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+Data Science Dojo <br/>
+Copyright (c) 2016 - 2019
+
+---
+
+**Level:** Beginner <br/>
+**Recommended Use:** Classification Models<br/>
+**Domain:** Finance/Banking<br/> 
+
+## Qualitative Bankruptcy Data Set 
+
+### Predict Bankruptcy from Qualitative parameters from experts 
+
+---
+![](407.jpg)
+---
+
+This *intermediate* level data set has 250 rows and 7 columns.
+This dataset contains 6 qualitative parameters from experts which could be used to predict the bankruptcy.
+This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, and **classification modelling techniques**. 
+Feel free to explore the data set with multiple **supervised** and **unsupervised** learning techniques. The Following data dictionary gives more details on this data set:
+
+---
+
+### Data Dictionary 
+
+| Column   Position 	| Atrribute Name        	| Definition                                                   	| Data Type   	| Example 	| % Null Ratios 	|
+|-------------------	|-----------------------	|--------------------------------------------------------------	|-------------	|---------	|---------------	|
+| 1                 	| Industrial Risk       	| Industrial Risk (P: Positive, A: Average, N: Negative)       	| Qualitative 	| P, A, N 	| 0             	|
+| 2                 	| Management Risk       	| Management Risk (P: Positive, A: Average, N: Negative)       	| Qualitative 	| P, A, N 	| 0             	|
+| 3                 	| Financial Flexibility 	| Financial Flexibility (P: Positive, A: Average, N: Negative) 	| Qualitative 	| P, A, N 	| 0             	|
+| 4                 	| Credibility           	| Credibility (P: Positive, A: Average, N: Negative)           	| Qualitative 	| P, A, N 	| 0             	|
+| 5                 	| Competitiveness       	| Competitiveness (P: Positive, A: Average, N: Negative)       	| Qualitative 	| P, A, N 	| 0             	|
+| 6                 	| Operating Risk        	| Operating Risk (P: Positive, A: Average, N: Negative)        	| Qualitative 	| P, A, N 	| 0             	|
+| 7                 	| Class                 	| Class (B: Bankruptcy, NB: Non-Bankruptcy)                    	| Qualitative 	| B, NB   	| 0             	|
+---
+Following are the details of the qualitative risk factors which mentions their risk components:
+
+**i.Industry risk (IR):** 
+	Government policies and International agreements, 
+	Cyclicality, 
+	Degree of competition,				
+	The price and stability of market supply,
+	The size and growth of market demand,	
+	The sensitivity to changes in macroeconomic factors,
+	Domestic and international competitive power, 
+	Product Life Cycle.
+
+**ii.Management risk(MR):** 
+	Ability and competence of management, 
+	Stability of management,
+	The relationship between management/ owner, 
+	Human resources management, 
+	Growth process/business performance, 
+	Short and long term business planning, 
+	achievement and feasibility. 
+
+**iii.Financial Flexibility(FF):** 
+	Direct financing, 
+	Indirect financing, 
+	Other financing 
+
+**iv.Credibility (CR):**  
+	Credit history,  
+	reliability of information, 
+	The relationship with financial institutes.
+
+**v.Competitiveness (CO):**  
+	Market position, 
+	The level of core capacities, 
+	Differentiated strategy, 
+
+**vi.Operating Risk (OP):**  
+	The stability and diversity of procurement, 
+	The stability of transaction, 
+	The efficiency of production, 
+	The prospects for demand for product and service, 
+	Sales diversification,
+	Sales price and settlement condition, 
+	Collection of A/R,
+	Effectiveness of sale network.
+
+---
+### Acknowledgement
+
+This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Qualitative Bankruptcy Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Qualitative_Bankruptcy). 
+The UCI page mentions the following publication as the original source of the data set:
+
+*"The discovery of experts’	decision rules from qualitative bankruptcy data using genetic algorithms" by Myoung-Jong Kim, Ingoo Han*
+