How to Analyze Income Dataset Using Pandas and Visualization Libraries
In this blog, we will take the income dataset and analyze all aspects of it. The dataset provided predictive features like age, education, employment status, marital status, etc. to predict if the salary is greater than $50k.
Download the Income Dataset
We can download adult dataset from Kaggle. We can follow the link below:
About Income Dataset
An individual’s annual income results from various factors. Intuitively, it is influenced by the individual’s education level, age, gender, occupation, and etc.
This is a widely cited KNN dataset. I encountered it during my course, and I wish to share it here because it is a good starter example for data pre-processing and machine learning practices.
Fields The dataset contains 16 columns Target filed: Income — The income is divide into two classes: <=50K and >50K Number of attributes: 14 — These are the demographics and other features to describe a person
Attribute Information:
- age: continuous.
2. workclass: Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked.
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