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')