights")
 
# Show the top 5 rows
flights.head()

# Show the shape: rows and columns
print("Shape:", flights.shape)
# Show quick summary of the dataset
print("\nInfo:")
flights.info()

# Plot how the number of passengers changes over time
plt.figure(figsize=(10,4))
sns.lineplot(data=flights, x="year", y="passengers")
plt.title("Passengers per Year")
plt.show()

# See all unique months in the dataset
print(flights["month"].unique())

# How many records for each month?
print(flights["month"].value_counts())

# Let\'s plot passengers per month for a year
data_1950 = flights[flights["year"]==1950]
sns.barplot(data=data_1950, x="month", y="passengers")
plt.title("Passengers per Month in 1950")
plt.show()

# What if we want to see change across all years by month?
pivot_data = flights.pivot(index="month", columns="year", values="passengers")
sns.heatmap(pivot_data, cmap="YlGnBu")
plt.title("Monthly Airline Passengers (1949-1960)")
plt.show()

# Check for any missing values in the dataset
print(flights.isnull().sum())

# Summary statistics for passengers
print(flights["passengers"].describe())

# Filter the data: find months with over 400 passengers
busy = flights[flights["passengers"]>400]
print(busy.head())

# Add a new column: Is Summer?
flights["is_summer"] = flights["month"].isin(["June","July","August"])
print(flights[["month", "is_summer"]].head(12))

# Mini-project: Visualize only the summer months
summer_flights = flights[flights["is_summer"]]
sns.lineplot(data=summer_flights, x="year", y="passengers", ci=None)
plt.title("Summer Passengers Over the Years")
plt.show()

# Save a chart to a file
plt.figure(figsize=(8,4))
sns.lineplot(data=flights, x="year", y="passengers")
plt.title("Passengers per Year")
plt.savefig("passengers_per_year.png")
plt.close()

# Troubleshooting: What if you make a typo?
try:
    sns.lineplot(data=flights, x="yeer", y="passengers")
except Exception as e:
    print("Error:", e)
    

# User input: Let\'s let you pick a year to visualize!
user_year = input("Type a year between 1949 and 1960: ")
selected = flights[flights["year"]==int(user_year)]
sns.barplot(data=selected, x="month", y="passengers")
plt.title(f"Airline Passengers in {user_year}")
plt.show()