(dthe th column lists the various odors of the mushroomsencoded as ' '' 'replace these with the names 'almond''creosote'etc (categories corresponding to each letter can be found on the websitealso replace the 'edibilitycategories 'eand 'pwith 'edibleand 'poisonous(emake contingency table cross-tabulating 'edibilityand 'odor(fwhich mushroom odors should be avoidedwhen gathering mushrooms for consumption(gwhat proportion of odorless mushroom samples were safe to eat change the type and value of variables in the nutri data set according to table and save the data as csv file the modified data should have eight categorical featuresthree floatsand two integer features it frequently happens that table with data needs to be restructured before the data can be analyzed using standard statistical software as an exampleconsider the test scores in table of students before and after specialized tuition table student scores student before after this is not in the standard format described in section in particularthe student scores are divided over two columnswhereas the standard format requires that they are collected in one columne labelled 'scorereformat (by handthe table in standard formatusing three features'score'taking continuous values'time'taking values 'beforeand 'after''student'taking values from to useful methods for reshaping tables in pandas are meltstackand unstack create similar barplot as in figure but now plot the corresponding proportions of males and females in each of the three situation categories that isthe heights of the bars should sum up to for both barplots with the same 'gendervalue [hintseaborn does not have this functionality built ininstead you need to first create contingency table and use matplotlib pyplot to produce the figure + the iris data setmentioned in section contains various featuresincluding 'petal lengthand 'sepal length'of three species of irissetosaversicolorand virginica