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

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

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.

If you look at the call signature of `np.int`

, youll see that it accepts a single value, not an array. In general, if you want to apply a function that accepts a single element to every element in an array, you can use `np.vectorize`

:

```
import numpy as np
import matplotlib.pyplot as plt
def f(x):
return np.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 np.int to the vectorize function: `f2 = np.vectorize(np.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).

Use:

```
x.astype(int)
```

Here is the reference.

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

`dataframe[column].squeeze()`

should solve this. It basically changes the dataframe column to a list.