Python: Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 2 * np.pi, 100) y = np.sin(x)

# Simple line plot plt.plot(x, y, color='steelblue', linewidth=2, linestyle='--', label='sin(x)') plt.plot(x, np.cos(x), color='tomato', label='cos(x)') plt.xlabel('x') plt.ylabel('y') plt.title('Trigonometric Functions') plt.legend() plt.grid(True, alpha=0.3) plt.tight_layout() plt.savefig('trig.png', dpi=150, bbox_inches='tight') plt.show() ```

fig, axes = plt.subplots(2, 3, figsize=(15, 10))

# Scatter axes[0, 0].scatter(x, y, c=y, cmap='viridis', alpha=0.6, s=10) axes[0, 0].set_title('Scatter Plot')

# Bar chart categories = ['A', 'B', 'C', 'D'] values = [23, 45, 12, 67] axes[0, 1].bar(categories, values, color='steelblue', edgecolor='black') axes[0, 1].set_title('Bar Chart')

# Histogram data = np.random.normal(0, 1, 1000) axes[0, 2].hist(data, bins=30, color='orange', edgecolor='black', density=True) axes[0, 2].set_title('Histogram')

# Box plot axes[1, 0].boxplot([np.random.normal(0, 1, 100), np.random.normal(2, 1.5, 100)], labels=['Group A', 'Group B'])

# Heatmap matrix = np.random.rand(5, 5) im = axes[1, 1].imshow(matrix, cmap='Blues', aspect='auto') plt.colorbar(im, ax=axes[1, 1])

# Pie chart axes[1, 2].pie(values, labels=categories, autopct='%1.1f%%', startangle=90)

plt.tight_layout() plt.show() ```

# OOP interface full control
fig = plt.figure(figsize=(12, 8))

# Add subplots manually ax1 = fig.add_subplot(2, 2, 1) # 2x2 grid, position 1 ax2 = fig.add_axes([0.1, 0.1, 0.8, 0.35]) # [left, bottom, width, height]

# GridSpec for complex layouts from matplotlib.gridspec import GridSpec gs = GridSpec(2, 3, figure=fig, hspace=0.4, wspace=0.3) ax_main = fig.add_subplot(gs[0, :]) # span full first row ax_left = fig.add_subplot(gs[1, 0]) ax_right = fig.add_subplot(gs[1, 1:]) # span last two cols

ax_main.plot(x, y) ax_main.set_title('Main Plot', fontsize=14, fontweight='bold') ax_main.tick_params(labelsize=10) ax_main.spines['top'].set_visible(False) # clean look ax_main.spines['right'].set_visible(False) ```

# Use built-in styles
plt.style.use('seaborn-v0_8-whitegrid')  # clean, publication-ready
plt.style.use('dark_background')          # dark theme

# Custom colors colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728']

# Annotations fig, ax = plt.subplots() ax.plot(x, y) ax.annotate('Peak', xy=(np.pi/2, 1), xytext=(2, 0.7), arrowprops=dict(arrowstyle='->', color='red'), fontsize=12, color='red')

# Add text ax.text(0.05, 0.95, 'R² = 0.97', transform=ax.transAxes, fontsize=12, verticalalignment='top', bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))

# Twin axes (dual y-axis) ax2 = ax.twinx() ax2.plot(x, np.cos(x), color='red', linestyle='--') ax2.set_ylabel('cos(x)', color='red') ```

from matplotlib.animation import FuncAnimation

fig, ax = plt.subplots() ax.set_xlim(0, 2 * np.pi) ax.set_ylim(-1, 1) line, = ax.plot([], [], lw=2)

def init(): line.set_data([], []) return (line,)

def animate(frame): x = np.linspace(0, 2 * np.pi, 100) y = np.sin(x + frame / 10) line.set_data(x, y) return (line,)

ani = FuncAnimation(fig, animate, frames=100, init_func=init, interval=50, blit=True)

# Save as GIF or MP4 ani.save('wave.gif', writer='pillow', fps=30) ani.save('wave.mp4', writer='ffmpeg', fps=30) plt.show() ```

# Configure global rcParams
plt.rcParams.update({
    'font.family': 'sans-serif',
    'font.size': 11,
    'axes.labelsize': 12,
    'axes.titlesize': 13,
    'xtick.labelsize': 10,
    'ytick.labelsize': 10,
    'legend.fontsize': 10,
    'figure.dpi': 150,
    'axes.spines.top': False,
    'axes.spines.right': False,
    'axes.grid': True,
    'grid.alpha': 0.3,
})

# Use context manager for local changes with plt.rc_context({'axes.facecolor': 'lightyellow'}): fig, ax = plt.subplots() ax.plot(x, y)

# Export high-resolution fig.savefig('figure.pdf', dpi=300, bbox_inches='tight', format='pdf') fig.savefig('figure.svg', format='svg', bbox_inches='tight') # vector ```