Bringing data together is one of the most important features of any database tool. In this video, instructors are challenged to join two datasets together using common fields.
- Data is inherently messy and in this next challenge,…our instructor has to clean it up.…Datasets are stored in different formats,…sometimes as flat files with simple rows…and column relationships,…sometimes as key value pairs as found in JSON or XML files,…sometimes data is stored and distributed…with built-in relationships.…These are often found in SQL files.…To make things more complex,…data is also stored in various formats.…
For example, sometimes dates are stored as strings,…other times as the number of seconds…since January 1st, 1970, also known as the epoch.…Numbers can be stored as strings, integers, or floats.…Locations can be represented as longitude and latitude…or it can be defined as a zip code, county,…or a magnitude of other formats.…Because of this, datasets often need to be reformatted.…Data scientists refer to this as the extract,…transform, and load process, or ETL.…
Extraction is the simple operation of opening a data file.…The instructor did this in the previous chapter.…Transform is the process of converting data…
- Strengths and weaknesses of SQLite
- Creating a database
- Joining data sets
- Calculations with SQLite and Python
- Searching a database
- Subqueries and queries in SQLite
- CRUD operations in SQLite with R
Skill Level Intermediate
1. SQLite in Five Minutes
2. Create a Database
3. Join Two Datasets
4. Search a Database
5. Create, Read, Update, and Delete Operations
6. Averages and Calculations
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