Check if a Column exists in Pandas DataFrame

In this article, we will discuss how to check if a column or multiple columns exist in a Pandas DataFrame or not.

Suppose we have a DataFrame,

    Name  Age       City    Country  Budget
a   jack   34     Sydney  Australia     200
b   Riti   30      Delhi      India     321
c  Vikas   31     Mumbai      India     333
d  Neelu   32  Bangalore      India     238
e   John   16   New York         US     262
f   Mike   17  las vegas         US     198

Now we want to check, if column with name ‘Age’ exists in this DataFrame? Also, it might be possible that we have a list of names and we want to check if all the columns mentioned in list exist in DataFrame or not? Let’s see how to do that.

First we will create a DataFrame from list of tuples,

import pandas as pd

# List of Tuples
students = [('jack',    34, 'Sydney',   'Australia', 200),
            ('Riti',    30, 'Delhi',    'India',     321),
            ('Vikas',   31, 'Mumbai',   'India',    333),
            ('Neelu',   32, 'Bangalore','India',    238),
            ('John',    16, 'New York',  'US',      262),
            ('Mike',    17, 'las vegas', 'US',      198)]

# Create a DataFrame object
df = pd.DataFrame( students,
                   columns=['Name', 'Age', 'City', 'Country', 'Budget'],
                   index=  ['a', 'b', 'c', 'd', 'e', 'f'])

# Display the DataFrame
print(df)

Output:

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    Name  Age       City    Country  Budget
a   jack   34     Sydney  Australia     200
b   Riti   30      Delhi      India     321
c  Vikas   31     Mumbai      India     333
d  Neelu   32  Bangalore      India     238
e   John   16   New York         US     262
f   Mike   17  las vegas         US     198

This DataFrame has five columns and six rows.

Check if a Column exists in DataFrame

In Pandas, the DataFrame provides an attribute columns, and it gives an Index object containing a sequence of all column names of the DataFrame. We can use the “in operator” with this Index object to check if a name exists in this sequence of column names. For example, let’s see how to check if column ‘Age’ exists in the above created DataFrame,

# Check if column with name 'Age' exists in a Dataframe
if 'Age' in df.columns:
    print('Column exists in the DataFrame')
else:
    print('Column does not exists in the DataFrame')

Output:

Column exists in the DataFrame

The df.columns returned an Index object containing all column names of the DataFrame, and then we checked if the name ‘Age’ was in it or not. As column exists in the DataFrame, the “in operator” returned True. Let’s check out a negative example,

# Check if column with name 'Experience' exists in a Dataframe
if 'Experience' in df.columns:
    print('Column exists in the DataFrame')
else:
    print('Column does not exists in the DataFrame')

Output:

Column does not exists in the DataFrame

In the example, “Experience” doesn’t exist in the DataFrame. Therefore the “in operator” returned False.

Check if multiple columns exist in Pandas DataFrame

Using list comprehension and in operator

Suppose we have a list of a few column names, and we want to check if all of these columns exist in a DataFrame or not. To do that, we can iterate over all of these column names and one by one check if the column name exists or not. For example,

column_names = ['Age', 'Budget']

# Check if all of the column names in a list exist in DataFrame
if all(col in df.columns for col in column_names):
    print('All Column names exists in the DataFrame')
else:
    print('All Column names does not exists in the DataFrame')

Output:

All Column names exists in the DataFrame

Our list had two column names ‘Age’ and ‘Budget’. We iterated over all the names in this list and checked if each of them exists in the DataFrame or not. There is another way to achieve the same using set.

Using Set and issubset()

Convert the list of names to a set and then call that set’s issubset() method. As an argument, pass all the column names of DataFrame. The issubset() function will return True if all the calling set items exist in the passed argument. For example,

column_names = ['Age', 'Budget']

# Check if all of the column names in a list exist in DataFrame
if set(column_names).issubset(df.columns):
    print('All Column names exists in the DataFrame')
else:
    print('All Column names does not exists in the DataFrame')

Output:

All Column names exists in the DataFrame

All the column names in the lists exist in the DataFrame.

How did it work?

We converted the list of column names to a Set and called the issubset() function. As an argument, we passed the df.columns i.e. all the column names of the DataFrame. The issubset() returned True because all the Set items exist in the passed sequence of DataFrame column names.

Let’s check out a negative example,

column_names = ['Age', 'Budget', 'Department']

# Check if all of the column names in a list exist in DataFrame
if set(column_names).issubset(df.columns):
    print('All Column names exists in the DataFrame')
else:
    print('All Column names does not exists in the DataFrame')

Output:

All Column names does not exists in the DataFrame

All the column names in the lists do not exist in the DataFrame.

Summary:

We learned how to check if single or multiple columns exist in the DataFrame or not in Pandas.

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