Pandas Interview Questions and Answers

Ques 1. What is the difference between loc and iloc in Pandas?

loc is label-based indexing, while iloc is integer-based indexing.

Ques 2. How to drop a column in a DataFrame?

You can drop a column using the drop() method: df.drop('ColumnName', axis=1, inplace=True)

Ques 3. Explain the use of groupby() in Pandas.

groupby() is used to group DataFrame by a column and perform aggregate functions.

Example:

df.groupby('Column').mean()

Ques 4. What is the purpose of the apply() function in Pandas?

apply() is used to apply a function along the axis of a DataFrame.

Example:

df['Column'].apply(lambda x: x*2)

Ques 5. How to filter rows in a DataFrame based on a condition?

You can use boolean indexing to filter rows based on a condition: df[df['Column'] > 10]

Ques 6. What is the purpose of the pivot_table() function?

pivot_table() is used to create a spreadsheet-style pivot table as a DataFrame.

Example:

pd.pivot_table(df, values='Value', index='Index', columns='Column', aggfunc=np.sum)

Ques 7. How to handle duplicate values in a DataFrame?

You can use drop_duplicates() to remove duplicate rows: df.drop_duplicates()

Ques 8. Explain the purpose of the iterrows() function in Pandas.

iterrows() is used to iterate over DataFrame rows as (index, Series) pairs.

Example:

for index, row in df.iterrows(): print(index, row['Column'])

Ques 9. Explain the use of melt() function in Pandas.

melt() is used to reshape or transform data by unpivoting it.

Example:

pd.melt(df, id_vars=['ID'], value_vars=['Var1', 'Var2'])

Ques 10. What is the purpose of the to_csv() method in Pandas?

to_csv() is used to write a DataFrame to a CSV file.

Example:

df.to_csv('output.csv', index=False)

Ques 11. How to calculate correlation between columns in a DataFrame?

You can use the corr() method: df.corr()

Ques 12. Explain the purpose of the get_dummies() function in Pandas.

get_dummies() is used for one-hot encoding categorical variables.

Example:

pd.get_dummies(df['Category'])