Exploring Python Libraries for Data Science

What is the purpose of data visualization in data analysis?

• To perform statistical calculations

• To store data in a database

• To create complex algorithms

• The purpose of data visualization in data analysis is to make complex data more accessible and understandable.

Name two common data visualization libraries in Python.

• Pandas, NumPy

• Matplotlib, Seaborn

• Plotly, Bokeh

• TensorFlow, Keras

How do you create a Pandas Series from a list?

• my_series = pd.create_series(my_list)

• my_series = pd.Series(my_list, index=my_index)

• my_series = pd.Series.from_list(my_list)

• import pandas as pd; my_series = pd.Series(my_list)

What method would you use to access the first element of a Pandas Series?

• series.get(0)

• series.iloc[0]

• series.first()

• series[0]

How can you transpose a DataFrame in Pandas?

• df.transposeData()

• df.switch()

• df.T or df.transpose()

• df.flip()

What is the difference between a Series and a DataFrame in Pandas?

• A Series is a table-like structure; a DataFrame is a list of values.

• A Series is one-dimensional; a DataFrame is two-dimensional.

• A Series is used for data visualization; a DataFrame is used for data analysis.

• A Series can hold multiple data types; a DataFrame can only hold one.

Describe how to create a NumPy array from a Python list.

• Use 'np.create_array(your_list)' to generate a NumPy array from a Python list.

• Apply 'np.array_list(your_list)' to transform a Python list into a NumPy array.

• Convert the list using 'np.tolist(your_list)' to make a NumPy array.

• Use 'np.array(your_list)' to create a NumPy array from a Python list.

What function is used to create a 2D NumPy array (matrix)?

• numpy.matrix()

• numpy.ndarray()

• numpy.array()

• numpy.create_2d_array()

How do you access a specific element in a NumPy matrix?

• Use matrix[row + col] to access the element.

• Use matrix[row, col] to access the element at the specified row and column.

• Access elements using matrix[row][col].

• Use matrix.get(row, col) to retrieve the element.

What is the purpose of the 'plot' function in Matplotlib?

• To create 3D surface plots.

• To create 2D line plots.

• To generate random data for analysis.

• To display images and graphics.