Exploratory Data Analysis - Missing Data References
Lesson references
For supplemental reading material on this topic, check out the following resources:
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Academic Content (roughly sorted from least technical to most)
- Good summary of single vs. multiple imputation
- Flexible Imputation of Missing Data, 2nd ed.
- Pattern Submodel Paper from “Biostatistics”
- The prevention and handling of missing data
- Should you use a missing data indicator?
- Boston University Technical Report on Missing Data, Assumptions, and Applications
- Andrew Gelman Chapter on Missing Data - thorough and very good, but academic
Python
- Scikit-Learn Write-Up of Imputation
- Scikit-Learn SimpleImputer Class
- Scikit-Learn IterativeImputer Class note: this is experimental
- Scikit-Learn KNNImputer Class
- Scikit-Learn Imputation Examples
- MissingNo in Python
- MissingNo Paper
- KNNImputer or IterativeImputer
- Adding a missing indicator
- Imputing missing values before building an estimator