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.contains() function return a boolean indicating whether the provided key is in the index. If the input value is present in the Index then it returns True else it returns False indicating that the input value is not present in the Index.
Syntax: Index.contains(key)
Parameters :
Key : ObjectReturns : boolean
Example #1: Use Index.contains() function to check if the given date is present in the Index.
# importing pandas as pd import pandas as pd # Creating the Index idx = pd.Index(['2015-10-31', '2015-12-02', '2016-01-03', '2016-02-08', '2017-05-05']) # Print the Index idx |
Output :
Let’s check if ‘2016-02-08’ is present in the Index or not.
# Check if input date in present or not. idx.contains('2016-02-08') |
Output :
As we can see in the output, the function has returned True indicating that the value is present in the Index.
Example #2: Use Index.contains() function to check if the input month is present in the Index or not.
# 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 check if ‘May’ is present in the Index or not
# to check if the input month is # part of the Index or not. idx.contains('May') |
Output :
