Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - Line Chart

The video tutorial guides viewers through creating a line chart using Python libraries. It starts with importing numpy and matplotlib, then generates data for the X and Y axes using numpy functions. The tutorial demonstrates plotting the data with matplotlib and explains how to display the plot in different environments. It also covers adding labels and a title to the plot and provides a tip for suppressing unwanted output in notebook environments.

Which libraries are essential for creating a line chart in this tutorial?

• Pandas and Seaborn

• NumPy and Matplotlib

• SciPy and Plotly

• TensorFlow and Keras

What function is used to create evenly spaced data points for the X-axis?

• np.arange

• np.linspace

• np.array

• np.random

What additional function is needed to display the plot when not using a notebook?

• plt.display

• plt.show

• plt.render

• plt.exhibit

How can you label the X-axis in a Matplotlib plot?

• plt.xlabel('input')

• plt.xaxis('input')

• plt.axisx('input')

• plt.labelx('input')

What is a method to suppress unwanted output in a notebook?

• End the line with a comma

• End the line with a period

• End the line with a colon

• End the line with a semicolon