Write a program in Python to check if a series contains duplicate elements or not

A Pandas Series is a one-dimensional data structure that can contain duplicate values. To check if a series contains duplicates, we can compare the series length with the number of unique elements.

Sample Series Data

Let's start with a series that has no duplicate elements ?

import pandas as pd
import numpy as np

# Series with no duplicates
data = pd.Series([1, 2, 3, 4, 5])
print("Original Series:")
print(data)

Original Series:
0    1
1    2
2    3
3    4
4    5
dtype: int64

Method 1: Using len() and np.unique()

Compare the length of the original series with the length of unique elements ?

import pandas as pd
import numpy as np

data = pd.Series([1, 2, 3, 4, 5])

if len(data) == len(np.unique(data)):
    print("No duplicates found")
else:
    print("Duplicates found!")

No duplicates found

Method 2: Using Pandas duplicated()

The duplicated() method returns a boolean Series indicating duplicate rows ?

import pandas as pd

data = pd.Series([1, 2, 3, 4, 5])

if data.duplicated().any():
    print("Duplicates found!")
else:
    print("No duplicates found")

No duplicates found

Testing with Duplicate Elements

Now let's test both methods with a series containing duplicate values ?

import pandas as pd
import numpy as np

# Series with duplicates
data_with_duplicates = pd.Series([1, 2, 3, 4, 5, 3])
print("Series with duplicates:")
print(data_with_duplicates)

# Method 1: Using np.unique()
if len(data_with_duplicates) == len(np.unique(data_with_duplicates)):
    print("Method 1: No duplicates found")
else:
    print("Method 1: Duplicates found!")

# Method 2: Using duplicated()
if data_with_duplicates.duplicated().any():
    print("Method 2: Duplicates found!")
else:
    print("Method 2: No duplicates found")

Series with duplicates:
0    1
1    2
2    3
3    4
4    5
5    3
dtype: int64
Method 1: Duplicates found!
Method 2: Duplicates found!

Comparison

Conclusion

Use duplicated().any() for a pandas-native approach, or compare len(data) with len(np.unique(data)) for a simple length-based check. Both methods effectively identify duplicate elements in a Series.