Line Charts and Trend Visualization

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# Sample: Monthly website traffic
months = pd.date_range('2024-01', periods=12, freq='MS')
traffic = [45000, 48000, 52000, 51000, 58000, 63000,
           61000, 65000, 70000, 68000, 72000, 78000]

fig, axes = plt.subplots(2, 2, figsize=(14, 10))

# Chart 1: Basic line
axes[0,0].plot(months, traffic, color='#2196F3', linewidth=2)
axes[0,0].set_title('Basic Line Chart')

# Chart 2: Styled with markers
axes[0,1].plot(months, traffic, 'o-', color='#E91E63', linewidth=2,
               markersize=8, markerfacecolor='white', markeredgewidth=2,
               markeredgecolor='#E91E63', label='Monthly Traffic')
axes[0,1].fill_between(months, traffic, alpha=0.1, color='#E91E63')
axes[0,1].set_title('Line with Markers and Fill')
axes[0,1].legend()

# Chart 3: With trend line
traffic_arr = np.array(traffic)
x_num = np.arange(len(traffic))
z = np.polyfit(x_num, traffic_arr, 1)
p = np.poly1d(z)
axes[1,0].plot(months, traffic, 'o-', color='#4CAF50', linewidth=2, label='Actual')
axes[1,0].plot(months, p(x_num), '--', color='#FF5722', linewidth=2, label=f'Trend (+{z[0]:.0f}/month)')
axes[1,0].set_title('With Linear Trend Line')
axes[1,0].legend()

# Chart 4: With annotations
axes[1,1].plot(months, traffic, 'o-', color='#9C27B0', linewidth=2)
peak_idx = traffic.index(max(traffic))
axes[1,1].annotate(f'Peak: {max(traffic):,}',
    xy=(months[peak_idx], max(traffic)),
    xytext=(months[peak_idx-3], max(traffic) + 3000),
    arrowprops=dict(arrowstyle='->', color='gray'))
axes[1,1].set_title('With Peak Annotation')

for ax in axes.flatten():
    ax.xaxis.set_major_formatter(plt.matplotlib.dates.DateFormatter('%b'))
    ax.grid(True, alpha=0.3)
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)

plt.suptitle('Line Chart Variations', fontsize=14, fontweight='bold')
plt.tight_layout()
plt.savefig('line_variations.png', dpi=150)
plt.show()

# Multi-product revenue comparison
products = {
    'Product A': [42000, 45000, 51000, 48000, 53000, 62000, 58000, 61000, 67000, 72000, 89000, 95000],
    'Product B': [28000, 31000, 35000, 33000, 38000, 42000, 39000, 43000, 47000, 51000, 60000, 68000],
    'Product C': [15000, 16000, 18000, 17000, 19000, 22000, 21000, 24000, 26000, 28000, 32000, 36000]
}

colors = ['#1565C0', '#2E7D32', '#E65100']
months_str = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']

fig, ax = plt.subplots(figsize=(12, 6))

for (product, values), color in zip(products.items(), colors):
    ax.plot(months_str, values, 'o-', color=color, linewidth=2.5,
            markersize=6, label=f'{product} (Dec: ${values[-1]:,.0f})')

# Add a target line
ax.axhline(y=50000, color='red', linestyle=':', linewidth=1.5, label='Target: $50K')

ax.set_title('Product Revenue Comparison — 2024', fontsize=14, fontweight='bold')
ax.set_xlabel('Month')
ax.set_ylabel('Revenue ($)')
ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f'${x/1000:.0f}K'))
ax.legend(loc='upper left', framealpha=0.8)
ax.grid(True, alpha=0.3)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.tight_layout()
plt.savefig('multi_line.png', dpi=150)
plt.show()

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

np.random.seed(42)
months = pd.date_range('2024-01', periods=12, freq='MS')
revenue = np.array([95000, 88000, 102000, 97000, 115000, 128000,
                    120000, 132000, 140000, 135000, 155000, 175000])
target = np.full(12, 120000)
ma3 = pd.Series(revenue).rolling(3).mean().values  # 3-month moving average

fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 10), sharex=True)

# Top: Revenue vs Target
ax1.fill_between(months, revenue, target,
                  where=(revenue >= target), alpha=0.2, color='green', label='Above target')
ax1.fill_between(months, revenue, target,
                  where=(revenue < target), alpha=0.2, color=&#039;red', label='Below target')
ax1.plot(months, revenue, &#039;o-', color='#1565C0', linewidth=2.5, markersize=8, label='Revenue')
ax1.plot(months, target, &#039;--', color='gray', linewidth=1.5, label='Target ($120K)')
ax1.plot(months, ma3, &#039;-', color='#FF9800', linewidth=2, alpha=0.8, label='3-Month MA')
ax1.set_title(&#039;Revenue vs Target with Moving Average', fontsize=13, fontweight='bold')
ax1.set_ylabel(&#039;Revenue ($)')
ax1.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f&#039;${x/1000:.0f}K'))
ax1.legend(loc=&#039;upper left')
ax1.grid(True, alpha=0.3)
ax1.spines[&#039;top'].set_visible(False)
ax1.spines[&#039;right'].set_visible(False)

# Bottom: Month-over-month change
mom_change = np.diff(revenue, prepend=revenue[0])
colors = [&#039;#4CAF50' if c >= 0 else '#F44336' for c in mom_change]
ax2.bar(months, mom_change, color=colors, alpha=0.8, width=20)
ax2.axhline(y=0, color=&#039;black', linewidth=0.8)
ax2.set_title(&#039;Month-over-Month Change', fontsize=13, fontweight='bold')
ax2.set_ylabel(&#039;Change ($)')
ax2.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f&#039;${x:+,.0f}'))
ax2.xaxis.set_major_formatter(plt.matplotlib.dates.DateFormatter(&#039;%b'))
ax2.grid(True, alpha=0.3)
ax2.spines[&#039;top'].set_visible(False)
ax2.spines[&#039;right'].set_visible(False)

total = revenue.sum()
avg = revenue.mean()
fig.suptitle(f&#039;Revenue Tracker 2024 | Total: ${total/1e6:.2f}M | Avg: ${avg:,.0f}/month',
              fontsize=14, fontweight=&#039;bold')
plt.tight_layout()
plt.savefig(&#039;revenue_tracker.png', dpi=150, bbox_inches='tight')
plt.show()