TypeError: only length-1 arrays can be converted to Python scalars while plot showing

by

The error “only length-1 arrays can be converted to Python scalars” is raised when the function expects a single value but you pass an array instead.

np.int was an alias for the built-in int, which is deprecated in numpy v1.20. The argument for int should be a scalar and it does not accept array-like objects. In general, if you want to apply a function to each element of the array, you can use np.vectorize:

import numpy as np
import matplotlib.pyplot as plt

def f(x):
    return int(x)
f2 = np.vectorize(f)
x = np.arange(1, 15.1, 0.1)
plt.plot(x, f2(x))
plt.show()

You can skip the definition of f(x) and just pass the function int to the vectorize function: f2 = np.vectorize(int).

Note that np.vectorize is just a convenience function and basically a for loop. That will be inefficient over large arrays. Whenever you have the possibility, use truly vectorized functions or methods (like astype(int) as @FFT suggests).

More Related Contents:

  1. Is there a NumPy function to return the first index of something in an array?
  2. Understanding NumPy’s einsum
  3. How to calculate rolling / moving average using python + NumPy / SciPy?
  4. Saving a Numpy array as an image
  5. Intuition and idea behind reshaping 4D array to 2D array in NumPy
  6. Removing nan values from an array
  7. How to count the occurrence of certain item in an ndarray?
  8. How do I compute derivative using Numpy?
  9. binning data in python with scipy/numpy
  10. How do I count the occurrence of a certain item in an ndarray?
  11. Calculating Pearson correlation and significance in Python
  12. Numpy: Get random set of rows from 2D array
  13. ValueError: could not broadcast input array from shape (224,224,3) into shape (224,224)
  14. How can I release memory after creating matplotlib figures
  15. Sliding window of M-by-N shape numpy.ndarray
  16. numpy array concatenate: “ValueError: all the input arrays must have same number of dimensions”
  17. Precision lost while using read_csv in pandas
  18. reading v 7.3 mat file in python
  19. Creating a Confidence Ellipses in a sccatterplot using matplotlib
  20. Pandas in AWS lambda gives numpy error
  21. Pandas groupby with categories with redundant nan
  22. Shuffling NumPy array along a given axis
  23. How to display progress of scipy.optimize function?
  24. Easy way to test if each element in an numpy array lies between two values?
  25. Python numpy: cannot convert datetime64[ns] to datetime64[D] (to use with Numba)
  26. ImportError: No module named numpy on spark workers
  27. Automatic White Balancing with Grayworld assumption
  28. How to use sklearn fit_transform with pandas and return dataframe instead of numpy array?
  29. mean from pandas and numpy differ
  30. sparse 3d matrix/array in Python?

Leave a Comment