Question 1
Question: What is the purpose of the pivot_table() function in Pandas?
To create a new DataFrame
To pivot rows and columns in a DataFrame
To perform statistical operations on a DataFrame
To create a summary table
Question 2
How can you handle missing values in a Pandas DataFrame?
Use df.fillna(value) to replace missing values
Use df.dropna() to remove rows with missing values
Both A and B
Neither A nor B
Question 3
Question: How can you handle duplicate values in a Pandas DataFrame?
Use the df.drop_duplicates() method
Use the df.remove_duplicates() method
Use the df.drop_duplicate_rows() method
Use the df.eliminate_duplicates() method
Question 4
What is the purpose of the melt() function in Pandas?
To melt a DataFrame into a longer format
To create a melted cheese plot
To melt a DataFrame into a wider format
To melt a DataFrame into a binary format
Question 5
What does the nunique() method in Pandas calculate?
The number of non-null values
The number of unique values
The number of distinct groups
The number of unique rows
Question 6
How can you perform a time-based resampling in Pandas?
df.resample()
df.time_resample()
df.groupby("time_column").resample()
df.time_groupby().resample()
Question 7
How can you save a Pandas DataFrame to a CSV file?
df.save_csv("filename.csv")
df.write_csv("filename.csv")
df.to_csv("filename.csv")
df.export_csv("filename.csv")
Question 8
Question: What does the nlargest() method in Pandas do?
Returns the smallest values in a DataFrame
Returns the largest values in a DataFrame
Returns the smallest values in a column
Returns the largest values in a column
Question 9
How can you reset the index of a Pandas DataFrame?
df.reset_index()
df.set_index()
df.index_reset()
df.index_reset()
Question 10
What is the purpose of the pd.cut() function in Pandas?
To cut a DataFrame into smaller pieces
To categorize continuous data into discrete bins
To remove duplicate values from a DataFrame
To concatenate DataFrames along a particular axis
There are 25 questions to complete.