Advanced Visualization Techniques

import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np

fig, ax = plt.subplots(figsize=(10, 6))
ax.set_xlim(0, 12)
ax.set_ylim(0, 120000)

months = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
data   = [42000, 48000, 52000, 49000, 58000, 63000, 61000, 67000, 71000, 69000, 75000, 82000]
colors = ['#42A5F5'] * 12
colors[data.index(max(data))] = '#1565C0'

bars = ax.bar([], [], color='#42A5F5')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f'${x/1000:.0f}K'))
ax.set_title('Monthly Revenue Animation', fontsize=13, fontweight='bold')
ax.grid(True, axis='y', alpha=0.3)

def animate(i):
    ax.cla()
    ax.set_xlim(-0.5, 11.5)
    ax.set_ylim(0, 120000)
    c = [&#039;#1565C0' if j <= i and data[j] == max(data[:i+1]) else '#42A5F5' if j <= i else '#E0E0E0'
         for j in range(12)]
    b = ax.bar(range(12), data, color=c, width=0.7, edgecolor=&#039;white')
    ax.set_xticks(range(12))
    ax.set_xticklabels(months)
    ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f&#039;${x/1000:.0f}K'))
    ax.set_title(f&#039;Monthly Revenue — {months[i]} (${data[i]:,})', fontsize=13, fontweight='bold')
    ax.spines[&#039;top'].set_visible(False)
    ax.spines[&#039;right'].set_visible(False)
    ax.grid(True, axis=&#039;y', alpha=0.3)

ani = animation.FuncAnimation(fig, animate, frames=12, interval=600, repeat=True)
ani.save(&#039;revenue_animation.gif', writer='pillow', fps=2)  # pip install pillow
plt.show()

import plotly.express as px
import pandas as pd

# Product hierarchy data
hierarchy = pd.DataFrame({
    'Category': ['Electronics','Electronics','Electronics','Furniture','Furniture','Clothing','Clothing','Clothing'],
    'Product':  ['Laptop','Phone','Monitor','Desk','Chair','Jacket','Shirt','Shoes'],
    'Revenue':  [425000, 318000, 189000, 142000, 98000, 86000, 54000, 72000],
    'Margin':   [28, 22, 31, 18, 24, 45, 38, 42]
})

fig = px.treemap(hierarchy,
                  path=[px.Constant('All Products'), 'Category', 'Product'],
                  values='Revenue',
                  color='Margin',
                  color_continuous_scale='RdYlGn',
                  color_continuous_midpoint=30,
                  hover_data={'Revenue': ':$,.0f', 'Margin': ':.1f%'},
                  title='Product Revenue Treemap (Color = Margin %)')
fig.update_layout(template='plotly_white', height=500)
fig.show()

import plotly.graph_objects as go

# Customer journey flow
fig = go.Figure(go.Sankey(
    node=dict(
        pad=20, thickness=25, line=dict(color='black', width=0.5),
        label=['Website', 'Product Page', 'Cart', 'Checkout', 'Purchase',
               'Bounce', 'Abandoned Cart', 'Abandoned Checkout'],
        color=['#1565C0','#1976D2','#2196F3','#42A5F5','#4CAF50',
               '#EF5350','#FF7043','#FFCA28']
    ),
    link=dict(
        source=[0,0,1,1,2,2,3,3],   # From node indices
        target=[1,5,2,5,3,6,4,7],   # To node indices
        value= [45000,55000,32000,13000,20000,12000,15000,5000],
        color= ['rgba(25,118,210,0.4)','rgba(239,83,80,0.3)',
                'rgba(33,150,243,0.4)','rgba(239,83,80,0.3)',
                'rgba(66,165,245,0.4)','rgba(255,112,67,0.3)',
                'rgba(76,175,80,0.4)', 'rgba(255,202,40,0.3)']
    )
))
fig.update_layout(title='Customer Journey Flow Analysis', font_size=12,
                   template='plotly_white', height=450)
fig.show()

import matplotlib.pyplot as plt
import numpy as np

categories = ['Sales', 'Marketing', 'Tech', 'Finance', 'HR', 'Operations']
N = len(categories)
teams_data = {
    'Team Alpha': [85, 70, 92, 78, 65, 88],
    'Team Beta':  [72, 88, 76, 83, 90, 70],
    'Team Gamma': [90, 65, 85, 75, 72, 82]
}

angles = np.linspace(0, 2 * np.pi, N, endpoint=False).tolist()
angles += angles[:1]  # Close the polygon

fig, ax = plt.subplots(figsize=(8, 8), subplot_kw=dict(projection='polar'))
colors = ['#1565C0', '#2E7D32', '#E65100']

for (team, values), color in zip(teams_data.items(), colors):
    values_closed = values + values[:1]
    ax.plot(angles, values_closed, 'o-', linewidth=2, color=color, label=team)
    ax.fill(angles, values_closed, alpha=0.1, color=color)

ax.set_xticks(angles[:-1])
ax.set_xticklabels(categories, fontsize=11)
ax.set_ylim(0, 100)
ax.set_yticks([25, 50, 75, 100])
ax.set_yticklabels(['25', '50', '75', '100'], fontsize=8)
ax.set_title('Team Performance Radar', fontsize=14, fontweight='bold', pad=20)
ax.legend(loc='lower right', bbox_to_anchor=(1.3, 0))
plt.tight_layout()
plt.savefig('radar_chart.png', dpi=150, bbox_inches='tight')
plt.show()