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import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.datasets import load_iris


iris = load_iris()
iris_df = pd.DataFrame(iris.data, columns=iris.feature_names)
iris_df['species'] = pd.Categorical.from_codes(iris.target, iris.target_names)


iris_df.shape

iris_df['species'].unique()

iris_df['species'].value_counts()

subset = iris_df[iris_df['species'] == 0]
subset.shape

iris_df['species'].value_counts()

import seaborn as sns
import matplotlib.pyplot as plt

sns.barplot(x='species', y='sepal length (cm)', data=iris_df)

plt.title('Species vs Sepal Length')
plt.show()

iris_df['species'].unique()

import seaborn as sns
import matplotlib.pyplot as plt

iris_df_reset = iris_df.reset_index(drop=True)

sns.lineplot(
    x=iris_df_reset.index,
    y='sepal length (cm)',
    hue='species',      
    data=iris_df_reset,
    marker='o'
)

plt.xlabel('Sample Index')
plt.ylabel('Sepal Length (cm)')
plt.title('Sepal Length for All Species')
plt.show()