Data Science Asked on June 19, 2021
I have never worked with a Binary dataset (1 and 0) (True or False) so I’m unsure what kind of statistical tests I should run to draw up simple conclusions.
I’m doing a data science project and the company wants to know/understand what features/characteristics are important to decide whether or not a customer will renew their lease (last column in Graph). They want me to just perform basic/simple probability and statistical analysis on the dataset.
I’m working in a Juypter notebook (pandas, seaborm, numpy, matplotlib, sklearn). I would appreciate it if someone could help lead me in a direction to what kind of simple analysis I can run on binary data.
Heres a sample of the table:
| ID | Age 20-29 | Age 30-39 | Age 40-49 | Age 50 > | Lease Length < 1 year | Lease Length 1-2 Years | Lease Length > 3 Years | Late Payment | No Fine Violations | Credit Score Below 600 | Renews |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 312 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
| 313 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 |
| 314 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| 315 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 |
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