Matplotlib is a visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
matplotlib.pyplot.tick_params()
matplotlib.pyplot.tick_params() is used to change the appearance of ticks, tick labels, and gridlines.
Syntax:
matplotlib.pyplot.tick_params(axis='both', **kwargs)
Parameters :
| Parameter | Value | Use |
|---|---|---|
| axis | {‘x’, ‘y’, ‘both’}, optional | Which axis to apply the parameters to. Default is ‘both’. |
| reset | bool, default: False | If True, set all parameters to defaults before processing other keyword arguments.. |
| which | {‘major’, ‘minor’, ‘both’} | Default is ‘major’; apply arguments to which ticks. |
| direction | {‘in’, ‘out’, ‘inout’} | Puts ticks inside the axes, outside the axes, or both. |
| length | float | Tick length in points. |
| width | float | Default is ‘major’; apply arguments to which ticks. |
| color | color | Tick color. |
| pad | float | Distance in points between tick and label. | labelsize | float or str | Tick label font size in points or as a string (e.g., ‘large’). | labelcolor | color | Tick label color. | colors | color | Tick color and label color. | zorder | float | Tick and label zorder. | bottom, top, left, right | bool | Whether to draw the respective ticks. | labelbottom, labeltop, labelleft, labelright | bool | Whether to draw the respective tick labels. | labelrotation | float | Tick label rotation | grid_color | color | Gridline color | grid_alpha | float | Transparency of gridlines: 0 (transparent) to 1 (opaque). | grid_linewidth | float | Width of gridlines in points. | grid_linestyle | str | Any valid Line2D line style spec. |
Example #1: Default plot
# importing libraries import matplotlib.pyplot as plt # values of x and y axes x = [i for i in range(5, 55, 5)] y = [1, 4, 3, 2, 7, 6, 9, 8, 10, 5] plt.plot(x, y) plt.xlabel('x') plt.ylabel('y') plt.show() |
Output :
Example #2:
# importing libraries import matplotlib.pyplot as plt from matplotlib.ticker import MultipleLocator, ScalarFormatter fig, ax = plt.subplots() ax.plot([0, 10, 20, 30], [0, 2, 1, 2]) ax.xaxis.set_minor_locator(MultipleLocator(1)) ax.xaxis.set_minor_formatter(ScalarFormatter()) ax.tick_params(axis ='both', which ='major', labelsize = 16, pad = 12, colors ='r') ax.tick_params(axis ='both', which ='minor', labelsize = 8, colors ='b') plt.show() |
Output:
