Consider a Dataframe with 4 columns : ‘ConsumerId’, ‘CarName’, CompanyName, and ‘Price’. We have to determine whether a particular column is present in the DataFrame or not.
In this pandas program, we are using Dataframe.columns attribute That return the column labels of the given Dataframe.
Syntax: Dataframe.columns
Parameter: None
Returns: column names
Let’s create a Datafame:
Code:
Python
# import pandas libraryimport pandas as pd # dictionaryd = {'ConsumerId': [1, 2, 3, 4, 5], 'CarName': ['I3', 'S4', 'J3', 'Mini', 'Beetle'], 'CompanyName': ['BMW','Mercedes', 'Jeep', 'MiniCooper', 'Volkswagen'], 'Price': [1200, 1400, 1500, 1650, 1750] } # create a dataframedf = pd.DataFrame(d) # show the dataframedf |
Output:
Example 1: To check whether the ‘ConsumerId’ column exists in Dataframe or not.
Python
if 'ConsumerId' in df.columns : print('ConsumerId column is present') else: print('ConsumerId column is not present') |
Output:
ConsumerId column is present
Example 2: To check whether the ‘CarName’ column exists in Dataframe or not.
Python
if 'CarName' in df.columns: print('CarName column is present') else: print('CarName column is not present') |
Output:
CarName column is present
Example 3: To check whether the ‘CarType’ column exists in Dataframe or not.
Python
if 'CarType' in df.columns: print('CarType column is present') else: print('CarType column is not present') |
Output:
CarType column is not present
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