application_vnd.jupyter.stderr_output_1.png
from pandas.plotting import andrews_curves

from sklearn.model_selection import train_test_split

from sklearn.preprocessing import StandardScaler, LabelEncoder, LabelBinarizer

import matplotlib.pyplot as plt

import pandas as pd

df_iris = pd.DataFrame(pd.read_csv('/kaggle/input/iris/Iris.csv'))

df_iris.groupby('Species').size()

X = df_iris.iloc[:, 1:5]
y = pd.DataFrame(df_iris.iloc[:, 5])
le = LabelEncoder()
y['Species'] = le.fit_transform(y['Species'])
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=0)

plt.figure(figsize=(15, 10))
andrews_curves(df_iris.drop('Id', axis=1), 'Species')
plt.title('Andrews Curves Plot', fontsize=20, fontweight='bold')
plt.legend(loc=1, prop={'size': 15}, frameon=True, facecolor='white', edgecolor='black')
plt.show()