import ipywidgets
print(ipywidgets.__version__)

8.1.5

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from ipywidgets import interact, widgets
from IPython.display import clear_output
%matplotlib inline
%config InlineBackend.figure_format = 'retina'

names = [
    'Aarav', 'Aditi', 'Arjun', 'Ananya', 'Dhruv', 'Diya', 
    'Ishaan', 'Isha', 'Krishna', 'Kavya', 'Mira', 'Mihir',
    'Neha', 'Nikhil', 'Priya', 'Pranav', 'Riya', 'Rohan'
]

df = pd.DataFrame({
    'Name': names,
    'Age': np.random.randint(18, 23, len(names)),
    'Grade': np.random.randint(65, 100, len(names)),
    'Subject': np.random.choice(['Math', 'Physics', 'Chemistry'], len(names))
})

display(df)

	Name	Age	Grade	Subject
0	Aarav	20	69	Chemistry
1	Aditi	21	68	Physics
2	Arjun	19	72	Physics
3	Ananya	21	65	Chemistry
4	Dhruv	20	75	Physics
5	Diya	21	88	Physics
6	Ishaan	22	84	Math
7	Isha	18	99	Math
8	Krishna	19	77	Chemistry
9	Kavya	21	87	Physics
10	Mira	21	69	Chemistry
11	Mihir	19	77	Chemistry
12	Neha	18	66	Math
13	Nikhil	18	78	Physics
14	Priya	22	89	Physics
15	Pranav	20	99	Math
16	Riya	18	84	Math
17	Rohan	21	65	Physics

print("\nBasic Subsetting Examples:")
print("\nMath Students:")
math_students = df.query('Subject == "Math"')
math_students

Basic Subsetting Examples:

Math Students:

	Name	Age	Grade	Subject
6	Ishaan	22	84	Math
7	Isha	18	99	Math
12	Neha	18	66	Math
15	Pranav	20	99	Math
16	Riya	18	84	Math

print("\nHigh Performers (Grade > 85):")
high_performers = df.query("Grade > 85")
display(high_performers)

High Performers (Grade > 85):

	Name	Age	Grade	Subject
5	Diya	21	88	Physics
7	Isha	18	99	Math
9	Kavya	21	87	Physics
14	Priya	22	89	Physics
15	Pranav	20	99	Math

@interact
def filter_by_subject(subject=['All'] + list(df['Subject'].unique())):
    print(f"Showing {subject} students")
    """Simple filtering using @interact"""
    if subject == 'All':
        return df
    return df.query('Subject == @subject')

def filter_students(subject='All', min_grade=0):
    """More controlled filtering using interactive"""
    print(f"Showing {subject} students with grade >= {min_grade:0.1f}")
    filtered = df if subject == 'All' else df.query('Subject == @subject')
    out = filtered.query('Grade >= @min_grade')
    return out

filter_students()

Showing All students with grade >= 0.0

	Name	Age	Grade	Subject
0	Aarav	20	69	Chemistry
1	Aditi	21	68	Physics
2	Arjun	19	72	Physics
3	Ananya	21	65	Chemistry
4	Dhruv	20	75	Physics
5	Diya	21	88	Physics
6	Ishaan	22	84	Math
7	Isha	18	99	Math
8	Krishna	19	77	Chemistry
9	Kavya	21	87	Physics
10	Mira	21	69	Chemistry
11	Mihir	19	77	Chemistry
12	Neha	18	66	Math
13	Nikhil	18	78	Physics
14	Priya	22	89	Physics
15	Pranav	20	99	Math
16	Riya	18	84	Math
17	Rohan	21	65	Physics

student_filter_viz = interact(
    filter_students,
    subject = ['All'] + list(df['Subject'].unique()),
    min_grade=(0.0, 99.5, 5.0)
)

def plot_wave(freq=1):
    """Basic plotting function"""
    x = np.linspace(-1*np.pi, 1*np.pi, 500)
    
    plt.plot(x, np.sin(np.pi*2*freq*x), label='sin(x)')
    plt.plot(x, np.cos(np.pi*2*freq*x), label='cos(x)')
    plt.grid(True)
    plt.legend()
    plt.title('Trigonometric Functions')
    plt.show()

print("\nBasic Plot (Direct Function Call):")
plot_wave()

Basic Plot (Direct Function Call):

print("\nPlotting with @interact:")

@interact
def plot_wave_interact(freq=(1, 5, 1)):
    """Simple interactive plotting with @interact"""
    plot_wave(freq)

Plotting with @interact:

def plot_wave_advanced(func_type='sine', frequency=1, color='blue', show_grid=True):
    """Advanced plotting with more control"""
    fig, ax = plt.subplots(figsize=(6, 4))
    
    num_points = 1000
    
    x = np.linspace(-2 * np.pi, 2 * np.pi, num_points)
    
    if func_type == 'sine':
        y = np.sin(2 * np.pi * frequency * x)
        title = 'Sine Wave'
    elif func_type == 'cosine':
        y = np.cos(2 * np.pi * frequency * x)
        title = 'Cosine Wave'
    
    plt.plot(x, y, color=color, label=func_type)
    plt.title(title)
    plt.legend()
    plt.grid(show_grid)
    
    plt.show()

# Create the interact widget and store it in plot_viz
plot_viz = interact(
    plot_wave_advanced,
    func_type=widgets.RadioButtons(
        options=['sine', 'cosine'],
        description='Function:',
        style={'description_width': 'initial'},
        layout={'width': '200px'}
    ),
    frequency=widgets.FloatSlider(
        value=1,
        min=0.1,
        max=5,
        step=0.1,
        description='Frequency:',
        style={'description_width': 'initial'},
        layout={'width': '300px'}
    ),
    color=widgets.Dropdown(
        options=['blue', 'red', 'green', 'purple'],
        value='blue',
        description='Color:',
        style={'description_width': 'initial'},
        layout={'width': '200px'}
    ),
    show_grid=widgets.Checkbox(
        value=True,
        description='Show Grid',
        style={'description_width': 'initial'}
    )
)