Matplotlib.axes.Axes.format_coord() in Python

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

Matplotlib.axes.Axes.format_coord() Function

The Axes.format_coord() function in axes module of matplotlib library is used to return a format string formatting the x, y coordinates.

Syntax: Axes.format_coord(self, x, y)

Return value: This method return a format string formatting the x, y coordinates.

Below examples illustrate the matplotlib.axes.Axes.format_coord() function in matplotlib.axes:

Example-1:

# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.pyplot as plt
import numpy as np

# make an agg figure
fig, ax = plt.subplots()
ax.plot([1, 2, 3, 7], [1, 5, 6, 9])

def format_coord(x = 7, y = 9):
    col = int(x + 0.5)
    row = int(y + 0.5)
    if col >= 0 and col < 5 and row >= 0 and row < 5:
        z = row + col
        return 'x =% 1.4f, y =% 1.4f, z =% 1.4f' % (x, y, z)
    else:
        return 'x =% 1.4f, y =% 1.4f' % (x, y)

ax.format_coord = format_coord

fig.suptitle('matplotlib.axes.Axes.format_coord()\
 function Example', fontweight ="bold")
plt.show()

Output:

Example-2:

# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt

# Fixing random state for reproducibility
np.random.seed(19680801)


X = np.random.rand(15, 30)

fig, ax = plt.subplots()
ax.imshow(X)

val1, val2 = X.shape


def format_coord(x, y):
    col = int(x + 2)
    row = int(y - 2)
    if col >= 0 and col < val2 and row >= 0 and row < val1:
        z = X[row, col]
        return 'x =% 2.0f, y =% 2.0f, z =% 2.0f' % (x, y, z)
    else:
        return 'x =% 2.0f, y =% 2.0f' % (x, y)

ax.format_coord = format_coord

fig.suptitle('matplotlib.axes.Axes.format_coord() \
function Example', fontweight ="bold")
plt.show()

Output: