IT Career Guides & Free Resources
Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
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Data Cleaning: A Practical Step-by-Step Guide
A step-by-step data cleaning guide on 541,909 real transaction lines: profiling before touching anything, removing duplicates, standardising messy text, fixing inconsistent categories, investigating extreme values, keeping a cleaning log, and validation checks that caught a problem the cleaning itself created.
Pandas Guide: DataFrames, Cleaning and Aggregation
One messy sales export, cleaned and summarised step by step with pandas: reading it with the right types, the values pandas silently turns into missing data, fixing text and number columns, removing duplicates, named aggregations with groupby, pivot tables that can hide gaps, and merges that check themselves.
Data Preprocessing: Cleaning Data the Right Way
Preprocessing for machine learning without score-inflating mistakes: splitting before anything learns from data, imputing while recording what was missing, standard versus robust scaling, encoding categories unseen in production, and one ColumnTransformer pipeline for all of it.
Excel Power Query: Cleaning Data Without Code
How to clean data in Excel with Power Query instead of formulas and manual edits: combining a folder of monthly exports, fixing data types and messy text, removing duplicates without the case-sensitivity trap, merging lookup tables, unpivoting wide layouts, and turning it all into a query you refresh each month.