This half is a continuation of the earlier evaluation. Now that we’ve cleaned and ready the info, we transfer ahead with exploratory information evaluation (EDA) to uncover insights that can assist in mannequin constructing. If you wish to learn earlier half click on Part 1
On this part, the univariate and bivariate evaluation are carried out to find hidden insights from information, that additional helps in modelling evaluation.
3.1 Univariate Evaluation
3.1.1 Demographic and Clients account data associated Variables Evaluation
- The Gender variable is being analyzed right here, a categorical variable with two classes: female and male. The bar chart exhibits the proportion of every class, with virtually 50% of the pattern being feminine and 50% being male. The distribution is equally balanced.(As proven in determine 10)
- The Senior Citizen variable is being analyzed right here, a categorical variable with two classes: Sure (1) and No (0). The pie chart exhibits the proportion of every class, with virtually 84% of the shoppers are non-senior residents and solely 16% are senior residents. The distribution is skewed in direction of non…
