we can repeat this for the other variables (see exercise and save this modified data frame as csv fileby using the pandas method to_csv nutri to_csv ('nutri csv ',index false summary tables it is often useful to summarize large spreadsheet of data in more condensed form table of counts or table of frequencies makes it easier to gain insight into the underlying distribution of variableespecially if the data are qualitative such tables can be obtained with the methods describe and value_counts as first examplewe load the nutri dataframewhich we restructured and saved (see previous sectionas 'nutri csv'and then construct summary for the feature (column'fatnutri pd read_csv ('nutri csv 'nutri ['fat 'describe (count unique top sunflower freq namefat dtype object we see that there are different types of fat used and that sunflower has the highest countwith out of individuals using this type of cooking fat the method value_counts gives the counts for the different fat types nutri ['fat 'value_counts (sunflower peanut olive margarine isio butter duck colza namefat dtype int column labels are also attributes of dataframeand nutri fatfor exampleis exactly the same object as nutri['fat'