I have a scatter plot with about 19,000 data points. By visual inspection, I noticed some points for which I want to look at the corresponding numerical data from the data frame (basically a subset of the original data whose scatter plot we are looking at).

Is there a way to isolate the data corresponding to the point(s) [when the coordinates of the data points are not apparent from the figure] ?

Below is an example. How do I get data corresponding to the circled point on the plot?

enter image description here

Any response would be of great help.


  • 1
    $\begingroup$ How about interactive access to points? stackoverflow.com/questions/10655217/… It is easier than bokeh/ plotly, and if combined with annotate mentioned below you get your points of interest. $\endgroup$ Dec 19, 2018 at 7:01
  • $\begingroup$ Okay..this is interesting....thanks for sharing @MajidMortazavi. $\endgroup$
    – user62198
    Dec 19, 2018 at 16:16

1 Answer 1


You could also show the values for each point by using matplotlibs annotate command:

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(5)
y = np.random.randint(10, size=5)

fig = plt.figure()
ax = fig.add_subplot(111)
for i,j in zip(x,y):
    # xytext and textcoords are used to offset the labels
    ax.annotate("({},{})".format(i, j), xy=(i, j), xytext=(5, 5), textcoords='offset')

Annotated graph

  • $\begingroup$ Although helpful for small number of points, this may become unwieldy when there a lot of points involve. Having said that, I can't think of any other way to do it except may be using some fancy bokeh/ plotly type packages. $\endgroup$
    – user62198
    Dec 19, 2018 at 6:38
  • 1
    $\begingroup$ What you could do is an outlier detection: Add another value to x,y to determine if the point is an outlier and then only annotate the point if it is. $\endgroup$
    – oezguensi
    Dec 19, 2018 at 14:47
  • 1
    $\begingroup$ I was thinking of annotating the points with index values instead of (x,y) coordinates, but your solution is better. $\endgroup$
    – user62198
    Dec 19, 2018 at 16:13

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