Mastering Data Handling in Python

What is the primary data structure used in pandas for handling tabular data?

• Array

• DataFrame

• Series

• List

How do you read a CSV file into a pandas DataFrame?

• Use 'pd.read_csv("file_path.csv")' to read a CSV file into a pandas DataFrame.

• Use 'pd.load_csv("file_path.csv")' to read a CSV file into a pandas DataFrame.

• Read the CSV file with 'pd.open_csv("file_path.csv")' into a DataFrame.

• You can import a CSV file using 'pd.import_csv("file_path.csv")' to create a DataFrame.

What function would you use to check for missing values in a DataFrame?

• df.nan_count()

• df.missing().count()

• df.checkna()

• df.isnull().sum()

How can you filter rows in a DataFrame based on a condition?

• Use df.filter(condition) to select rows.

• Use df[condition] where condition is a boolean expression.

• Apply df.select(condition) for filtering.

• Invoke df.where(condition) to get filtered results.

What method is used to group data in a DataFrame?

• filter

• groupby

• sort

• aggregate

How do you merge two DataFrames in pandas?

• pd.concat(df1, df2)

• df1 + df2

• pd.merge(df1, df2, on='key_column', how='inner')

• df1.append(df2)

What is the purpose of the 'apply' function in pandas?

• To filter rows based on a condition.

• To merge two DataFrames together.

• To apply a function along an axis of a DataFrame or on values in a Series.

• To sort the values in a DataFrame.

How can you sort a DataFrame by a specific column?

• df.order_by('column_name')

• df.sort('column_name')

• df.arrange(column_name)

• df.sort_values(by='column_name')

What is the difference between 'loc' and 'iloc' in pandas?

• 'loc' requires numeric indices; 'iloc' requires string indices.

• 'loc' can only access rows; 'iloc' can only access columns.

• 'loc' is label-based indexing; 'iloc' is integer-location based indexing.

• 'loc' is used for filtering data; 'iloc' is for sorting data.

How do you save a DataFrame to a CSV file?

• df.save('filename.csv')

• df.to_csv('filename.csv', include_index=True)

• df.write.csv('filename.csv')

• df.to_csv('filename.csv', index=False)