The answer is to use matplotlib.pyplot to easily draw line charts and basic beautification. 1. Use plt.plot() to draw lines, supporting setting parameters such as color, linestyle, marker, etc.; 2. Add title and axis labels through plt.title(), plt.xlabel(), and plt.ylabel(); 3. Use plt.legend() to display legends, and define labels in plot; 4. Call plt.grid(True) to add grids to improve readability; 5. Finally, use plt.show() to display the image, or use plt.savefig() to save the image. Proficient in these steps, you can complete the basic drawing tasks.
Drawing is a very common requirement in data analysis and visualization, and Python's matplotlib is one of the most basic and commonly used drawing libraries. Below is a typical matplotlib.pyplot drawing example, showing how to draw a simple line chart and add common elements such as title, axis labels, legends, etc.
? Basic line chart example
import matplotlib.pyplot as plt # Sample data x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] # Draw a line chart plt.plot(x, y, label='y = 2x', color='blue', marker='o') # Add title and axis label plt.title('Simple Line Plot') plt.xlabel('X axis') plt.ylabel('Y axis') # Show legend plt.legend() # Show grid (optional) plt.grid(True) # Show the graphics plt.show()
? Key points description
-
plt.plot(): Draw a line chart, supporting setting line colors, styles, marking points, etc. -
label: used for legend annotation, used withplt.legend(). -
marker='o': Add circle marks to the data points for easy observation. -
plt.grid(True): add grid to improve readability. -
plt.show(): Must be called in the script to display the image (sometimes omitted in Jupyter).
?? Extension: Draw multiple lines (comparison image)
import matplotlib.pyplot as plt x = [1, 2, 3, 4, 5] y1 = [1, 4, 9, 16, 25] # y = x^2 y2 = [2, 4, 6, 8, 10] # y = 2x plt.plot(x, y1, label='y = x2', color='red', linestyle='-', marker='s') plt.plot(x, y2, label='y = 2x', color='blue', linestyle='--', marker='o') plt.title('Multiple Lines Plot') plt.xlabel('X axis') plt.ylabel('Y axis') plt.legend() plt.grid(True) plt.show()
? Tips
In Jupyter Notebook , adding
%matplotlib inlinecan make the image appear inline:%matplotlib inline
Support saving images:
plt.savefig('my_plot.png', dpi=300, bbox_inches='tight')
-
Common parameters:
-
color: color ('red', 'green', '#FF5733') -
linestyle: Line style ('-' solid line, '--' dotted line, ':' dotted line) -
marker: marking points ('o' circle, 's' square, '^' triangle, etc.)
-
Basically all that, not complicated but very practical. Proficient in plt.plot() and commonly used decorative functions, you can meet most basic drawing needs.
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