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Distributions in practice: histograms, KDEs, and when the mean deceives
Statistics often starts with a simple question:
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Data visualization that doesn’t lie: choosing the right plot for the question
A chart is not neutral merely because every number in it is technically correct.
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Correlation is not causation, but it’s also not nothing: reading correlation matrices right
A correlation matrix is one of the fastest ways to get a rough map of a numeric dataset.
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Outliers: detect, understand, and only then decide to delete
An outlier is a record that looks unusual relative to other observations. That definition says nothing about whether the record is wrong.
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Missing data is a message: patterns, mechanisms, and honest imputation
Missing values are often treated as an inconvenience: fill them, drop them, move on.
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First hour with a new dataset: a repeatable EDA checklist in pandas
A new dataset is not a blank canvas. It is the result of a pipeline: databases, APIs, spreadsheets, sensors, human input, and business processes. Every one of those sources can introduce problems.