In assignment 2 of ML, housing price dataset: there are 81 columns in which 1 housing price is DV and remaining 80 are IV ,do we need to plot 80 graphs?

If you have 80 independent variables in your housing price dataset, plotting 80 individual graphs for each independent variable would not be practical or necessary.

Instead, there are more efficient ways to explore the relationships between the independent variables and the dependent variable. One way is to use correlation matrices, which can show the pairwise correlations between all variables in the dataset, including the dependent variable. This can help you identify which independent variables may be most strongly related to the dependent variable.

Another way is to use visualization techniques such as scatterplots or heat maps to explore the relationships between the independent variables and the dependent variable. For example, you could create scatterplots of each independent variable against the dependent variable to see if there are any obvious trends or patterns in the data. Alternatively, you could create a heatmap showing the correlation coefficients between each pair of variables in the dataset, which can help identify which variables are most strongly correlated with the dependent variable.

Ultimately, the choice of visualization technique will depend on the specific goals of your analysis, as well as the nature of the data you are working with. However, plotting individual graphs for each independent variable is not typically necessary or practical.