Python Fundamentals for Analysis
Practical Python for people who analyse data: the core building blocks, working with tabular data in a dataframe, vectorised thinking, missing values, grouping, quick charts, calm debugging and reproducible working habits.
52m
Общее время
4
Уровни компетенций
12
Уроки
Чему вы научитесь
- Explain when an analysis outgrows a spreadsheet and what Python adds in repeatability, volume and auditability
- Use variables, types, lists, dictionaries, indexing, loops, conditionals and functions to build a working script
- Apply the load, inspect, clean, transform, summarise and export sequence to a CSV file using a dataframe
- Replace row-by-row loops with vectorised column operations and handle missing values deliberately
- Group and aggregate data, report counts alongside averages, and plot a quick chart to sanity-check results
- Read a traceback bottom-up to debug calmly, and work reproducibly with version control, relative paths and pinned environments
Программа
Проходите уровни компетенций по порядку.
1
Awareness
- 3mWhy Analysts Reach for PythonЗнания
- 2mVariables, Types, Lists and DictionariesЗнания
- 7mAwareness Check: Why Python, and What It Is Made OfОценка
2
Knowledge
- 2mLoops, Conditionals and FunctionsЗнания
- 2mFrom CSV to DataframeЗнания
- 8mKnowledge Check: Logic and the Dataframe WorkflowОценка
3
Skill
- 3mVectorised Thinking, Missing Values and GroupingЗнания
- 3mBuild a Repeatable Analysis ScriptЗадание
- 8mSkill Check: Working with Real DataОценка
4
Mastery
- 3mDebugging Calmly and Working ReproduciblyЗнания
- 3mMake an Analysis Reproducible and Hand It OverЗадание
- 8mMastery Check: Debugging and Reproducibility JudgementОценка
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