To form the Union of two Index objects with different datatypes, use the index1.union(index2) method in Pandas.
At first, import the required libraries −
import pandas as pd
Creating two Pandas index −
index1 = pd.Index([10, 20, 30, 40, 50]) index2 = pd.Index(['p','q', 'r', 's', 't','u'])
Display the Pandas index1 and index2 −
print("Pandas Index1...\n",index1)
print("Pandas Index2...\n",index2)Perform union of mismatched datatypes −
res = index1.union(index2)
Example
Following is the code −
import pandas as pd
# Creating two Pandas index
index1 = pd.Index([10, 20, 30, 40, 50])
index2 = pd.Index(['p','q', 'r', 's', 't','u'])
# Display the Pandas index1 and index2
print("Pandas Index1...\n",index1)
print("Pandas Index2...\n",index2)
# Return the number of elements in Index1 and Index2
print("\nNumber of elements in index1...\n",index1.size)
print("\nNumber of elements in index2...\n",index2.size)
# Perform union of mismatched datatypes
res = index1.union(index2)
# Union of both the indexes
print("\nThe index1 and index2 Union...\n",res)Output
This will produce the following output −
Pandas Index1... Int64Index([10, 20, 30, 40, 50], dtype='int64') Pandas Index2... Index(['p', 'q', 'r', 's', 't', 'u'], dtype='object') Number of elements in index1... 5 Number of elements in index2... 6 The index1 and index2 Union... Index([10, 20, 30, 40, 50, 'p', 'q', 'r', 's', 't', 'u'], dtype='object')