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.difference() function return a new Index with elements from the index that are not in other.
The function automatically sorts the output if sorting is possible.
Syntax: Index.difference(other)
Parameters :
other : Index or array-like
Returns : difference : Index
Example #1: Use Index.difference() function to find the set difference of a given Index with an array-like object.
Python3
# importing pandas as pdimport pandas as pd# Creating the Indexidx = pd.Index([17, 69, 33, 15, 19, 74, 10, 5])# Print the Indexidx |
Output :
Let’s find the set difference of the given Index with an array-like object
Python3
# find the set difference of this Index # with the passed array object.idx.difference([69, 33, 15, 74, 19]) |
Output :
As we can see in the output, the function has returned an object which contains only those values which are unique to the idx Index.
Note that the output object has its element sorted in Increasing order.
Example #2: Use Index.difference() function to find the set difference of two Indexes.
Python3
# importing pandas as pdimport pandas as pd# Creating the first Indexidx1 = pd.Index(['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'])# Creating the second Indexidx2 = pd.Index(['May', 'Jun', 'Jul', 'Aug'])# Print the first and second Indexprint(idx1, "\n", idx2) |
Output :
Now, let’s find the set difference between two Indexes.
Python3
# to find the set differenceidx1.difference(idx2) |
Output :
The function has returned the set difference of idx1 and idx2. It contains only those values which are unique to idx1 Index. Note that the output is not sorted.
