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Data Science Dojo <br/>
Copyright (c) 2019 - 2020
---
**Level:** Beginner <br/>
**Recommended Use:** Classification <br/>
**Domain:** Health/Social Sciences <br/>
---
### Accidental Drug Related Deaths in Connecticut, US
---
![](IllegalDrugAbuse.jpg)
---
The Connecticut Deaths due to Drugs Dataset contains information about 5106 people who died due to drug overdose between 2012 and 2018 in Connecticut, US.
The dataset includes data related to the age, race, gender, place of residence of the victims as well as the drugs they overdosed on. This information can be used to understand if drug use is prevalent in a specific area or city, drug use by individuals of different age groups and races as well as the popularity of different types of drugs.
This dataset is recommended for exploring data visualization techniques, clustering techniques and implementing regression models to predict how drug use may increase over time.
---
### Data Dictionary
| Column Number | Attribute | Attribute Description | Data Type |
| ------------- | ------------------- | ----------------------------------------------------------------- | --------- |
| 1 | ID | Row ID | Text |
| 2 | Date | Date | Date/Time |
| 3 | DateType | Type of Date in Column 2 <br>[Date of Reporting ot Date of Death] | Text |
| 4 | Age | Age of Patient | Numeric |
| 5 | Sex | Sex of Patient | Text |
| 6 | Race | Race of Patient | Text |
| 7 | ResidenceCity | City of Residence | Text |
| 8 | ResidenceCounty | County of Residence | Text |
| 9 | ResidenceState | State of Residence | Text |
| 10 | DeathCity | City of Death | Text |
| 11 | DeathCounty | County of Death | Text |
| 12 | Location | Location of Death [Hospital or Residence] | Text |
| 13 | LocationifOther | Location of Death if Not Hospital or Residence | Text |
| 14 | DescriptionofInjury | Cause of Death | Text |
| 15 | InjuryPlace | Place of Event that caused Death | Text |
| 16 | InjuryCity | City of Event that caused Death | Text |
| 17 | InjuryCounty | County of Event that caused Death | Text |
| 18 | InjuryState | State of Event that caused Death | Text |
| 19 | COD | Detailed Cause of Death | Text |
| 20 | OtherSignifican | Other Significant Injuries that may have lead to Death | Text |
| 21 | Heroin | Drug Found in Body [Y/N] | Text/Bool |
| 22 | Cocaine | Drug Found in Body [Y/N] | Text/Bool |
| 23 | Fentanyl | Drug Found in Body [Y/N] | Text/Bool |
| 24 | FentanylAnalogue | Drug Found in Body [Y/N] | Text/Bool |
| 25 | Oxycodone | Drug Found in Body [Y/N] | Text/Bool |
| 26 | Oxymorphone | Drug Found in Body [Y/N] | Text/Bool |
| 27 | Ethanol | Drug Found in Body [Y/N] | Text/Bool |
| 28 | Hydrocodone | Drug Found in Body [Y/N] | Text/Bool |
| 29 | Benzodiazepine | Drug Found in Body [Y/N] | Text/Bool |
| 30 | Methadone | Drug Found in Body [Y/N] | Text/Bool |
| 31 | Amphet | Drug Found in Body [Y/N] | Text/Bool |
| 32 | Tramad | Drug Found in Body [Y/N] | Text/Bool |
| 33 | Morphine_NotHeroin | Drug Found in Body [Y/N] | Text/Bool |
| 34 | Hydromorphone | Drug Found in Body [Y/N] | Text/Bool |
| 35 | Other | Drug Found in Body [Y/N] | Text/Bool |
| 36 | OpiateNOS | Drug Found in Body [Y/N] | Text/Bool |
| 37 | AnyOpioid | Drug Found in Body [Y/N] | Text/Bool |
| 38 | MannerofDeath | Manner of Death | Text |
| 39 | DeathCityGeo | City of Death | Text |
| 40 | ResidenceCityGeo | City of Residence | Text |
| 41 | InjuryCityGeo | City of Injury | Text |
---
### Acknowledgement
This data set has been sourced from the [US Government's
Open Data Initiative](https://data.gov) [Accidental Drug Related Deaths Dataset](https://catalog.data.gov/dataset/accidental-drug-related-deaths-january-2012-sept-2015).
The Open Data Initiative page mentions the following as the original source of the
data set:
*Local Government, Connecticut*
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Data Science Dojo <br/>
Copyright (c) 2019 - 2020
---
**Level:** Beginner <br/>
**Recommended Use:** Regression/Classification <br/>
**Domain:** Transportation and Mobility <br/>
---
## Birmingham Parking Dataset
![](ParkingBirmingham.jpg )
---
The Birmingham Parking Dataset is a simple beginner level dataset with 4 columns and 35718 rows. The dataset contains information about the number of cars parked in 30 parking areas around Birmingham at different times of the day between October to December 2016.
The information in the dataset can be used to understand driving patterns of Birmingham with respect to time and date and be used for efficient planning of new parking facilities.
---
### Data Dictionary
| Column Number | Attribute | Attribute Description | Data Type |
|---------------|------------------|---------------------------------------|-----------|
| 1 | SystemCodeNumber | Parking Lot ID | Text |
| 2 | Capacity | Maximum Capacity of the Parking Lot | Numeric |
| 3 | Occupancy | Number of Cars Parked at Time Instant | Numeric |
| 4 | LastUpdated | Time Stamp at which data was updated | Date/Time |
---
### Acknowledgement
This data set has been sourced from the Machine Learning Repository of
University of California, Irvine [Parking Birmingham Dataset (UC
Irvine)](https://archive.ics.uci.edu/ml/datasets/Parking+Birmingham). <br/><br/>
The UCI page mentions the following publication as the original source of the
data set:
*Stolfi, Daniel H. & Alba, Enrique & Yao, Xin. (2017). Predicting Car Park Occupancy Rates in Smart Cities. 107-117. 10.1007/978-3-319-59513-9_11.*
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Data Science Dojo <br/>
Copyright (c) 2019 - 2020
---
**Level:** Advanced <br/>
**Recommended Use:** Classification <br/>
**Domain:** Neuroscience/Healthcare <br/>
---
## EEG Eye State Dataset
![](BrainScanviaEEG.jpg)
---
The EEG Eye State Dataset is an advanced dataset of EEG (brainwave) Signals recorded to study the EEG activity of the brain with the eyes closed and open.
The data was recorded via the Emotiv Epoc+ EEG Headset with the subject having their eyes open and closed. The Emotiv Epoc+ EEG Headset has 14 electrodes placed at different areas of the scalp. Each row contains electrical signals generated by the brain gathered from the electrodes.
This data set can be used to explore which areas of the brain are active when a subject is receiving visual stimuli. This dataset is recommended for practicing classification models.
---
### Data Dictionary
| Column Number | Attribute | Attribute Description | Data Type |
| ------------- | ---------------------------- | -------------------------------------------------------- | --------- |
| 1 | ATTRIBUTE AF3 NUMERIC | Data from EEG Sensor placed at AF3 Location on the Skull | Numeric |
| 2 | ATTRIBUTE F7 NUMERIC | Data from EEG Sensor placed at F7 Location on the Skull | Numeric |
| 3 | ATTRIBUTE F3 NUMERIC | Data from EEG Sensor placed at F3 Location on the Skull | Numeric |
| 4 | ATTRIBUTE FC5 NUMERIC | Data from EEG Sensor placed at FC5 Location on the Skull | Numeric |
| 5 | ATTRIBUTE T7 NUMERIC | Data from EEG Sensor placed at T7 Location on the Skull | Numeric |
| 6 | ATTRIBUTE P7 NUMERIC | Data from EEG Sensor placed at P7 Location on the Skull | Numeric |
| 7 | ATTRIBUTE O1 NUMERIC | Data from EEG Sensor placed at O1 Location on the Skull | Numeric |
| 8 | ATTRIBUTE O2 NUMERIC | Data from EEG Sensor placed at O2 Location on the Skull | Numeric |
| 9 | ATTRIBUTE P8 NUMERIC | Data from EEG Sensor placed at P8 Location on the Skull | Numeric |
| 10 | ATTRIBUTE T8 NUMERIC | Data from EEG Sensor placed at T8 Location on the Skull | Numeric |
| 11 | ATTRIBUTE FC6 NUMERIC | Data from EEG Sensor placed at FC6 Location on the Skull | Numeric |
| 12 | ATTRIBUTE F4 NUMERIC | Data from EEG Sensor placed at F4 Location on the Skull | Numeric |
| 13 | ATTRIBUTE F8 NUMERIC | Data from EEG Sensor placed at F8 Location on the Skull | Numeric |
| 14 | ATTRIBUTE AF4 NUMERIC | Data from EEG Sensor placed at AF4 Location on the Skull | Numeric |
| 15 | ATTRIBUTE eyeDetection [0/1] | State of Eye <br>[0: Eye is Open, 1: Eye is Closed] | Numeric |
---
#### EEG Headset Electrode Placement
![](EEGElectrodePlacement.png)
### Acknowledgement
This data set has been sourced from the Machine Learning Repository of
University of California, Irvine [EEG Eye State Dataset (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/EEG+Eye+State).
<br/>
The UCI page mentions the following as the original source of the
data set:
*Baden-Wuerttemberg Cooperative State University (DHBW), Stuttgart, Germany*
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EEG Steady State Evoked Potential Dataset/A026SB1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A026SB2_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A026SB3_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A026SM1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A026SV1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A027SB1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A027SB2_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A027SB3_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A027SM1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A027SV1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A028SB1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A028SB2_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A028SB3_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A028SM1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A028SV1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A029SB1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A029SB2_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A029SB3_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A029SM1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A029SV1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A030SB1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A030SB2_2.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A030SB3_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A030SM1_1.csv 0 → 100644
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EEG Steady State Evoked Potential Dataset/A030SV1_1.csv 0 → 100644
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Hepatitis C Virus (HCV) Classification Dataset/Hepatitis C Virus (HCV) Classification Dataset.csv 0 → 100644
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Interstate-94 (I-94) Traffic Volume Dataset/Metro_Interstate_Traffic_Volume.csv 0 → 100644
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Portugal 2019 Election Dataset/PortugalElectionData2019.csv 0 → 100644
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