# Tool to Generate 2D Data via Mouse Clicking

Often when I am learning new machine learning methods or experimenting with a data analysis algorithm I need to generate a series of 2D points. Teachers also do this often when making a lesson or tutorial.

In some cases I just create a function, add some noise, and plot it, but there are many times when I wish I could just click my mouse on a graph to generate points. For instance, when I want to generate a fairly complex relationship between x and y, it's a hassle to think of the right formulation to generate the points programmatically.

Does there exist a tool that will allow me to generate data points using my mouse, with an option to export to CSV (or other simple format)?

For example, I am currently learning how to use mutual information and entropy as a metric of dependence between variables. I'd like to see what happens when I have data that is clearly dependent but does not have a linear relationship, so I drew this image:

Now I just need a way to export the coordinates of the points to CSV. I realize this is a simple program and I could write my own, but surely someone has already done this and created a tool to do so? It could be a website, an .exe, Python source, or any other application.

I recently discovered this site: https://guoguibing.github.io/librec/datagen.html

Outputs list of points, and color ID (class) for each point.

Screenshot:

• In Python, one can convert the output from this website to a Pandas Dataframe using points = pandas.read_csv(io.BytesIO(pointsTxt), sep='\n', delimiter=',', names=['x','y','class']) Apr 7, 2017 at 18:16
• Sadly, this website is no longer online :( Dec 24, 2020 at 1:15
• ...but I found a working link and have updated the link above. Jan 6 at 19:28

In R:

First set up a blank plot with whatever x and y scale limits you need:

plot(NA, xlim=c(11,20),ylim=c(10,99))


Then click click click with mouse-button 1 and end with mouse-button 2 (probably):

pts = data.frame(locator(type="p"))


Then save as a CSV file:

write.csv(pts,"pts.csv",row.names=FALSE)


producing:

"x","y"
20.9461142167608,54.0921852908633
11.6463003491398,24.5409354249845
14.4239385175408,44.1769632963908
14.7755382856928,29.5957544809901
14.7931182741004,62.8409105801038


I found a simple Python solution, adapted from https://stackoverflow.com/q/25521120/1265192

This also works in a Jupyter Notebook, if desired.

import numpy as np
import matplotlib.pyplot as plt

%matplotlib qt

fig = plt.figure(figsize=(8,6))
ax.set_xlim(0,800)
ax.set_ylim(0,600)

plt.grid(True)

coords = []

def onclick(event):
x, y = event.xdata, event.ydata

print(f'{x:0.1f},{y:0.1f}')

global coords
coords.append((x, y))

ax.scatter([x], [y], c='b', s=150)
plt.draw()

cid = fig.canvas.mpl_connect('button_press_event', onclick)

fig.show()


The coordinates are stored in coords and also printed to the screen (but with 1 decimal place). One could save the coordinates to a file, but I just copy/paste the printed coordinates wherever I want them.

points = pd.read_csv('/content/pontos.csv', sep='\n', delimiter=',', names=['x','y','class'])