# Let us import the required packages.
import warnings; warnings.filterwarnings('ignore')
import networkx as nx
from pyvis.network import Network
import matplotlib.pyplot as plt
import pandas as pd
 
 

# Let us create our very first, simple graph.
G = nx.Graph()
G.add_node('A')
G.add_node('B')
G.add_node('C')
G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'A')
 
 

# Let us see our basic graph as a picture.
nx.draw(G, with_labels=True, node_color='lightblue', font_weight='bold')
plt.show()
 
 

# Let us make the graph interactive with PyVis.
net = Network(height='350px', width='600px', notebook=True)
net.from_nx(G)
net.show('basic_graph.html')
 
 

# Data setup: Let us download airline passenger data.
df = pd.read_csv('https://raw.githubusercontent.com/jbrownlee/Datasets/master/airline-passengers.csv')
print('Shape:', df.shape)
df.head()
 
 

# Let us plot passenger counts to see trends.
plt.figure(figsize=(10,4))
plt.plot(df['Passengers'])
plt.title('Airline Passengers Over Time')
plt.xlabel('Month')
plt.ylabel('Passengers')
plt.grid()
plt.show()
 
 

# Let us suppose airports are nodes and The number of passengers is the edge value.
airports = ['JFK', 'LAX', 'ORD', 'DFW', 'ATL']
# We build a toy network, for learning.
G2 = nx.DiGraph()
G2.add_nodes_from(airports)
G2.add_edge('JFK', 'LAX', weight=103)
G2.add_edge('LAX', 'DFW', weight=95)
G2.add_edge('DFW', 'ATL', weight=87)
G2.add_edge('ORD', 'ATL', weight=83)
G2.add_edge('ATL', 'JFK', weight=110)
 
 

# Let us draw the airline route graph and show edge weights.
pos = nx.circular_layout(G2)
nx.draw(G2, pos, with_labels=True, node_color='lightgreen', node_size=1200, font_size=10, arrows=True)
edge_labels = nx.get_edge_attributes(G2, 'weight')
nx.draw_networkx_edge_labels(G2, pos, edge_labels=edge_labels)
plt.show()
 
 

# Let us make this routes network interactive with PyVis.
net2 = Network(height='350px', width='600px', directed=True, notebook=True)
for u, v, d in G2.edges(data=True):
    net2.add_edge(u, v, value=d['weight'], title=f'Passengers: {d['weight']}')
for n in G2.nodes() :
    net2.add_node(n, label=n, title=f'Airport: {n}')
net2.show('airline_routes.html')
 
 

# Let us print every airport and how many airports it connects to.
for airport in G2.nodes():
    print(f"{airport}: {G2.degree(airport)} connections")
 
 

# Let us find the shortest route from JFK to ATL.
shortest_path = nx.shortest_path(G2, source='JFK', target='ATL')
print('Shortest path from JFK to ATL:', shortest_path)
 
 

# Let us see all neighbors of ATL.
print('Neighbors of ATL:', list(G2.neighbors('ATL')))
 
 

# Let us filter routes with more than 100 passengers.
busy_routes = [(u, v) for u, v, d in G2.edges(data=True) if d['weight'] > 100]
print('Busy routes:', busy_routes)
 
 

# Let us show how to safely check if an airport exists before adding a route.
source = 'SEA'
target = 'JFK'
if source in G2.nodes() and target in G2.nodes():
    G2.add_edge(source, target, weight=77)
    print(f"Added a route from {source} to {target}.")
else:
    print(f"Cannot add route: one or both airports are missing.")
 
 

# Let us remove an airport from the graph.
airport_remove = 'SEA'
if airport_remove in G2:
    G2.remove_node(airport_remove)
    print(f"Removed {airport_remove} from the network.")
else:
    print(f"Airport {airport_remove} not found.")
 
 

# Let us get a list of all current airports and edges.
airports_list = list(G2.nodes())
routes_list = list(G2.edges(data=True))
print('Airports:', airports_list)
print('Routes:', routes_list)
 
 

# Mini-Project, Part 1: Build a social network graph from user input.
num_people = int(input('How many people are in your group? '))
people = []
for i in range(num_people):
    name = input(f'Enter name of person {i+1}: ')
    people.append(name)
socialG = nx.Graph()
socialG.add_nodes_from(people)
# Now add some connections.
num_connections = int(input('How many friendships? '))
for i in range(num_connections):
    p1 = input('Person 1: ')
    p2 = input('Person 2: ')
    socialG.add_edge(p1, p2)
print('People:', socialG.nodes())
print('Friendships:', socialG.edges())
 
 

# Mini-Project, Part 2: Visualize your social network.
pos = nx.spring_layout(socialG)
nx.draw(socialG, pos, with_labels=True, node_color='orange', node_size=1500, font_size=12)
plt.title('Your Social Network')
plt.show()
 
 

# Best practice: Give nodes and edges meaningful names and values.
# Always check if nodes and edges exist before changing them.
# Use visuals to debug your work and spot mistakes.
 

# Troubleshooting tip: If you get an error, check for typos in node names.
# If a node is missing, add it before adding an edge.
# Check that your packages are installed with the right spelling.
 

# Extra tip: Try adding more information to your graph.
# For example, add colors by group or size by passenger count.
# Visuals are more fun when they tell a story.
 

# Quick challenge: Add a new node and connect it to two others.
# Can you plot the network and see the update?