From 0dee162cfc36b5bf255d412281343d20eed924c8 Mon Sep 17 00:00:00 2001 From: nilbuild <4921183+nilbuild@users.noreply.github.com> Date: Tue, 13 Oct 2026 09:10:01 +0000 Subject: [PATCH] chore: sync content to repo --- .../content/environment-setup@8Z20apU8ugXwdH8rRZAcr.md | 4 ++-- .../content/indexing--slicing@mAOljEWt_0Hb9jLBKuc-H.md | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/roadmaps/python-data-analysis/content/environment-setup@8Z20apU8ugXwdH8rRZAcr.md b/roadmaps/python-data-analysis/content/environment-setup@8Z20apU8ugXwdH8rRZAcr.md index c10d7f945..fc1fa768c 100644 --- a/roadmaps/python-data-analysis/content/environment-setup@8Z20apU8ugXwdH8rRZAcr.md +++ b/roadmaps/python-data-analysis/content/environment-setup@8Z20apU8ugXwdH8rRZAcr.md @@ -4,5 +4,5 @@ Setting up a proper Python environment for data analysis involves choosing a pac Visit the following resources to learn more: -- [@video@Setting Up A Python Environment for Data Analysis and Machine Learning](https://www.youtube.com/watch?v=NDFMa5FSQuI) -- [@article@How to Set Environment Variables in Python (Step-by-Step)](https://roadmap.sh/python/set-environment-variable) \ No newline at end of file +- [@article@How to Set Environment Variables in Python (Step-by-Step)](https://roadmap.sh/python/set-environment-variable) +- [@video@Setting Up A Python Environment for Data Analysis and Machine Learning](https://www.youtube.com/watch?v=NDFMa5FSQuI) \ No newline at end of file diff --git a/roadmaps/python-data-analysis/content/indexing--slicing@mAOljEWt_0Hb9jLBKuc-H.md b/roadmaps/python-data-analysis/content/indexing--slicing@mAOljEWt_0Hb9jLBKuc-H.md index 6c0eba228..e7707d056 100644 --- a/roadmaps/python-data-analysis/content/indexing--slicing@mAOljEWt_0Hb9jLBKuc-H.md +++ b/roadmaps/python-data-analysis/content/indexing--slicing@mAOljEWt_0Hb9jLBKuc-H.md @@ -1,6 +1,6 @@ -# Array Operations +# Indexing & Slicing -NumPy supports a wide range of array operations: element-wise arithmetic, aggregation functions (`sum`, `mean`, `std`, `min`, `max`), reshaping, stacking, and splitting. These operations are vectorized, meaning they apply to the entire array at once without explicit loops, making them highly efficient. +Indexing and slicing are techniques used to access, extract, or modify specific elements within a NumPy array. Indexing refers to selecting a single item based on its position, typically using square brackets and integer coordinates, while slicing allows you to retrieve a contiguous subset of the array by defining a range of indices using a colon separator. These methods provide a flexible way to work with parts of a dataset, such as selecting individual rows, specific columns, or smaller multi-dimensional segments without needing to iterate through the entire structure. Visit the following resources to learn more: