| Concept | Syntax/Example | Explanation |
|---|---|---|
| Importing Matplotlib | import matplotlib.pyplot as plt | Import the pyplot module, the main interface for plotting with Matplotlib. |
| Basic Line Plot | plt.plot([1, 2, 3], [4, 5, 6]) plt.title('Line Plot') plt.show() |
Creates a basic line plot with x and y values. Use plt.show() to display the plot. |
| Adding Titles and Labels | plt.title('My Title') plt.xlabel('X-axis') plt.ylabel('Y-axis') |
Add a title and labels to the x and y axes. |
| Styling Line Plots | plt.plot(x, y, color='red', linestyle='--', marker='o', label='Data') plt.legend() |
Customize line color, style, marker, and add a legend. |
| Bar Plot | plt.bar(['A', 'B', 'C'], [10, 15, 7], color='blue') | Creates a vertical bar plot. |
| Horizontal Bar Plot | plt.barh(['A', 'B', 'C'], [10, 15, 7], color='green') | Creates a horizontal bar plot. |
| Scatter Plot | plt.scatter(x, y, color='orange', alpha=0.5, label='Points') plt.legend() |
Creates a scatter plot. Use alpha to control point transparency. |
| Histogram | plt.hist(data, bins=20, color='purple', edgecolor='black') | Plots a histogram to show data distribution. Use bins to control intervals. |
| Pie Chart | plt.pie([15, 30, 45], labels=['A', 'B', 'C'], autopct='%1.1f%%', startangle=140) | Creates a pie chart. Use autopct to show percentages. |
| Box Plot | plt.boxplot([data1, data2], labels=['Set 1', 'Set 2']) | Displays a box plot to visualize the spread and outliers of data. |
| Multiple Subplots | plt.subplot(2, 1, 1) plt.plot(x, y) plt.subplot(2, 1, 2) plt.bar(x, y) plt.tight_layout() |
Create multiple plots within a single figure using subplot(rows, cols, index). |
| Figure Size | plt.figure(figsize=(8, 6)) | Adjust the figure size using figsize. |
| Saving Figures | plt.savefig('plot.png', dpi=300) | Save the current figure to a file. Use dpi to specify resolution. |
| Logarithmic Scale | plt.xscale('log') plt.yscale('log') |
Set logarithmic scaling for the x or y axis. |
| Annotations | plt.annotate('Peak', xy=(2, 6), xytext=(3, 8), arrowprops=dict(facecolor='black', arrowstyle='->')) | Add annotations to highlight points of interest on the plot. |
| Grid | plt.grid(True, linestyle='--', color='gray') | Add a grid to the plot for better readability. |
| Legend | plt.plot(x, y, label='Data') plt.legend(loc='best') |
Add a legend to label different data series. Use loc to specify position. |
| Ticks | plt.xticks([0, 1, 2], ['Zero', 'One', 'Two']) plt.yticks(rotation=45) |
Customize x and y axis ticks and their labels. |
| 3D Plotting | from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.plot(x, y, z) |
Create 3D plots using the Axes3D module for advanced visualizations. |
| Adding Text | plt.text(1, 2, 'Point (1,2)', fontsize=12, color='red') | Add custom text to the plot at a specific location. |
| Horizontal and Vertical Lines | plt.axhline(y=0.5, color='blue', linestyle='--') plt.axvline(x=1.5, color='green', linestyle='--') |
Add horizontal and vertical reference lines to a plot. |
| Fill Between | plt.fill_between(x, y1, y2, color='yellow', alpha=0.3) | Fill the area between two curves or a curve and the axis. |
| Color Maps | plt.imshow(data, cmap='viridis', interpolation='none') | Display data as an image. Use cmap to choose a color map. |
| Tight Layout | plt.tight_layout() | Automatically adjust subplot parameters to give specified padding. |