Exploring Data Science with Python

What is the primary purpose of Python in data science?

• To manage databases and server infrastructure.

• To develop web applications and services.

• To create complex machine learning algorithms.

• To provide tools for data manipulation, analysis, and visualization.

Which library is commonly used for data manipulation in Python?

• Pandas

• Scikit-learn

• NumPy

• Matplotlib

What function is used to read a CSV file in pandas?

• fetch_csv

• read_csv

• import_csv

• load_csv

What is the difference between a list and a tuple in Python?

• Tuples are created using square brackets while lists use parentheses.

• Lists are faster than tuples in all operations.

• Lists can contain only numbers while tuples can contain any data type.

• The main difference is that lists are mutable and tuples are immutable.

How do you handle missing data in a pandas DataFrame?

• Ignore missing data and proceed with analysis.

• Use dropna(), fillna(), or interpolation methods to handle missing data.

• Use groupby() to handle missing data.

• Use mean() to replace missing values.

What is the purpose of the NumPy library in Python?

• The purpose of the NumPy library in Python is to facilitate numerical computing with powerful array and matrix operations.

• To manage databases and SQL queries.

• To create graphical user interfaces in Python.

• To handle web scraping and data extraction.

Which function is used to create a scatter plot in Matplotlib?

• bar()

• scatter()

• plot()

• line()

What is the significance of the 'train-test split' in machine learning?

• It is used to combine training and testing data for better results.

• It ensures that the model learns from all available data.

• The significance of the 'train-test split' is to evaluate model performance and prevent overfitting.

• It helps in increasing the size of the dataset.

How can you visualize the distribution of a dataset in Python?

• Visualize data using SQL queries

• Create a text file with data summaries

• Use Matplotlib or Seaborn to create histograms, box plots, or density plots.

• Use Excel to create pie charts

What is the role of the 'fit' method in machine learning models?

• The 'fit' method trains the model on the dataset.

• The 'fit' method evaluates the model's performance.

• The 'fit' method saves the model to a file.

• The 'fit' method generates predictions from the model.