How about print (x, y) at once. from matplotlib import pyplot as plt fig = plt.figure() ax = fig.add_subplot(111) A = -0.75, -0.25, 0, 0.25, 0.5, 0.75, 1.0 B = 0.73, 0.97, 1.0, 0.97, 0.88, 0.73, 0.54 ax.plot(A,B) for xy in zip(A, B): # <– ax.annotate(‘(%s, %s)’ % xy, xy=xy, textcoords=”data”) # <– ax.grid() plt.show()
I just wanted to post here another solution, a small library I wrote to implement this kind of things: https://github.com/Phlya/adjustText An example of the process can be seen here: Here is the example image: import matplotlib.pyplot as plt from adjustText import adjust_text import numpy as np together = [(0, 1.0, 0.4), (25, 1.0127692669427917, 0.41), (50, … Read more
How about print (x, y) at once. from matplotlib import pyplot as plt fig = plt.figure() ax = fig.add_subplot(111) A = -0.75, -0.25, 0, 0.25, 0.5, 0.75, 1.0 B = 0.73, 0.97, 1.0, 0.97, 0.88, 0.73, 0.54 ax.plot(A,B) for xy in zip(A, B): # <– ax.annotate(‘(%s, %s)’ % xy, xy=xy, textcoords=”data”) # <– ax.grid() plt.show()
hjust = 0 does what you want. hjust stands for horizontal justification, 0 will be left-justified, 0.5 will be centered, and 1 will be right-justified. qplot(mtcars$mpg) + annotate(geom = “text”, x = 30, y = 3, label = “Some text\nSome more text”, hjust = 0) See also vjust for vertical justification. In ggplot2, these arguments … Read more
I’m not aware of any plotting method which takes arrays or lists but you could use annotate() while iterating over the values in n. import matplotlib.pyplot as plt y = [2.56422, 3.77284, 3.52623, 3.51468, 3.02199] z = [0.15, 0.3, 0.45, 0.6, 0.75] n = [58, 651, 393, 203, 123] fig, ax = plt.subplots() ax.scatter(z, y) … Read more