In [1]:

    

import pandas as pd
import seaborn as sns


    

In [2]:

    

df = sns.load_dataset("iris")
print(df.shape)


    

    




(150, 5)

In [3]:

    

print(df.sample())


    

    




     sepal_length  sepal_width  petal_length  petal_width    species
108           6.7          2.5           5.8          1.8  virginica

In [4]:

    

print(df.sample(n=3))


    

    




    sepal_length  sepal_width  petal_length  petal_width     species
3            4.6          3.1           1.5          0.2      setosa
1            4.9          3.0           1.4          0.2      setosa
96           5.7          2.9           4.2          1.3  versicolor

In [5]:

    

print(df.sample(n=3, random_state=0))


    

    




     sepal_length  sepal_width  petal_length  petal_width     species
114           5.8          2.8           5.1          2.4   virginica
62            6.0          2.2           4.0          1.0  versicolor
33            5.5          4.2           1.4          0.2      setosa

In [6]:

    

print(df.sample(frac=0.04))


    

    




     sepal_length  sepal_width  petal_length  petal_width     species
119           6.0          2.2           5.0          1.5   virginica
97            6.2          2.9           4.3          1.3  versicolor
46            5.1          3.8           1.6          0.2      setosa
137           6.4          3.1           5.5          1.8   virginica
56            6.3          3.3           4.7          1.6  versicolor
62            6.0          2.2           4.0          1.0  versicolor

In [7]:

    

print(df.head(3).sample(n=3, replace=True))


    

    




   sepal_length  sepal_width  petal_length  petal_width species
2           4.7          3.2           1.3          0.2  setosa
1           4.9          3.0           1.4          0.2  setosa
1           4.9          3.0           1.4          0.2  setosa

In [8]:

    

print(df.head(3).sample(n=5, replace=True))


    

    




   sepal_length  sepal_width  petal_length  petal_width species
1           4.9          3.0           1.4          0.2  setosa
0           5.1          3.5           1.4          0.2  setosa
1           4.9          3.0           1.4          0.2  setosa
0           5.1          3.5           1.4          0.2  setosa
0           5.1          3.5           1.4          0.2  setosa

In [9]:

    

print(df.head().sample(n=2, axis=1))


    

    




   sepal_width species
0          3.5  setosa
1          3.0  setosa
2          3.2  setosa
3          3.1  setosa
4          3.6  setosa