feature distrubution plotting

from matplotlib import pyplot as plt
import seaborn as sns
%matplotlib inline

def dist_plotting(dataset):
    numerical_set = []
    categorical_set = []
    last_col = dataset.columns[-1]
    for col in dataset:
        if np.issubdtype(dataset[col].dtype, np.number):
            numerical_set.append(col)
        else:
            categorical_set.append(col)

    count_categorical = len(categorical_set)
    count_numerical = len(numerical_set)
    for n in range(2, count_numerical):
        if n * n >= count_numerical:
            break

    fig = plt.figure(figsize=(18, 18))
    i = 1
    for col in numerical_set:
        axes = fig.add_subplot(n, n, i)
        if col == last_col:
            sns.histplot(x=dataset[col], kde=True, color='salmon')
        else:
            sns.histplot(x=dataset[col], kde=True)
        i += 1

    fig = plt.figure(figsize=(18, 18*n/2))
    i = 1
    for col in categorical_set:
        axes = fig.add_subplot(count_categorical, 1, i)
        sorted_counts = dataset[col].value_counts(
        ).sort_values(ascending=False).index
        if col == last_col:
            sns.countplot(data=dataset, y=col, palette="YlOrBr_r",
                          orient='h', order=sorted_counts)
        else:
            sns.countplot(data=dataset, y=col, palette="Blues_r",
                          orient='h', order=sorted_counts)
        i += 1