Python Pandas Questions et reponses d'entretien

Question 31. How do you handle duplicate values in a Pandas DataFrame?

Use the drop_duplicates() function. df.drop_duplicates()

Question 32. Explain the purpose of the to_datetime() function in Pandas.

to_datetime() is used to convert the argument to datetime.

Example:

df['date_column'] = pd.to_datetime(df['date_column'])

Question 33. What is the difference between Series.value_counts() and DataFrame['column'].value_counts()?

Series.value_counts() returns the counts of unique values in a Series, while DataFrame['column'].value_counts() returns counts for a specific column.

Question 34. Explain the use of the transform() function in Pandas.

transform() is used to perform group-specific computations and return a DataFrame with the same shape as the input.

Example:

df['normalized_column'] = df.groupby('group_column')['value_column'].transform(lambda x: (x - x.mean()) / x.std())

Question 35. How do you change the data type of a Pandas Series or DataFrame column?

Use the astype() function. df['column'] = df['column'].astype('new_dtype')