# Histogram plotting “AttributeError: max must be larger than min in range parameter.”

The following should do:

```import numpy as np
from numpy import array
import matplotlib.pyplot as plt

newH1 = H1[~np.isnan(H1)]
norm1 = np.apply_along_axis(func1d=lambda x: x/np.max(newH1), arr=newH1, axis=0)
nbins1 = 400
plt.hist(norm1, nbins1, color='purple', alpha=0.5)

plt.figure()

plt.subplot(111)
plt.hist(norm1, nbins1, color='purple', alpha=0.5)
plt.ylabel('Frequency', fontsize=20)

plt.show()

```

### Explanation:

The script above loads the data with the help of the `np.loadtxt` function and subsequently removes the rows that contain null values. The latter is done by indexing the imported array with the boolean array `~np.isnan(H1)`. Here, `np.isnan` finds the rows where the values are `null` or `nan` and the `~` sign negates that; changing the `True` values to `False`, and vice-versa. Once that’s done, it moves on to applying a function to each value of the new array. The function here is `lambda x: x/np.max(newH1)`; which basically divides each value of the array by the maximum value present in the new array.

The next step is to plot the histogram. We set the number of bins needed to 400 and use `plt.hist` to plot the histogram. There is also an added bonus to create a `figure` and then add a `subplot` to our `figure`. Subsequently, we use the `subplot` to draw the histogram.

I hope this proves useful.