Series of 4 data analytics projects - summarized

1. Analysis of Credit Card
Application Data
A Data Scientist’s Approach

2. Data Clean-up
(wrangling)
The purpose is to clean-up the ‘Credit
Card Application’ dataset by removing
missing values and other out of place
characters from the dataset
1

3. Dataset in .txt
and .csv
formats
Excel conversion

4. Variables of
the Dataset

5. Basic
Statistics of
continuous
type variables

6. Imputing for
missing
values

7. Missing
values
successfully
replaced

8. Exploratory Data Analysis
Our purpose is to do a pre-analysis
examination of the clean ‘Credit Card
Application’ dataset.
2

9. P a ir p lo t o f six
co n t in u o u s
va ria b le s b y
n o m in a l
va ria b le A 1

10. P a ir p lo t o f
f o u r co n t in u o u s
va ria b le s b y
cla ssif ie r
va ria b le A 1 6

11. Measure of
correlation
between the
variables

12. Interactive Data
Visualization
Purpose is to extend the scope of our
diagnostic analysis by inviting all
stakeholders to participate in the
derivation of a plausible model.
3

13. A single
interactive
dashboard to
display the
scatter of the
variables

14. Machine Learning
4

15. De cisio n Tre e
Mo d e l: RO C -
A UC, Co n f u sio n
Ma t rix a n d
B a sic S t a t ist ics

16. Tre e
E n se m b le
Mo d e l: ROC -
A UC,
Co n f u sio n
Ma trix a n d
B a sic
S t a t ist ics

17. D e p l o ye d -
D e c i s i o n
Tr e e a n d
Tr e e
E n s e m b l e
M o d e l s

19. What next?
L e t u s s e e h o w w e c a n w o r k t o g e t h e r
C o n t a c t :
B a b a ; j o m b a b a . s 7 @ g m a i l . c o m ; + 1 2 4 0 - 3 7 4 - 3 3 8 5 .
V i s i t t h i s l i n k t o l e a r n m o r e