You can keep the first occurrence of duplicate rows and remove subsequent duplicates using the keep parameter in the drop_duplicates() method.
Example Code :
import pandas as pd
# Create a sample DataFrame
data = {'A': [1, 2, 2, 3, 4],
'B': ['X', 'Y', 'Y', 'Z', 'X']}
df = pd.DataFrame(data)
# Keep the first occurrence of duplicates
df_no_duplicates = df.drop_duplicates(keep='first')
print(df_no_duplicates)