<jupyter_start><jupyter_text>Univariate,Bivariate and MultiVariate Analysis<jupyter_code>import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
df=pd.read_csv('https://raw.githubusercontent.com/uiuc-cse/data-fa14/gh-pages/data/iris.csv')
df.head()
df.species.unique()
df.shape<jupyter_output><empty_output><jupyter_text>Univariate<jupyter_code>df_setosa = df.loc[df['species'] == 'setosa']
df_versicolor = df.loc[df['species'] == 'versicolor']
df_virginica = df.loc[df['species'] == 'virginica']
plt.plot(df_setosa['petal_length'], np.zeros_like(df_setosa['petal_length']), 'o')
plt.plot(df_versicolor['petal_length'], np.zeros_like(df_versicolor['petal_length']), 'o')
plt.plot(df_virginica['petal_length'],np.zeros_like(df_virginica['petal_length']),'o')
plt.xlabel('petal_length')
plt.show()<jupyter_output><empty_output><jupyter_text>Bivariate<jupyter_code>## we can easily draw linear line between setosa and (versicolor+virginica)
sns.FacetGrid(df,hue="species",size=5).map(plt.scatter,"petal_length","sepal_width").add_legend();
plt.show()<jupyter_output>C:\Users\SHIVAM CHOUDHARY\anaconda3\lib\site-packages\seaborn\axisgrid.py:243: UserWarning: The `size` parameter has been renamed to `height`; please update your code.
  warnings.warn(msg, UserWarning)<jupyter_text>multivatiate<jupyter_code>sns.pairplot(df, hue='species', size=3)<jupyter_output>C:\Users\SHIVAM CHOUDHARY\anaconda3\lib\site-packages\seaborn\axisgrid.py:2071: UserWarning: The `size` parameter has been renamed to `height`; please update your code.
  warnings.warn(msg, UserWarning)
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