This content originally appeared on DEV Community and was authored by Abid
The life of a data analyst revolves around loading data through SQL serve, analyzing it using various Python packages, and finally creating the technical report. Sometimes these SQL queries can take a longer time to process as we are dealing with terabytes of data. In this fast-paced world, this strategy fails miserably and most analytics are moving away from traditional ways to doing data analytics. DuckDB solves all the issues, it is integrated with Python & R. It works similarly to SQLite and focuses on providing faster analytical queries.
Sample Code
res = duckdb.query(“SELECT sex, SUM(expected_recovery_amount) as Expected,
SUM(actual_recovery_amount) as Actual
FROM ‘bank_data.csv’
WHERE recovery_strategy LIKE ‘Level 4 Recovery’
GROUP BY sex
HAVING sex = ‘Female’”)
res.df()
Read full guide on Analytics Vidhya
This content originally appeared on DEV Community and was authored by Abid
Abid | Sciencx (2021-12-01T17:19:41+00:00) A Guide to Data Analytics with DuckDB. Retrieved from https://www.scien.cx/2021/12/01/a-guide-to-data-analytics-with-duckdb/
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