Da Types Of Data — Free Data Analytics Tutorial
Learn Da Types Of Data in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Da Types Of Data in Data Analytics with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
Written & reviewed by the Syllab.in Academic Team (CBSE/NCERT subject experts) · Updated
Da Types Of Data in Data Analytics
Data comes in different types, and understanding the type determines what analysis you can do. The wrong analysis on the wrong data type gives meaningless results.
Structured Data: Organised in rows and columns — like a spreadsheet or database table. Every row is a record, every column is a field. Examples: student marks database, UPI transaction records, cricket match scores. Easy to analyse with SQL and Pandas.
Unstructured Data: No fixed format — text, images, audio, video, social media posts. ~80% of all data in the world is unstructured. Harder to analyse — requires NLP for text, Computer Vision for images.
Quantitative vs Qualitative: Quantitative data is numbers you can calculate with (marks, temperature, price). Qualitative (categorical) data is labels or categories (city name, subject, gender). Different statistical methods apply to each.
Continuous vs Discrete: Continuous can take any value in a range (temperature: 36.7°C). Discrete takes only specific values (number of students: 30, not 30.5).
Da Types Of Data — Syntax
# Data types in programming vs data analytics: # int/float → Quantitative continuous # str (categories) → Qualitative nominal # bool → Binary categorical # date → Temporal data
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