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.delete()
function returns a new object with the passed locations deleted. We can pass more than one locations to be deleted in the form of list.
Syntax: Index.delete(loc)
Parameters :
loc : Scalar/List of IndicesReturns : new_index : Index
Example #1: Use Index.delete()
function to delete the first value in the Index.
# importing pandas as pd import pandas as pd # Creating the Index idx = pd.Index([ 'Jan' , 'Feb' , 'Mar' , 'Apr' , 'May' , 'Jun' , 'Jul' , 'Aug' , 'Sep' , 'Oct' , 'Nov' , 'Dec' ]) # Print the Index idx |
Output :
Let’s delete the month of ‘Jan’. It is present at the 0th index so we will pass 0 as an argument to the function.
# delete the first label in the given Index idx.delete( 0 ) |
Output :
As we can see in the output, the function has returned an object with its first label deleted.
Example #2: Use Index.delete()
function to delete more than one labels in the Index.
# importing pandas as pd import pandas as pd # Creating the Index idx = pd.Index([ 'Jan' , 'Feb' , 'Mar' , 'Apr' , 'May' , 'Jun' , 'Jul' , 'Aug' , 'Sep' , 'Oct' , 'Nov' , 'Dec' ]) # Print the Index idx |
Output :
Let’s delete the second, third, fourth and fifth indices from the Index. We pass a list of values to be deleted to the function.
# to delete values present at 2nd, 3rd, 4th and 5th place in the Index. idx.delete([ 2 , 3 , 4 , 5 ]) |
Output :
As we can see the labels corresponding to the passed values in the Index has been deleted.