Code: Select all

```
import numpy as np
import matplotlib.pyplot as plot
arr = np.random.random((2000, 2)) * 2 - 1
Y = np.bitwise_xor(np.sign(arr[:, 0]).astype(int), np.sign(-arr[:, 1]).astype(int))
plot.scatter(arr[:, 0], arr[:, 1], c=Y)
plot.show()
```

- Mon Jul 20, 2020 11:43 pm
- Forum: Deep Learning Prerequisites: The Numpy Stack in Python
- Topic: Matplotlib exercise
- Replies:
**9** - Views:
**1047**

Short version

Code: Select all

```
import numpy as np
import matplotlib.pyplot as plot
arr = np.random.random((2000, 2)) * 2 - 1
Y = np.bitwise_xor(np.sign(arr[:, 0]).astype(int), np.sign(-arr[:, 1]).astype(int))
plot.scatter(arr[:, 0], arr[:, 1], c=Y)
plot.show()
```

- Mon Jul 20, 2020 11:33 pm
- Forum: Deep Learning Prerequisites: The Numpy Stack in Python
- Topic: Pandas Exercise
- Replies:
**4** - Views:
**2438**

Hi guys! I think I did it. Hopefully, solution will help someone. But does anybody know, is there any built-in way to generate donut distribution? Or at least to convert polar->cartesian->polar coordinates? import numpy as np import pandas as pd import matplotlib.pyplot as plot def create_donut(radi...