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Adding Autism dataset

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Data Science Dojo <br/>
Copyright (c) 2016 - 2019
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**Level:** Advanced <br/>
**Recommended Use:** Classification Models<br/>
**Domain:** Healthcare/Social Sciences <br/>
## Autism Screening Adult Data Set
### Detect Autistic Spectrum Disorder (ASD) cases
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![](79.jpg)
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This *advanced* level data set has Autistic Spectrum Disorder (ASD) Screening Test Data for 704 adults. There are 21 attributes in the dataset that include test takers'
demographics such as *Age*, *Gender*, *Ethnicity* etc. The screening test included 10 questions (A1 to A10) that test takers answered. In each of these 10 questions,
the test takers were given a statement with which they had to agree or disagree. For example, the statement at question A1 is "I often notice small sounds when other do not".
The test takers' responses to A1 and A10 are coded as binary values (0,1). Once the test taker has answered all 10 questions, his/her status on ASD is determined which
is recorded under **Class/ASD** variable. You can encouraged to explore the [ASD Test Mobile App](http://asdtests.com/#)
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:
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### Data Dictionary
| Column Position | Atrribute Name | Definition | Data Type | Example | % Null Ratios |
|------------------- |----------------- |----------------------------------------------------------------------------------------------------------------------------------------------------- |-------------- |------------------------------------ |--------------- |
| 1 | A1_Score | Question 1 Answer: Binary (0, 1) | Quantitative | 0, 1 | 0 |
| 2 | A2_Score | Question 2 Answer: Binary (0, 1) | Quantitative | 0, 2 | 0 |
| 3 | A3_Score | Question 3 Answer: Binary (0, 1) | Quantitative | 0, 3 | 0 |
| 4 | A4_Score | Question 4 Answer: Binary (0, 1) | Quantitative | 0, 4 | 0 |
| 5 | A5_Score | Question 5 Answer: Binary (0, 1) | Quantitative | 0, 5 | 0 |
| 6 | A6_Score | Question 6 Answer: Binary (0, 1) | Quantitative | 0, 6 | 0 |
| 7 | A7_Score | Question 7 Answer: Binary (0, 1) | Quantitative | 0, 7 | 0 |
| 8 | A8_Score | Question 8 Answer: Binary (0, 1) | Quantitative | 0, 8 | 0 |
| 9 | A9_Score | Question 9 Answer: Binary (0, 1) | Quantitative | 0, 9 | 0 |
| 10 | A10_Score | Question 10 Answer: Binary (0, 1) | Quantitative | 0, 10 | 0 |
| 11 | Age | Age in years | Quantitative | 24, 32, 40 | 1 |
| 12 | Gender | Gender (m: Male, f: Female) | Qualitative | "m", "f" | 0 |
| 13 | Ethnicity | List of common ethnicities (White-European, Latino, Others, Black, Asian, Middle Eastern, Pasifika, South Asian, Hispanic, Turkish) | Qualitative | "Middle-Eastern", "Asian", "Black" | 13 |
| 14 | Jundice | Whether the case was born with Jundice (Yes, No) | Qualitative | "yes", "no" | 0 |
| 15 | Austim | Whether any immediate family member has a PDD (Yes, No) | Qualitative | "yes", "no" | 0 |
| 16 | Country_of_res | Country of residence (List of countries) | Qualitative | "Austria", "Ireland", "Jordan" | 0 |
| 17 | Used_app_before | Whether the user has used the screening app before (Yes, No) | Qualitative | "yes", "no" | 0 |
| 18 | Result | Screening score: The final score obtained based on the scoring algorithm of the screening method used. This was computed in an automated manner | Quantitative | 5, 8, 10 | 0 |
| 19 | Age_desc | Age description | Qualitative | "18 and more" | 0 |
| 20 | Relation | Who is completing the test (Self, Parent, Health care professional, Relative, etc) | Qualitative | "Parent", "Self", "Relative" | 13 |
| 21 | Class/ASD | yes, no | Qualitative | "yes", "no" | 0 |
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### Acknowledgement
This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Autism Screening Adult Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Autism+Screening+Adult).
The UCI page mentions the following as the original source of the data set:
+ Fadi Fayez Thabtah, Department of Digital Technology, Manukau Institute of Technology, Auckland, New Zealand
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