application_vnd.jupyter.stderr_output_1.png
from sklearn.preprocessing import LabelEncoder

import matplotlib.pyplot as plt

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

df = pd.read_csv('../input/mushroom-classification/mushrooms.csv')

from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()
df = df.apply(LabelEncoder().fit_transform)

f, ax = plt.subplots(1, 2, figsize=(15, 7))
df['class'].value_counts().plot.bar(ax=ax[0])
df['class'].value_counts().plot.pie(ax=ax[1], autopct='%.2f%%')