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1). What does the `pandas` library primarily deal with in Python??

A) Data manipulation and analysis

B) Machine learning

C) Web development

D) Game development

2). How do you import the Pandas library in Python??

A) import pandas as pd

B) import pd as pandas

C) import pandas.py

D) import pandas as np

3). Which of the following is the primary data structure in Pandas??

A) DataFrame

B) Array

C) Series

D) Matrix

4). How can you create a Pandas DataFrame from a dictionary??

A) Using pd.DataFrame()

B) Using pd.Series()

C) Using pd.list()

D) Using pd.array()

5). What is the purpose of the `head()` function in Pandas??

A) To return the first n rows of a DataFrame

B) To return the last n rows of a DataFrame

C) To drop missing values

D) To describe the DataFrame

6). How do you select a column named 'Age' from a Pandas DataFrame??

A) df['Age']

B) df.Age()

C) df.Age

D) df.select('Age')

7). Which method is used to remove missing values from a DataFrame??

A) dropna()

B) fillna()

C) isna()

D) notna()

8). How can you add a new column 'Salary' to an existing DataFrame??

A) df['Salary'] = [50000, 60000]

B) df.add_column('Salary', [50000, 60000])

C) df.insert('Salary', [50000, 60000])

D) df.add('Salary', [50000, 60000])

9). What is the purpose of the `groupby()` function in Pandas??

A) To split the data into groups based on some criteria

B) To create pivot tables

C) To sort the DataFrame

D) To filter the DataFrame

10). How do you read a CSV file into a Pandas DataFrame??

A) Using pd.read_csv()

B) Using pd.load_csv()

C) Using pd.read_file()

D) Using pd.read_table()

11). Which method is used to concatenate two DataFrames vertically??

A) concat()

B) merge()

C) join()

D) append()

12). What does the `describe()` function do in Pandas??

A) Generates descriptive statistics of the DataFrame

B) Describes the DataFrame schema

C) Returns the head of the DataFrame

D) Filters the DataFrame

13). How do you sort a DataFrame by a column named 'Age'??

A) df.sort_values(by='Age')

B) df.sort(by='Age')

C) df.order(by='Age')

D) df.arrange(by='Age')

14). How can you reset the index of a DataFrame??

A) reset_index()

B) set_index()

C) reindex()

D) index_reset()

15). How do you filter rows in a DataFrame where the 'Age' column is greater than 25??

A) df[df['Age'] > 25]

B) df.filter('Age' > 25)

C) df.select('Age' > 25)

D) df.loc['Age' > 25]

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