This code analyzes voting data for the 2016 US Presidential election from three states: Wisconsin, Michigan, and Pennsylvania. The data is read from a CSV file and only counties with more than 10 votes for each of the three main candidates (Trump, Clinton, and Stein) are selected.
For each candidate, the second digit of their vote count is extracted, and the number of occurrences of each digit (0-9) is calculated using the effectifs function. The resulting frequency of each digit is stored in a DataFrame E.
The code is analyzing a data set of individuals in Benin, including their age and level of education. The code first plots a bar graph of the frequency of ages in the data set, which is sorted by age. Then, it categorizes each individual's age as either being a multiple of 5 or not. The mean values of the variables are calculated for each group of individuals based on their level of education, and a cross-tabulation is made to see the relationship between the "multiple of 5" and "level of education" variables. Finally, pie charts are made to visualize the proportion of individuals in each category of the cross-tabulation.