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Try YTGrowAI FreeTop 100 Python Pandas MCQs with Answers
Pandas is one of the most important Python libraries for data analysis and data-driven roles. It is widely used in startups and major tech companies to efficiently handle, clean, and analyse data.
Listed below are the top 100 Python Pandas MCQs, designed to boost your confidence in Pandas. Plus, these questions are frequently asked in exams and interviews, and also help in daily development practices.
100 Python Pandas MCQs with Answers
Q1. Which of the following is the standard alias used for importing the Pandas library in Python?
A. import pandas as pd
B. import pandas as py
C. import pandas as pn
D. import pandas as p
Show Answer
Answer: A
The standard convention is ‘import pandas as pd’ to keep code concise and readable.
Q2. Which Pandas data structure represents a one-dimensional labeled array capable of holding any data type?
A. DataFrame
B. Panel
C. Series
D. Matrix
Show Answer
Answer: C
A Series is a one-dimensional labeled array in Pandas, while a DataFrame is two-dimensional.
Q3. Which Pandas function is primarily used to read data from a CSV file into a DataFrame?
A. pd.read_csv()
B. pd.load_csv()
C. pd.import_csv()
D. pd.open_csv()
Show Answer
Answer: A
The pd.read_csv() function is the standard method to load comma-separated values files.
Q4. What is the primary data structure in Pandas that represents a two-dimensional, size-mutable, potentially heterogeneous tabular data?
A. Series
B. DataFrame
C. Array
D. List
Show Answer
Answer: B
A DataFrame is a 2D labeled data structure with columns of potentially different types.
Q5. Which method is used to display the first ‘n’ rows of a DataFrame?
A. df.first()
B. df.top()
C. df.head()
D. df.start()
Show Answer
Answer: C
The df.head(n) method returns the first n rows (default is 5) of the DataFrame.
Q6. Which method provides a concise summary of a DataFrame including non-null counts and data types?
A. df.describe()
B. df.summary()
C. df.info()
D. df.dtypes()
Show Answer
Answer: C
df.info() prints a summary of the DataFrame including index dtype, columns, non-null values, and memory usage.
Q7. How can you access a specific column named ‘Age’ from a DataFrame named ‘df’ using bracket notation?
A. df[‘Age’]
B. df.Age
C. df(‘Age’)
D. Both A and B
Show Answer
Answer: D
You can access a column using df[‘Age’] (bracket notation) or df.Age (dot notation), though bracket notation is preferred for column names with spaces.
Q8. Which attribute is used to get the dimensions (rows, columns) of a DataFrame?
A. df.dim
B. df.shape
C. df.size
D. df.ndim
Show Answer
Answer: B
The df.shape attribute returns a tuple representing the number of rows and columns.
Q9. Which Pandas method is used to remove missing values (NaN) from a DataFrame?
A. df.dropna()
B. df.fillna()
C. df.remove_na()
D. df.clean()
Show Answer
Answer: A
df.dropna() removes rows or columns containing missing values based on the parameters provided.
Q10. Which method is used to replace missing values (NaN) with a specific value in a DataFrame?
A. df.dropna()
B. df.fillna()
C. df.replace_na()
D. df.impute()
Show Answer
Answer: B
df.fillna() is used to fill NA/NaN values using the specified method like a constant value or mean.
Q11. In Pandas, which indexer is used for label-based indexing?
A. .iloc
B. .loc
C. .ix
D. .at
Show Answer
Answer: B
.loc is primarily label-based, but may also be used with a boolean array.
Q12. In Pandas, which indexer is used for integer position-based indexing?
A. .loc
B. .iloc
C. .iat
D. .get
Show Answer
Answer: B
.iloc is primarily integer position-based (from 0 to length-1 of the axis).
Q13. Which function is used to combine two DataFrames based on a common column (similar to SQL JOIN)?
A. pd.concat()
B. pd.merge()
C. pd.append()
D. pd.join()
Show Answer
Answer: B
pd.merge() is used to merge DataFrame or named Series objects with a database-style join.
Q14. Which Pandas method is used to concatenate Pandas objects along a particular axis?
A. pd.merge()
B. pd.join()
C. pd.concat()
D. pd.combine()
Show Answer
Answer: C
pd.concat() is used to concatenate pandas objects along a particular axis with optional set logic.
Q15. Which method is used to group data in a DataFrame based on one or more columns?
A. df.aggregate()
B. df.groupby()
C. df.partition()
D. df.segment()
Show Answer
Answer: B
df.groupby() involves splitting the object, applying a function, and combining the results.
Q16. Which method is used to generate descriptive statistics of a DataFrame’s numerical columns?
A. df.describe()
B. df.stats()
C. df.calculate()
D. df.summary()
Show Answer
Answer: A
df.describe() generates descriptive statistics like count, mean, std, min, and percentiles.
Q17. How do you sort a DataFrame ‘df’ by the values of a column named ‘Salary’?
A. df.order(‘Salary’)
B. df.sort_values(‘Salary’)
C. df.sort(‘Salary’)
D. df.rank(‘Salary’)
Show Answer
Answer: B
df.sort_values() sorts a DataFrame by the values of the specified column(s).
Q18. Which attribute returns the column labels of a DataFrame?
A. df.index
B. df.columns
C. df.rows
D. df.labels
Show Answer
Answer: B
The df.columns attribute returns an Index object containing the column labels.
Q19. Which Pandas function creates a DataFrame from a Python dictionary?
A. pd.Series()
B. pd.DataFrame()
C. pd.from_dict()
D. Both B and C
Show Answer
Answer: D
pd.DataFrame() can take a dictionary, and pd.from_dict() constructs a DataFrame from a dict specifically.
Q20. Which method is used to save a DataFrame to a CSV file?
A. df.save_csv()
B. df.to_csv()
C. df.export_csv()
D. df.write_csv()
Show Answer
Answer: B
df.to_csv() writes the DataFrame to a comma-separated values (csv) file.
Q21. Which method is used to display the last ‘n’ rows of a DataFrame?
A. df.end()
B. df.bottom()
C. df.tail()
D. df.last()
Show Answer
Answer: C
df.tail(n) returns the last n rows of the DataFrame object.
Q22. What will be the output of `df.isnull().sum()`?
A. Total number of elements in the DataFrame.
B. Total number of non-null values in each column.
C. Total number of missing values in each column.
D. Boolean DataFrame indicating missing values.
Show Answer
Answer: C
df.isnull() creates a boolean mask, and .sum() counts the True (missing) values for each column.
Q23. Which parameter in `pd.read_csv()` is used to specify which row should be used as the column labels?
A. index_col
B. header
C. names
D. usecols
Show Answer
Answer: B
The ‘header’ parameter allows you to specify the row number to use as the column names.
Q24. Which parameter in `pd.read_csv()` is used to specify a column to be used as the row labels?
A. header
B. index_col
C. row_label
D. primary_key
Show Answer
Answer: B
The ‘index_col’ parameter is used to set a specific column as the index of the DataFrame.
Q25. Which method is used to rename the column names of a DataFrame?
A. df.columns.rename()
B. df.rename()
C. df.rename(columns={})
D. df.alter()
Show Answer
Answer: C
df.rename(columns={‘old’:’new’}) is used to alter axes labels, specifically columns here.
Q26. Which method is used to remove duplicate rows from a DataFrame?
A. df.remove_duplicates()
B. df.drop_duplicates()
C. df.unique()
D. df.nunique()
Show Answer
Answer: B
df.drop_duplicates() returns a DataFrame with duplicate rows removed.
Q27. Which method is used to find the number of unique values in a Series?
A. df.unique()
B. df.nunique()
C. df.count()
D. df.value_counts()
Show Answer
Answer: B
.nunique() returns the number of unique elements in the object.
Q28. Which method returns a Series containing counts of unique values?
A. df.count()
B. df.value_counts()
C. df.unique()
D. df.freq()
Show Answer
Answer: B
.value_counts() returns a Series containing counts of unique values, sorted in descending order.
Q29. Which method applies a function to each element of a DataFrame?
A. df.apply()
B. df.map()
C. df.applymap()
D. df.func()
Show Answer
Answer: C
df.applymap() applies a function to a DataFrame element-wise; df.apply() works on rows/columns.
Q30. Which method applies a function along an axis of the DataFrame (row-wise or column-wise)?
A. df.applymap()
B. df.apply()
C. df.map()
D. df.agg()
Show Answer
Answer: B
df.apply() applies a function along an axis (0 for index, 1 for columns) of the DataFrame.
Q31. Which method is used to change the data type of a Series?
A. df.convert()
B. df.astype()
C. df.change_type()
D. df.type()
Show Answer
Answer: B
The .astype() method is used to cast a pandas object to a specified dtype.
Q32. Which Pandas function reads an Excel file into a DataFrame?
A. pd.read_excel()
B. pd.read_xls()
C. pd.load_excel()
D. pd.import_excel()
Show Answer
Answer: A
pd.read_excel() reads an Excel file into a pandas DataFrame.
Q33. What is the result of `type(pd.Series([1, 2, 3]))`?
A. <class ‘list’>
B. <class ‘numpy.ndarray’>
C. <class ‘pandas.core.series.Series’>
D. <class ‘dict’>
Show Answer
Answer: C
Creating a Series object results in the pandas.core.series.Series class type.
Q34. Which attribute of a Series returns the index (row labels)?
A. .columns
B. .index
C. .keys
D. .labels
Show Answer
Answer: B
The .index attribute returns the index (axis labels) of the Series.
Q35. How can you select rows 0 to 3 (inclusive) from a DataFrame ‘df’ using integer location?
A. df.loc[0:3]
B. df.iloc[0:3]
C. df.iloc[0:4]
D. df[0:3]
Show Answer
Answer: C
With .iloc, the stop index is exclusive, so to include row 3, you must specify 4.
Q36. Which method is used to reset the index of a DataFrame?
A. df.set_index()
B. df.reset_index()
C. df.reindex()
D. df.new_index()
Show Answer
Answer: B
df.reset_index() resets the index to the default integer index (0, 1, 2…).
Q37. Which method is used to set an existing column as the index of the DataFrame?
A. df.reset_index()
B. df.set_index()
C. df.index()
D. df.reindex()
Show Answer
Answer: B
df.set_index() sets the DataFrame index using one or more existing columns.
Q38. Which function is used to handle date and time data conversion in Pandas?
A. pd.to_datetime()
B. pd.date_convert()
C. pd.datetime()
D. pd.to_date()
Show Answer
Answer: A
pd.to_datetime() is used to convert argument to datetime.
Q39. What does the `inplace=True` parameter do in a Pandas method?
A. Returns a new object with changes.
B. Modifies the object in place and returns None.
C. Does not modify the object.
D. Creates a copy of the object.
Show Answer
Answer: B
If inplace=True, the operation modifies the object directly without returning a new object.
Q40. Which type of join keeps all rows from the left DataFrame and matches from the right?
A. Inner Join
B. Right Join
C. Outer Join
D. Left Join
Show Answer
Answer: D
A Left Join (how=’left’) uses only keys from the left frame, similar to a SQL left outer join.
Q41. Which parameter in `pd.merge()` is used to specify the type of join?
A. on
B. type
C. how
D. join_type
Show Answer
Answer: C
The ‘how’ parameter determines the type of merge to be performed (left, right, outer, inner).
Q42. Which method is used to iterate over DataFrame rows as (index, Series) pairs?
A. df.iterrows()
B. df.iteritems()
C. df.itertuples()
D. df.loop()
Show Answer
Answer: A
df.iterrows() iterates over DataFrame rows as (index, Series) pairs.
Q43. Which method is generally faster for iterating over DataFrame rows?
A. df.iterrows()
B. df.apply()
C. df.itertuples()
D. for loop with .loc
Show Answer
Answer: C
df.itertuples() is generally faster than iterrows() because it returns namedtuples.
Q44. Which method is used to pivot a DataFrame from long format to wide format?
A. df.pivot_table()
B. df.pivot()
C. df.melt()
D. df.stack()
Show Answer
Answer: B
df.pivot() returns reshaped DataFrame organized by given index / column values.
Q45. Which method is used to pivot a DataFrame with aggregation of duplicate values?
A. df.pivot()
B. df.melt()
C. df.pivot_table()
D. df.cross_tab()
Show Answer
Answer: C
df.pivot_table() creates a spreadsheet-style pivot table as a DataFrame, allowing for aggregation.
Q46. Which method is used to unpivot a DataFrame from wide format to long format?
A. df.pivot()
B. df.melt()
C. df.unstack()
D. df.transpose()
Show Answer
Answer: B
df.melt() unpivots a DataFrame from wide to long format, optionally leaving identifiers set.
Q47. Which attribute returns the total number of elements in a DataFrame?
A. df.shape
B. df.size
C. df.ndim
D. df.length
Show Answer
Answer: B
df.size returns an int representing the number of elements (rows * columns).
Q48. Which attribute returns the number of dimensions (axes) of a DataFrame?
A. df.shape
B. df.size
C. df.ndim
D. df.axes
Show Answer
Answer: C
df.ndim returns 2 for a DataFrame and 1 for a Series.
Q49. Which method is used to compute the pairwise correlation of columns?
A. df.cov()
B. df.corr()
C. df.correlation()
D. df.stats()
Show Answer
Answer: B
df.corr() computes pairwise correlation of columns, excluding NA/null values.
Q50. Which method is used to compute the covariance matrix of columns?
A. df.corr()
B. df.cov()
C. df.diff()
D. df.var()
Show Answer
Answer: B
df.cov() computes pairwise covariance of columns, excluding NA/null values.
Q51. Which method allows you to filter rows based on a condition?
A. df.filter()
B. df.select()
C. Boolean Indexing
D. df.query()
Show Answer
Answer: C
Boolean Indexing (e.g., df[df[‘col’] > 5]) is the primary way to filter rows based on conditions.
Q52. Which method allows filtering rows using a query string?
A. df.filter()
B. df.where()
C. df.query()
D. df.search()
Show Answer
Answer: C
df.query() queries the columns of a DataFrame with a boolean expression.
Q53. Which method is used to replace values in a DataFrame?
A. df.substitute()
B. df.replace()
C. df.swap()
D. df.exchange()
Show Answer
Answer: B
df.replace() is used to replace values given in ‘to_replace’ with ‘value’.
Q54. Which method is used to transpose a DataFrame (swap rows and columns)?
A. df.T
B. df.transpose()
C. df.flip()
D. Both A and B
Show Answer
Answer: D
Both df.T and df.transpose() transpose the index and columns.
Q55. Which function creates a date range in Pandas?
A. pd.date_range()
B. pd.time_range()
C. pd.sequence()
D. pd.period()
Show Answer
Answer: A
pd.date_range() returns a fixed frequency DatetimeIndex.
Q56. Which method is used to shift index by desired number of periods?
A. df.move()
B. df.shift()
C. df.offset()
D. df.slide()
Show Answer
Answer: B
df.shift() shifts index by desired number of periods with an optional time freq.
Q57. Which method is used to find the index of the maximum value in a Series?
A. df.idxmax()
B. df.argmax()
C. df.max_index()
D. df.max()
Show Answer
Answer: A
df.idxmax() returns the index of the first occurrence of maximum value.
Q58. Which method is used to find the index of the minimum value in a Series?
A. df.idxmin()
B. df.argmin()
C. df.min_index()
D. df.min()
Show Answer
Answer: A
df.idxmin() returns the index of the first occurrence of minimum value.
Q59. Which method is used to insert a column into a DataFrame at a specific location?
A. df.insert()
B. df.add()
C. df.append()
D. df.assign()
Show Answer
Answer: A
df.insert(loc, column, value) inserts a column into DataFrame at specified location.
Q60. Which method is used to add new columns to a DataFrame?
A. df.insert()
B. df.assign()
C. df.add()
D. df.create()
Show Answer
Answer: B
df.assign() assigns new columns to a DataFrame, returning a new object with all original columns in addition to new ones.
Q61. Which function creates a crosstabulation of two factors?
A. pd.pivot_table()
B. pd.crosstab()
C. pd.merge()
D. pd.concat()
Show Answer
Answer: B
pd.crosstab() computes a simple cross tabulation of two (or more) factors.
Q62. What does the `axis=1` parameter signify in DataFrame operations?
A. Operation is performed column-wise.
B. Operation is performed row-wise.
C. Operation is performed on the index.
D. Operation is performed on values.
Show Answer
Answer: A
axis=1 represents columns, meaning the operation is applied across columns (e.g., dropping a column).
Q63. What does the `axis=0` parameter signify in DataFrame operations?
A. Operation is performed column-wise.
B. Operation is performed row-wise (index).
C. Operation is performed on values.
D. Operation is performed on headers.
Show Answer
Answer: B
axis=0 represents rows (index), meaning the operation is applied across rows.
Q64. Which method is used to drop specified labels from rows or columns?
A. df.remove()
B. df.drop()
C. df.delete()
D. df.discard()
Show Answer
Answer: B
df.drop() removes rows or columns by specifying label names and corresponding axis.
Q65. Which method is used to calculate the percentage change between current and prior element?
A. df.diff()
B. df.pct_change()
C. df.rate()
D. df.shift()
Show Answer
Answer: B
df.pct_change() calculates the percentage change between the current and a prior element.
Q66. Which method is used to calculate the difference between elements?
A. df.pct_change()
B. df.subtract()
C. df.diff()
D. df.minus()
Show Answer
Answer: C
df.diff() calculates the difference of a DataFrame element compared with another element in the DataFrame.
Q67. Which method is used to calculate cumulative sum over a DataFrame or Series axis?
A. df.sum()
B. df.cumsum()
C. df.total()
D. df.aggregate()
Show Answer
Answer: B
df.cumsum() returns cumulative sum over a DataFrame or Series axis.
Q68. Which method creates a copy of the DataFrame?
A. df.copy()
B. df.clone()
C. df.duplicate()
D. df.snapshot()
Show Answer
Answer: A
df.copy() creates a deep copy of the object’s data and index.
Q69. Which method checks if a DataFrame is empty?
A. df.is_empty()
B. df.empty
C. df.isnull()
D. df.null()
Show Answer
Answer: B
df.empty is a boolean attribute indicating if the DataFrame is empty.
Q70. Which method is used to select rows based on a date-time index?
A. Partial String Indexing
B. Integer Indexing
C. Boolean Indexing
D. Label Indexing
Show Answer
Answer: A
Pandas allows selecting rows using partial string indexing (e.g., df[‘2023-01’]) on a datetime index.
Q71. Which method is used to apply a function to a Series element-wise?
A. .apply()
B. .map()
C. .applymap()
D. .agg()
Show Answer
Answer: B
For a Series, .map() is typically used for element-wise operations using a function or dictionary.
Q72. Which Pandas function creates a Series from a NumPy array?
A. pd.Series(array)
B. pd.to_series(array)
C. pd.from_numpy(array)
D. pd.create_series(array)
Show Answer
Answer: A
pd.Series() can accept a NumPy array to create a Series object.
Q73. Which method is used to calculate the rolling mean?
A. df.mean()
B. df.rolling().mean()
C. df.window_mean()
D. df.moving_average()
Show Answer
Answer: B
df.rolling(window).mean() provides rolling window calculations.
Q74. Which method is used to stack the prescribed level(s) from columns to index?
A. df.stack()
B. df.unstack()
C. df.pivot()
D. df.melt()
Show Answer
Answer: A
df.stack() stacks the prescribed level(s) from columns to index.
Q75. Which method is used to unstack the prescribed level(s) from index to columns?
A. df.stack()
B. df.unstack()
C. df.pivot()
D. df.flatten()
Show Answer
Answer: B
df.unstack() pivots a level of the (necessarily hierarchical) index labels.
Q76. Which function is used to create a categorical variable from a column?
A. pd.cut()
B. pd.category()
C. pd.bin()
D. pd.group()
Show Answer
Answer: A
pd.cut() bins values into discrete intervals, useful for creating categorical variables.
Q77. Which function is used to quantile-based discretization of a variable?
A. pd.cut()
B. pd.qcut()
C. pd.bin()
D. pd.quantile()
Show Answer
Answer: B
pd.qcut() discretizes variable into equal-sized buckets based on rank or based on sample quantiles.
Q78. Which method is used to sort a DataFrame by its index?
A. df.sort_index()
B. df.sort_values()
C. df.order_index()
D. df.reindex()
Show Answer
Answer: A
df.sort_index() sorts object by labels (along an axis).
Q79. Which method allows getting data from a DataFrame based on integer location for a single scalar value?
A. .loc
B. .iloc
C. .iat
D. .at
Show Answer
Answer: C
.iat is used for fast scalar access by integer location.
Q80. Which method allows getting data from a DataFrame based on label for a single scalar value?
A. .loc
B. .iloc
C. .at
D. .iat
Show Answer
Answer: C
.at is used for fast scalar access by label.
Q81. What is the output of `df.groupby(‘col’).sum()`?
A. Returns a Series
B. Returns a DataFrame with sum of values grouped by ‘col’
C. Returns a scalar value
D. Returns a list
Show Answer
Answer: B
It groups the DataFrame by ‘col’ and calculates the sum of numeric columns within each group.
Q82. Which method is used to write a DataFrame to an Excel file?
A. df.to_xls()
B. df.save_excel()
C. df.to_excel()
D. df.write_excel()
Show Answer
Answer: C
df.to_excel() writes the DataFrame to an Excel sheet.
Q83. Which method is used to write a DataFrame to a SQL database?
A. df.to_sql()
B. df.save_sql()
C. df.write_sql()
D. df.export_sql()
Show Answer
Answer: A
df.to_sql() writes records stored in a DataFrame to a SQL database.
Q84. Which method converts a DataFrame to a dictionary?
A. df.to_dict()
B. df.to_json()
C. df.dict()
D. df.convert_dict()
Show Answer
Answer: A
df.to_dict() converts the DataFrame to a dictionary.
Q85. Which method converts a DataFrame to a NumPy array?
A. df.to_numpy()
B. df.to_array()
C. df.values()
D. df.as_matrix()
Show Answer
Answer: A
df.to_numpy() is the modern preferred method to convert a DataFrame to a NumPy array.
Q86. Which function creates a DataFrame from a list of lists?
A. pd.DataFrame(list_of_lists)
B. pd.from_list(list_of_lists)
C. pd.create_frame(list_of_lists)
D. pd.series(list_of_lists)
Show Answer
Answer: A
pd.DataFrame() constructor accepts a list of lists where each inner list is treated as a row.
Q87. Which function creates a DataFrame from a JSON string or file?
A. pd.read_json()
B. pd.load_json()
C. pd.import_json()
D. pd.parse_json()
Show Answer
Answer: A
pd.read_json() converts a JSON string or file to a pandas object.
Q88. Which parameter is used to skip the top N rows while reading a CSV?
A. skiprows
B. skip_top
C. header
D. start_row
Show Answer
Answer: A
The ‘skiprows’ parameter is used to skip the first N lines of the file.
Q89. Which method is used to plot a DataFrame directly?
A. df.draw()
B. df.plot()
C. df.graph()
D. df.show()
Show Answer
Answer: B
df.plot() is a wrapper around matplotlib.pyplot.plot() for plotting DataFrames.
Q90. Which method is used to perform an aggregation using a dictionary?
A. df.agg()
B. df.aggregate()
C. df.groupby().agg()
D. All of the above
Show Answer
Answer: D
.agg() is an alias for .aggregate() and can be used with groupby or directly on a DataFrame.
Q91. Which method returns a random sample of items from an axis of object?
A. df.random()
B. df.sample()
C. df.shuffle()
D. df.take()
Show Answer
Answer: B
df.sample() returns a random sample of elements from an axis of object.
Q92. Which attribute returns a Numpy representation of the DataFrame?
A. df.array
B. df.values
C. df.numpy
D. df.matrix
Show Answer
Answer: B
df.values returns a Numpy representation of the DataFrame (though .to_numpy() is now preferred).
Q93. Which method filters data based on labels, keeping rows where the condition is False as NaN?
A. df.filter()
B. df.mask()
C. df.where()
D. df.query()
Show Answer
Answer: C
df.where() replaces values where the condition is False with NaN (or specified value).
Q94. Which method is the inverse of df.where()?
A. df.mask()
B. df.filter()
C. df.loc()
D. df.replace()
Show Answer
Answer: A
df.mask() replaces values where the condition is True, opposite to where().
Q95. Which method is used to find unique values from a Series?
A. df.unique()
B. pd.unique(series)
C. series.unique()
D. Both B and C
Show Answer
Answer: D
pd.unique() works on arrays/series, and series.unique() returns unique values from the Series.
Q96. How do you drop a column named ‘temp’ permanently from a DataFrame?
A. df.drop(‘temp’, axis=1)
B. df.drop(‘temp’, axis=1, inplace=True)
C. df.drop(‘temp’)
D. df.drop_column(‘temp’)
Show Answer
Answer: B
Setting inplace=True ensures the column is dropped permanently from the original DataFrame.
Q97. Which method is used to rank the values in a Series?
A. df.sort_values()
B. df.rank()
C. df.order()
D. df.position()
Show Answer
Answer: B
df.rank() computes numerical data ranks (1 through n) along axis.
Q98. Which function is used to evaluate a Python expression as a string?
A. df.eval()
B. df.query()
C. pd.eval()
D. Both A and C
Show Answer
Answer: D
Both df.eval() and pd.eval() can evaluate a string expression, often more efficiently for large operations.
Q99. Which attribute is used to access the underlying data of a DataFrame?
A. .data
B. .values
C. .to_numpy()
D. .dtypes
Show Answer
Answer: C
.to_numpy() is the recommended method to access the underlying NumPy array data.
Q100. Which method provides a styled DataFrame object for formatting?
A. df.format()
B. df.style
C. df.render()
D. df.css()
Show Answer
Answer: B
df.style returns a Styler object, which provides methods for formatting and styling DataFrames.
Conclusion
These 100 Python Pandas MCQs will help you feel confident for data interviews and exams in 2026. Since Pandas is built on top of NumPy, understanding NumPy makes many Pandas concepts easier to grasp. To strengthen that foundation, you can also go through these NumPy interview questions for better preparation:
- NumPy Interview Questions
- For broader preparation, you may also check out: 100 Python Interview Questions for 2026 (Ultimate Preparation Guide)
- In case you are into Machine Learning, check out Machine Learning Interview Questions
Make sure to bookmark this page for later revision. Just press “Ctrl + D” on Windows or “Cmd + D” on Mac so you can easily revisit these MCQs anytime you need.
