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.set_ylabel() Function
The Axes.set_ylabel() function in axes module of matplotlib library is used to set the label for the y-axis.
Syntax: Axes.set_ylabel(self, xlabel, fontdict=None, labelpad=None, **kwargs)
Parameters: This method accepts the following parameters.
- ylabel : This parameter is the label text.
- labelpad : This parameter is the spacing in points from the axes bounding box including ticks and tick labels.
Returns:This method does not returns any value.
Below examples illustrate the matplotlib.axes.Axes.set_ylabel() function in matplotlib.axes:
Example 1:
import matplotlib.pyplot as plt
import numpy as np
t = np.arange( 0.01 , 5.0 , 0.01 )
s = np.exp( - t)
fig, ax = plt.subplots()
ax.plot(t, s) ax.set_ylim( 1 , 0 )
ax.set_ylabel( 'Display Y-axis Label' ,
fontweight = 'bold' )
ax.grid( True )
ax.set_title('matplotlib.axes.Axes.set_ylabel() \ Examples\n ', fontsize = 14, fontweight =' bold')
plt.show() |
Output:
Example 2:
#Implementation of matplotlib function import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
with cbook.get_sample_data( 'goog.npz' ) as datafile:
price_data = np.load(datafile)[ 'price_data' ].view(np.recarray)
# get the most recent 250 # trading days price_data = price_data[ - 250 :]
delta1 = np.diff(price_data.adj_close) / price_data.adj_close[: - 1 ]
volume = ( 25 * price_data.volume[: - 2 ] / price_data.volume[ 0 ]) * * ( 2.2 )
close = ( 0.03 * price_data.close[: - 2 ] / 0.03 * price_data. open [: - 2 ]) * * 2
fig, ax = plt.subplots()
ax.scatter(delta1[: - 1 ], delta1[ 1 :],
c = close, s = volume,
alpha = 0.5 )
ax.set_ylabel(r 'Y-axis contains $\Delta_{i+1}$ values' ,
fontweight = 'bold' )
ax.grid( True )
fig.suptitle( 'matplotlib.axes.Axes.set_ylabel() Examples\n' ,
fontsize = 14 , fontweight = 'bold' )
plt.show() |
Output: