figure - visualizing wine alcohol content and ph level distributions based on quality ratings the boxplots depicted in figure - show us stark differences in wine alcohol content distributions based on wine quality as compared to ph levelswhich look to be between and in fact if you look at the mean and median values for ph levels across the three groupsit is approximately across the three groups as compared to alcohol %which varies significantly can you find our more interesting patterns and hypothesis with other features from this datagive it tryunivariate analysis this is perhaps one of the easiest yet core foundational step in exploratory data analysis univariate analysis involves analyzing data such that at any instance of analysis we are only dealing with one variable or feature no relationships or correlations are analyzed among multiple variables the simplest way to easily visualize all the variables in your data is to build some histograms the following snippet helps visualize distributions of data values for all features while histogram may not be an appropriate visualization in many casesit is good one to start with for numeric data red_wine hist(bins= color='red'edgecolor='black'linewidth= xlabelsize= ylabelsize= grid=falseplt tight_layout(rect=( )rt plt suptitle('red wine univariate plots' = = fontsize= white_wine hist(bins= color='white'edgecolor='black'linewidth= xlabelsize= ylabelsize= grid=falseplt tight_layout(rect=( )wt plt suptitle('white wine univariate plots' = = fontsize=