Python Pandas for Data Analysis

Python Pandas for data analysis



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Question 1

What is Pandas primarily used for?

  • Creating games

  • Data manipulation and analysis

  • Building websites

  • Image editing

Question 2

Which of the following libraries is Pandas built on top of?

  • Matplotlib

  • Seaborn

  • NumPy

  • TensorFlow

Question 3

What is the command to install Pandas?

  • pip get pandas

  • pandas install

  • import pandas

  • pip install pandas

Question 4

What can be used to create a DataFrame in Pandas?

  • Only CSV files

  • Only SQL database

  • Lists, dictionaries or data from files

  • Only Excel files

Question 5

what is a Pandas series


  • A table with rows and columns

  • A one-dimensional labeled array

  • A list of strings

  • A chart for plotting

Question 6

Which NumPy function is often used to create data for a Pandas Series?

  • np.series()

  • np.make_array()

  • np.array()

  • np.series_array()

Question 7

How can you select a specific column from a DataFrame?

  • df.select_column("ColumnName")

  • df.get_column("ColumnName")

  • df["ColumnName"]

  • df.column("ColumnName")

Question 8

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

  • df.filter(condition)

  • df.select_rows(condition)

  • df[condition]

  • df.filter_rows(condition)

Question 9

What is the purpose of the describe() method in Pandas?

  • To describe the data types of columns

  • To display summary statistics of a DataFrame

  • To provide information about missing values

  • To describe the structure of a DataFrame

Question 10

How can you drop a column from a DataFrame in Pandas?

  • df.remove_column("ColumnName")

  • df.drop_column("ColumnName")

  • df.remove("ColumnName", axis=1)

  • df.drop("ColumnName", axis=1)

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