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Boston City Housing Predictor Data
Data Science and Analytics
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About
Explaining data related to housing in Boston, providing attributes necessary for analysis and exploration of influencing factors. The collection includes details on socioeconomic metrics, environmental factors, and infrastructure accessibility across various tracts. Key factors covered are the per capita crime rate, proportions of land zoning and non-retail industry, air quality metrics (nitric oxide concentration), and property statistics like the average number of rooms per dwelling and the age of owner-occupied units. The dataset also maps housing proximity to the Charles River, weighted distances to five Boston employment centres, and the accessibility index for radial highways.
Columns
The dataset contains 14 distinct columns:
- crim: Per capita crime rate by town.
- zn: The proportion of residential land that is zoned for large lots (those exceeding 25,000 square feet).
- indus: The proportion of non-retail business acres located in each town.
- chas: A dummy variable indicating proximity to the Charles River (1 if the tract borders the river; 0 otherwise).
- nox: Nitric oxides concentration, measured in parts per 10 million.
- rm: The average number of rooms found per dwelling.
- age: The proportion of owner-occupied units that were constructed prior to 1940.
- dis: Weighted distances calculated to five primary Boston employment centres.
- rad: An index representing the accessibility to radial highways.
- tax: The full-value property-tax rate, measured per $10,000.
- ptratio: The pupil-teacher ratio by town.
- b: A variable reflecting socioeconomic metrics.
- lstat: A variable related to the percentage of the lower status population.
- medv: A variable indicating the median value of owner-occupied homes, measured in $1000s.
Distribution
This data is provided in a CSV file format named
BostonHousing.csv, with a size of 36.24 kB. It consists of 14 columns, all of which contain 506 valid records. The sources indicate that there are no missing or mismatched values across the fields. The data is static, with an expected update frequency of never.Usage
The data is ideal for several analytical and statistical applications:
- Data Analytics: Performing quantitative analysis on urban factors influencing housing attributes.
- Exploratory Data Analysis: Generating initial insights into the relationships between crime rates, pollution, and property characteristics.
- Data Visualization: Creating visual representations of geographical and socioeconomic patterns within Boston housing areas.
- Data Cleaning: The clean structure (0% missing data) makes it suitable for direct model input or educational practice.
- Data Storytelling: Building narratives around the impact of environmental and industrial factors on residential property values and town demographics.
Coverage
The data covers housing statistics and socioeconomic factors specific to Boston. Attributes are typically calculated at the town level or housing tract level. The metrics include measurements of residential zoning, industrial presence, air quality, proximity to major environmental features like the Charles River, and accessibility to employment and highways. The age variable provides context by tracking the proportion of owner-occupied units built before 1940.
License
CC0: Public Domain
Who Can Use It
- Academics and Students: Utilising the data for educational exercises in statistical modelling and regression analysis, often used as a benchmark dataset.
- Urban Researchers and Policy Analysts: Examining the effects of zoning laws, industrial locations, and accessibility on urban development and residential areas.
- Data Scientists: Building machine learning models to predict housing values or understand the driving forces behind per capita crime rates.
Dataset Name Suggestions
- Boston Socioeconomic Housing Metrics
- Boston City Housing Predictor Data
- Boston Urban Attributes and Property Statistics
- New England Housing Factors
Attributes
Original Data Source: Boston City Housing Predictor Data
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