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1). Which method is used to merge two DataFrames based on a key column??

A) merge()

B) join()

C) concat()

D) append()

2). How can you change the index of a DataFrame to a column named 'ID'??

A) df.set_index('ID')

B) df.change_index('ID')

C) df.index('ID')

D) df.index_col('ID')

3). Which function is used to read Excel files into a Pandas DataFrame??

A) pd.read_excel()

B) pd.load_excel()

C) pd.import_excel()

D) pd.read_csv()

4). How do you filter rows in a DataFrame where the 'Salary' column is greater than 50000??

A) df[df['Salary'] > 50000]

B) df.filter('Salary' > 50000)

C) df.select('Salary' > 50000)

D) df.loc['Salary' > 50000]

5). What method is used to remove duplicates from a DataFrame??

A) drop_duplicates()

B) remove_duplicates()

C) delete_duplicates()

D) drop_na()

6). How can you rename columns of a DataFrame??

A) df.rename(columns={'old_name': 'new_name'})

B) df.change_columns({'old_name': 'new_name'})

C) df.columns_rename({'old_name': 'new_name'})

D) df.update_columns({'old_name': 'new_name'})

7). Which method is used to join two DataFrames on their indices??

A) join()

B) merge()

C) concat()

D) combine()

8). How can you create a pivot table using Pandas??

A) df.pivot_table(values='value_column', index='index_column', columns='columns_column')

B) df.create_pivot()

C) df.pivot()

D) df.pivot_data()

9). How can you check for missing values in a DataFrame??

A) df.isna()

B) df.check_na()

C) df.find_na()

D) df.missing()

10). Which method is used to concatenate two DataFrames along rows??

A) concat()

B) merge()

C) join()

D) append()

11). How do you calculate the mean of a column named 'age' in a DataFrame??

A) df['age'].mean()

B) df['age'].avg()

C) df.mean('age')

D) df['age'].average()

12). What method would you use to reset the index of a DataFrame??

A) reset_index()

B) set_index()

C) index_reset()

D) index_set()

13). Which method would you use to sort a DataFrame by a column named 'score'??

A) sort_values()

B) sort_by()

C) order_by()

D) arrange()

14). How can you drop a column named 'unnecessary_column' from a DataFrame??

A) df.drop('unnecessary_column', axis=1)

B) df.remove('unnecessary_column')

C) df.delete('unnecessary_column')

D) df.discard('unnecessary_column')

15). How would you apply a function to each element of a DataFrame column??

A) df['column'].apply(func)

B) df['column'].map(func)

C) df['column'].transform(func)

D) df['column'].apply_func(func)

16). Which method is used to calculate the cumulative sum of a column named 'values'??

A) cumsum()

B) cum_sum()

C) sum_cumulative()

D) total_sum()

17). How can you fill missing values in a DataFrame with the mean of the column??

A) df.fillna(df.mean())

B) df.fillna(df.mean(axis=1))

C) df.replace_na(df.mean())

D) df.fill_missing(df.mean())

18). What function is used to get a quick overview of the DataFrame's statistics??

A) describe()

B) summary()

C) info()

D) overview()

19). Which method is used to concatenate two DataFrames along columns??

A) concat(axis=1)

B) merge(axis=1)

C) join(axis=1)

D) append(axis=1)

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