dataset link :- https://archive.ics.uci.edu/ml/datasets/Iris

Import all libraries

import pandas as pd
import seaborn as sns
import numpy as np 
import matplotlib.pyplot as plt

Creating DataFrame 

df = pd.read_csv("https://raw.githubusercontent.com/uiuc-cse/data-fa14/gh-pages/data/iris.csv")

df.head()
sepal_length sepal_width petal_length petal_width species
0 5.1 3.5 1.4 0.2 setosa
1 4.9 3.0 1.4 0.2 setosa
2 4.7 3.2 1.3 0.2 setosa
3 4.6 3.1 1.5 0.2 setosa
4 5.0 3.6 1.4 0.2 setosa 
df.shape

(150, 5)

Univariate Analysis 

df.loc[df['species']=='setosa']
sepal_length sepal_width petal_length petal_width species
0 5.1 3.5 1.4 0.2 setosa
1 4.9 3.0 1.4 0.2 setosa
2 4.7 3.2 1.3 0.2 setosa
3 4.6 3.1 1.5 0.2 setosa
4 5.0 3.6 1.4 0.2 setosa
5 5.4 3.9 1.7 0.4 setosa
6 4.6 3.4 1.4 0.3 setosa
7 5.0 3.4 1.5 0.2 setosa
8 4.4 2.9 1.4 0.2 setosa
9 4.9 3.1 1.5 0.1 setosa
10 5.4 3.7 1.5 0.2 setosa
11 4.8 3.4 1.6 0.2 setosa
12 4.8 3.0 1.4 0.1 setosa
13 4.3 3.0 1.1 0.1 setosa
14 5.8 4.0 1.2 0.2 setosa
15 5.7 4.4 1.5 0.4 setosa
16 5.4 3.9 1.3 0.4 setosa
17 5.1 3.5 1.4 0.3 setosa
18 5.7 3.8 1.7 0.3 setosa
19 5.1 3.8 1.5 0.3 setosa
20 5.4 3.4 1.7 0.2 setosa
21 5.1 3.7 1.5 0.4 setosa
22 4.6 3.6 1.0 0.2 setosa
23 5.1 3.3 1.7 0.5 setosa
24 4.8 3.4 1.9 0.2 setosa
25 5.0 3.0 1.6 0.2 setosa
26 5.0 3.4 1.6 0.4 setosa
27 5.2 3.5 1.5 0.2 setosa
28 5.2 3.4 1.4 0.2 setosa
29 4.7 3.2 1.6 0.2 setosa
30 4.8 3.1 1.6 0.2 setosa
31 5.4 3.4 1.5 0.4 setosa
32 5.2 4.1 1.5 0.1 setosa
33 5.5 4.2 1.4 0.2 setosa
34 4.9 3.1 1.5 0.1 setosa
35 5.0 3.2 1.2 0.2 setosa
36 5.5 3.5 1.3 0.2 setosa
37 4.9 3.1 1.5 0.1 setosa
38 4.4 3.0 1.3 0.2 setosa
39 5.1 3.4 1.5 0.2 setosa
40 5.0 3.5 1.3 0.3 setosa
41 4.5 2.3 1.3 0.3 setosa
42 4.4 3.2 1.3 0.2 setosa
43 5.0 3.5 1.6 0.6 setosa
44 5.1 3.8 1.9 0.4 setosa
45 4.8 3.0 1.4 0.3 setosa
46 5.1 3.8 1.6 0.2 setosa
47 4.6 3.2 1.4 0.2 setosa
48 5.3 3.7 1.5 0.2 setosa
49 5.0 3.3 1.4 0.2 setosa 
df_setosa=df.loc[df['species']=='setosa']
df_virginica=df.loc[df['species']=='virginica']
df_versicolor=df.loc[df['species']=='versicolor']

plt.plot(df_setosa['sepal_length'],np.zeros_like(df_setosa['sepal_length']),'o')
plt.plot(df_virginica['sepal_length'],np.zeros_like(df_virginica['sepal_length']),'o')
plt.plot(df_versicolor['sepal_length'],np.zeros_like(df_versicolor['sepal_length']),'o')
plt.xlabel("sepal_length")
plt.show()

Bivariate Analysis 

sns.FacetGrid(df,hue='species',size=5).map(plt.scatter,"petal_length","sepal_width").add_legend();
plt.show()

Multivariate Analysis 

sns.pairplot(df,hue='species',size=3)

C:\Users\mrsid\anaconda3\lib\site-packages\seaborn\axisgrid.py:2079: UserWarning: The `size` parameter has been renamed to `height`; please update your code.
  warnings.warn(msg, UserWarning)

<seaborn.axisgrid.PairGrid at 0x13024488808>