Python · Theory

SimpleImputer

Theory

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SimpleImputer

SimpleImputer is a specialised library. Say what job it does in one line, then one tiny call you would write. Don’t fake a full ML pipeline on a fresher page.

SimpleImputer: PyTorch = tensors/models. OpenCV = images. SimpleImputer = fill missing numbers. Folium = maps. Spark/MLlib = big data. nsetools = market quotes. Grid search = try hyper-parameters. scraping = fetch HTML then parse.

Viva for SimpleImputer — purpose + one function name + one caution (API keys, missing values, robots.txt).

Output — [90, 85.0, 80]. Mean fill for missing — SimpleImputer does that.

Exam tip

What it does + one API name + one caution.

Example

# SimpleImputer
marks = [90, None, 80]
fill = sum(m for m in marks if m is not None) / 2
print([fill if m is None else m for m in marks])

Output: [90, 85.0, 80]. Mean fill for missing — SimpleImputer does that.

Short notes

DefSimpleImputer — one job, one library.
RuleSimpleImputer — purpose + one call.
TrapSimpleImputer — copying a huge notebook without explaining one line.

Python · Theory

SimpleImputer

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Theory

108/268

SimpleImputer

SimpleImputer is a specialised library. Say what job it does in one line, then one tiny call you would write. Don’t fake a full ML pipeline on a fresher page.

Viva for SimpleImputer — purpose + one function name + one caution (API keys, missing values, robots.txt).

Output — [90, 85.0, 80]. Mean fill for missing — SimpleImputer does that.

Exam tip

What it does + one API name + one caution.

Example

# SimpleImputer
marks = [90, None, 80]
fill = sum(m for m in marks if m is not None) / 2
print([fill if m is None else m for m in marks])

Output: [90, 85.0, 80]. Mean fill for missing — SimpleImputer does that.

Short notes

DefSimpleImputer — one job, one library.
RuleSimpleImputer — purpose + one call.
TrapSimpleImputer — copying a huge notebook without explaining one line.

SimpleImputer

Example

Short notes

Questions

SimpleImputer

Example

Short notes

Questions