12.5: Key Terms
- Page ID
- 58345
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Key Terms and Definitions
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pandas — Python library providing DataFrame structures for data manipulation and analysis.
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NumPy — Python library for fast numerical array operations underlying much of the scientific stack.
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scikit-learn — Python ML library with consistent API for classification, regression, clustering, and preprocessing.
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Jupyter Notebook — Interactive document combining live code, narrative text, equations, and visualization outputs.
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dplyr — R package providing a "grammar of data manipulation" with verbs like filter, mutate, summarize.
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ggplot2 — R visualization package based on the Grammar of Graphics for layered, declarative chart building.
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tidyverse — A collection of R packages (dplyr, ggplot2, tidyr, etc.) sharing a common design philosophy.
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R Markdown — A document format combining R code, narrative, and outputs for reproducible reports.
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Window Function — A SQL function that performs calculations across rows related to the current row without collapsing groups.
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CTE — Common Table Expression — a named temporary result set in SQL defined with the WITH clause.
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DataFrame — A tabular data structure with labeled rows and columns, used in both pandas and R.
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Vectorized Operation — Applying an operation to an entire array/column at once rather than looping element-by-element.
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Pipe Operator — The %>% (R) or | (pandas) syntax for chaining data transformations in a readable sequence.