This article will discuss how to check if all values in a DataFrame Column are the same.

First of all, we will create a DataFrame from a list of tuples,

import pandas as pd # List of Tuples students = [('jack', 34, 'Sydney', 'Australia', 100), ('Riti', 30, 'Delhi', 'India', 100), ('Vikas', 31, 'Mumbai', 'India', 100), ('Neelu', 32, 'Bangalore','India', 100), ('John', 16, 'New York', 'US', 100), ('Mike', 17, 'las vegas', 'US', 100)] # 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:**

Name Age City Country Budget a jack 34 Sydney Australia 100 b Riti 30 Delhi India 100 c Vikas 31 Mumbai India 100 d Neelu 32 Bangalore India 100 e John 16 New York US 100 f Mike 17 las vegas US 100

This DataFrame has six rows and five columns.

## Check if all values are equal in a column

We can compare and check if all column values are equal to the first value of that column, then it means all values in that column are equal. The steps to do this is as follows,

- Select the column by name using subscript operator of DataFrame i.e. df[‘column_name’]. It gives the column contents as a Pandas Series object.
- Compare the Series object (selected column) with the first value. It will return a boolean Series.
- Check if all values in the boolean Series are True or not. If yes, then it means all values in the column are equal.

For example, let’s check if all values are the same in column ‘Budget’ from the above created DataFrame,

# Check if all values are same in column 'Budget' if (df['Budget'] == df['Budget'][0]).all(): print("All values are equal in column 'Budget'") else: print("All values are not equal in column 'Budget'")

Output:

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All values are equal in column 'Budget'

We compared the first value of column ‘Budget’, with all the other column values and got a Boolean Series object. Then using the all() function of the Series object, we checked if all the values in Boolean Series are True or not. If all values are true, all values in that column are equal.

In this example, the ‘Budget’ column had equal values; therefore, the returned boolean Series had all True values and the Series.all() function returned True in this case. Let’s check out a negative example,

Let’s check if all values are equal in column ‘Age’ in the above created DataFrame,

# Check if all values are same in column 'Age' if (df['Age'] == df['Age'][0]).all(): print("All values are equal in column 'Age'") else: print("All values are not equal in column 'Age'")

**Output:**

All values are not equal in column 'Age'

In this example, the ‘Age’ column had different values; therefore, the returned boolean Series had some True and few False values, and the Series.all() function returned False in this case. It means that all values in column ‘Age’ are not equal.

**Summary:**

We learned about different ways to check if all the values in a DataFrame column are equal or not.