Python | Pandas Series.sample()
Last Updated :
07 Feb, 2019
Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas
Series.sample()
function return a random sample of items from an axis of object. We can also use random_state for reproducibility.
Syntax: Series.sample(n=None, frac=None, replace=False, weights=None, random_state=None, axis=None)
Parameter :
n : Number of items from axis to return.
frac : Fraction of axis items to return.
replace : Sample with or without replacement.
weights : Default ‘None’ results in equal probability weighting.
random_state : Seed for the random number generator (if int), or numpy RandomState object.
axis : Axis to sample.
Returns : Series or DataFrame
Example #1: Use
Series.sample()
function to draw random sample of the values from the given Series object.
Python3
# importing pandas as pd
import pandas as pd
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio', 'Moscow'])
# Create the Datetime Index
index_ = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5', 'City 6']
# set the index
sr.index = index_
# Print the series
print(sr)
Output :

Now we will use
Series.sample()
function to draw a random sample of values from the given Series object.
Python3
# Draw random sample of 3 values
selected_cities = sr.sample(n = 3)
# Print the returned Series object
print(selected_cities)
Output :

As we can see in the output, the
Series.sample()
function has successfully returned a random sample of 3 values from the given Series object.
Example #2: Use
Series.sample()
function to draw random sample of the values from the given Series object.
Python3
# importing pandas as pd
import pandas as pd
# Creating the Series
sr = pd.Series([100, 25, 32, 118, 24, 65])
# Create the Index
index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp']
# set the index
sr.index = index_
# Print the series
print(sr)
Output :

Now we will use
Series.sample()
function to select a random sample of size equivalent to 25% of the size of the given Series object.
Python3
# Draw random sample of size of 25 % of the original object
selected_items = sr.sample(frac = 0.25)
# Print the returned Series object
print(selected_items)
Output :

As we can see in the output, the
Series.sample()
function has successfully returned a random sample of 2 values from the given Series object, which is 25% of the size of the original series object.