A Practical Approach to Timeseries Forecasting Using Python - Data Visualization with Customized Features Selection

The video tutorial explains how to sort a dataframe of countries by population in descending order, display the top five countries, transpose the data, and plot it using a line graph. The tutorial also covers setting the index as an integer and provides a preview of upcoming topics like area plots and histograms.

What is the first step to ensure when plotting countries with the highest population?

• Create a new data frame object

• Ensure 'in place' is true for all commands

• Sort the data frame in ascending order

• Set 'in place' to false

Which command is used to display the top five countries in the data frame?

• DF.tail()

• DF.head()

• DF.show()

• DF.sort()

Before plotting, what transformation is applied to the data frame?

• Transpose

• Normalization

• Aggregation

• Standardization

What should be done to the index of the data frame before plotting?

• Convert it to string

• Map it to integer

• Leave it unchanged

• Remove the index

What type of plot is used to visualize the top five countries?

• Bar plot

• Scatter plot

• Line plot

• Pie chart

What is the title given to the plot of the top five countries?

• Top Five Countries Population

• Population Trends of Top Countries

• Immigration of Top Five Countries

• Countries with Most Immigrants

What labels are used for the axes in the plot?

• X: Regions, Y: Immigrants

• X: Time, Y: Growth Rate

• X: Countries, Y: Population

• X: Years, Y: Number of Immigrants