descriptive analysis

Table of Contents Introduction Data Quality Analysis Loans Customers Segmentation Law 26.951 Results Presence of Missing Values in the Dataset Presence of Missing Values in the Dataset Low Success Rate in Marketing Campaigns Risk of Default Among Borrowers Non-Compliance with Law 26.951 Introduction Language used: Python Libraries used Library Description pandas Data manipulation and analysis to work with structured data numpy For numerical operations to work on large and multi-dimensional arrays and matrices matplotlib....

Language used: R Database used: “listing.csv” from the website http://insideairbnb.com/get-the-data/ composed by a mix of 18 qualitative and quantitative variables and 3896 cases. Packages used: dplyr: to obtain a general descriptive analysis of the data. ggplot2: to create graphs ggmap: to be able to show maps RColorBrewer: to assign colors to the heatmap visualization osmdata: to obtain the geographic coordinates of the city of Bologna hrbrthemes: to obtain more ggplot themes Variables description:...