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Top 68 Pandas Interview Questions
Entry Junior Mid Senior Expert
Pandas Theoretical Questions
Q1:
How to create new columns derived from existing columns in Pandas?
Entry
Q2:
What does the in operator do in Pandas?
in operator do in Pandas? Junior
Q3:
How to check whether a Pandas DataFrame is empty?
Junior
Q4:
How are iloc() and loc() different?
iloc() and loc() different? Junior
Q5:
Define the different ways a DataFrame can be created in Pandas
Junior
Q6:
Why do should make a copy of a DataFrame in Pandas?
Junior
Q7:
How does the groupby() method works in Pandas?
groupby() method works in Pandas? Junior
Q8:
Name some methods you know to replace NaN values of a DataFrame in Pandas
NaN values of a DataFrame in Pandas Junior
Q9:
What are the operations that Pandas Groupby method is based on ?
Junior
Q10:
How would you iterate over rows in a DataFrame in Pandas?
Junior
Q11:
Describe how you will get the names of columns of a DataFrame in Pandas
Junior
Q12:
In Pandas, what do you understand as a bar plot and how can you generate a bar plot visualization
Junior
Q13:
When to use merge() over concat() and vice-versa in Pandas?
merge() over concat() and vice-versa in Pandas?
Mid Mid Q15:
What is the difference(s) between merge() and concat() in Pandas?
merge() and concat() in Pandas? Mid Q16:
What is the difference between join() and merge() in Pandas?
join() and merge() in Pandas? Mid Q17:
Related To: Scikit-Learn
When would you use Scikit-Learn OneHotEncoder() vs Pandas pd.get_dummies()?
Related To: Scikit-LearnOneHotEncoder() vs Pandas pd.get_dummies()? Mid Q18:
Describe how you can combine (merge) data on Common Columns or Indices?
Mid Q19:
When cleaning data, mention how you will identify outliers present in a DataFrame object
Mid Q20:
How would you convert continuous values into discrete values in Pandas?
Mid Q21:
Name the advantage of using applymap() vs apply() method
applymap() vs apply() method Mid Q22:
Compare the Pandas methods: map(), applymap(), apply()
map(), applymap(), apply() Mid Q23:
What's the difference between at and iat in Pandas?
at and iat in Pandas? Mid Q24:
What's the difference between pivot_table() and groupby()?
pivot_table() and groupby()? Mid Q25:
Is it a good idea to iterate over DataFrame rows in Pandas?
Mid Q26:
How can I achieve the equivalents of SQL's IN and NOT IN in Pandas?
IN and NOT IN in Pandas? Mid Mid Q28:
Name some type conversion methods in Pandas
Mid Q29:
What's the difference between interpolate() and fillna() in Pandas?
interpolate() and fillna() in Pandas? Mid Q30:
How will you write DataFrame to PostgreSQL table?
Mid Q31:
Explain what is Multi-indexing in Pandas?
Senior Q32:
How is a Pandas crosstab different from a Pandas pivot_table? When would you use each one?
crosstab different from a Pandas pivot_table? When would you use each one? Senior Q33:
What is Vectorization in a context of using Pandas?
Senior Q34:
What are some best practises to optimize Pandas code?
Senior Q35:
What's the difference between apply and transform on a Group object?
apply and transform on a Group object? Senior Q36:
What does the stack() and unstack() functions do in a DataFrame?
stack() and unstack() functions do in a DataFrame? Senior Q37:
What are some best-practices to work with Large Files in Pandas?
Senior Q38:
How would you deal with large CSV files in Pandas?
Senior Q39:
What is the pipe method? When you would use it?
pipe method? When you would use it? Expert Q40:
How do you construct a MultiIndex for a DataFrame? Provide an example
MultiIndex for a DataFrame? Provide an example Expert Pandas Practical Challenges
Q1:
How do you count unique values per group with Pandas?
Entry Q2:
Related To: Dimensionality Reduction, Feature Engineering
If we have a date column in our dataset, then how will you perform Feature Engineering using Python?
Related To: Dimensionality Reduction, Feature Engineeringdate column in our dataset, then how will you perform Feature Engineering using Python? Junior Q3:
How can you sort the DataFrame?
Junior Q4:
How to convert str to datetime format in Pandas?
str to datetime format in Pandas? Junior Q5:
What does describe() percentiles values tell about our data?
describe() percentiles values tell about our data? Junior Q6:
How to split a string column in a DataFrame into two columns?
Junior Q7:
How can you find the row for which the value of a specific column is max or min?
Junior Q8:
How can you get a list of Pandas DataFrame columns based on data type?
Junior Q9:
How to get a count of the number of observations for each year in the example dataframe?
Junior Q10:
A column in a df has boolean True/False values, but for further calculations, we need 1/0 representation. How would you transform it?
df has boolean True/False values, but for further calculations, we need 1/0 representation. How would you transform it? Junior Q11:
Find a way to binary encode multi-valued categorical variables from a Pandas dataframe
Mid Q12:
How can you determine the memory usage of a DataFrame and of each column?
Mid Q13:
How do you split a DataFrame according to a boolean criterion?
Mid Q14:
How to count occurrences of values within a specific range by row?
Mid Q15:
Pivot Table Challenge
Mid Q16:
Select rows from a DataFrame based on columns value in Pandas?
Mid Q17:
How can you subset DataFrame based on a list of values?
Mid Q18:
Count the NaN values in a column in pandas DataFrame
NaN values in a column in pandas DataFrame Mid Q19:
Select rows whose column value does not equal some_value in Pandas
some_value in Pandas Mid Mid Q21:
How can you get count and mean statistics for groups in Pandas?
count and mean statistics for groups in Pandas? Mid Q22:
Group DataFrame Rows into a List
Mid Q23:
How can you read multiple files to create a single DataFrame?
Mid Q24:
Related To: Scikit-Learn
Suppose df2 is a subset of df1. How can you get the rows of df1 which are not in df2?
Related To: Scikit-Learndf2 is a subset of df1. How can you get the rows of df1 which are not in df2? Senior Q25:
How to test if a string contains one of the substrings in a list, in Pandas?
Senior Q26:
How can you read only certain rows of a CSV file chunk-by-chunk?
CSV file chunk-by-chunk? Senior Q27:
How would you compare two DataFrames and output their differences side-by-side?
Senior Q28:
Select rows in pandas MultiIndex DataFrame: select rows with values t and w on level two
MultiIndex DataFrame: select rows with values t and w on level two Expert 
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