# Setup: import basic tools and filter warnings
import warnings; warnings.filterwarnings('ignore')
import pandas as pd
import plotly.express as px
 
 

# Data setup: Load the Airline Passengers dataset from a CSV file
url = 'https://raw.githubusercontent.com/jbrownlee/Datasets/master/airline-passengers.csv'
df = pd.read_csv(url)
print('Shape:', df.shape)
df.head()

# Line chart: Number of passengers over time
fig = px.line(df, x='Month', y='Passengers', title='Airline Passengers Over Time')
fig.show()

fig = px.line(df, x='Month', y='Passengers',
              title='Airline Passengers - Custom Style',
              markers=True,
              line_shape='linear',
              color_discrete_sequence=['red'])
fig.show()

fig = px.scatter(df, x='Month', y='Passengers', title='Passengers Per Month - Scatter Plot')
fig.show()

fig = px.bar(df.head(10), x='Month', y='Passengers', title='Passengers in First 10 Months')
fig.show()

# Adding labels and changing bar color
fig = px.bar(df.head(10), x='Month', y='Passengers',
            title='Colored Bars with Labels',
            color='Passengers',
            color_continuous_scale='Blues')
fig.update_traces(text=df.head(10)['Passengers'], textposition='outside')
fig.show()

# What month do you want to look at?
month = input("Type a month in the format YYYY-MM (for example, 1950-06): ")
row = df[df['Month'] == month]
if not row.empty:
    print('Passengers in', month, ':', int(row['Passengers']))
else:
    print('Sorry, that month was not found!')
    

# Show line and bar charts together with Plotly subplots
from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(rows=1, cols=2, subplot_titles=('Line Chart', 'Bar Chart'))
fig.add_trace(go.Scatter(x=df['Month'], y=df['Passengers'], name='Line', mode='lines+markers'), row=1, col=1)
fig.add_trace(go.Bar(x=df['Month'], y=df['Passengers'], name='Bar'), row=1, col=2)
fig.update_layout(title_text='Passengers: Two Chart Types')
fig.show()

# Try the Daily Minimum Temperatures dataset
weather_url = 'https://raw.githubusercontent.com/jbrownlee/Datasets/master/daily-min-temperatures.csv'
weather_df = pd.read_csv(weather_url)
print('Shape:', weather_df.shape)
weather_df.head()

# Plot temperatures over time
fig = px.line(weather_df, x='Date', y='Temp', title='Daily Minimum Temperatures')
fig.show()

# Mini-project: Compare summer and winter averages
weather_df['Date'] = pd.to_datetime(weather_df['Date'])
weather_df['Month'] = weather_df['Date'].dt.month
summer_temp = weather_df[weather_df['Month'].isin([12, 1, 2])]['Temp'].mean()
winter_temp = weather_df[weather_df['Month'].isin([6, 7, 8])]['Temp'].mean()
fig = px.bar(x=['Summer (Dec-Jan-Feb)', 'Winter (Jun-Jul-Aug)'], y=[summer_temp, winter_temp],
            labels={'x':'Season', 'y':'Average Min Temp'}, title='Average Temperatures by Season')
fig.show()

# Best practice: Save your favorite chart as an image file
fig = px.line(df, x='Month', y='Passengers', title='Line Chart Example')
fig.write_image('passengers_chart.png')
print('Chart saved as passengers_chart.png!')

# Troubleshooting: What if you see the chart area but no chart?
print('If your chart did not show up, check:')
print('- Did you use fig.show()?')
print('- Is the column name spelled correctly?')
print('- Did the dataset load without errors?')

# Tip: Add chart titles and axis labels for clarity
fig = px.bar(df.head(5), x='Month', y='Passengers', title='Chart with Custom Labels', labels={'Month': 'Year-Month', 'Passengers': 'Total People'})
fig.show()