Python | Pandas Index.slice_locs()

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Pandas Index.slice_locs() function compute slice locations for input labels. It takes start and end labels as the parameter and returns the integer value corresponding to those values.

Syntax: Index.slice_locs(start=None, end=None, step=None, kind=None)

Parameters :
start : If None, defaults to the beginning
end : If None, defaults to the end
step : If None, defaults to 1
kind : {‘ix’, ‘loc’, ‘getitem’} or None

Returns : start, end : int

Example #1: Use Index.slice_locs() function to find the slice labels for the input values.

# importing pandas as pd
import pandas as pd

# Creating the index
idx = pd.Index(['Beagle', 'Pug', 'Labrador', 'Sephard',
                             'Mastiff', None, 'Husky'])

# Print the index
idx

Output :

Now we will find the slice labels for ‘Pug’ and ‘Mastiff’

# finding the slice labels for the input value.
idx.slice_locs(start ='Pug', end ='Mastiff')

Output :

As we can see in the output, the function has returned the slice locations for the input labels.

Example #2: Use Index.slice_locs() function to find the slice labels in the date-time base index.

# importing pandas as pd
import pandas as pd

# Creating the index
idx = pd.date_range('1 / 1/2018', periods = 5, freq ='MS')

# Print the index
idx

Output :

Now we would find the slice labels for the input labels.

# finding the slice labels
idx.slice_locs(start ='2018-02-01', end ='2018-04-01')

Output :

As we can see in the output, the function has returned the range values which contains the input slice label value.