Data Scientist — Technical Track

Module 1 · Python and SQL for Data · Lesson 1 of 1

Module overview — Python and SQL for Data

Module overview — Python and SQL for Data Goal : Query, join and manipulate data from several sources. Study time : Durée d'étude : 6 h Prerequisites : Aucun module préalable : savoir faire une somme et un filtre dans un tableur suffit pour commencer Running thread : Maricel, in Manila. Maricel is an analyst at a small mobile money operator in Manila. Transactions arrive as a CSV export, while customer data lives in a SQL table. When she combines the two, some customers appear twice and others vanish: the totals she gives her director are distorted without her noticing. In this module she learns to join without losing or duplicating anything, and to prove her totals with three checks. Lesson plan : 1. Express Python and pandas refresher 2. SQL: joins and multi-table aggregations 3. Combining a SQL database with a field CSV export What you will be able to do : - Filter and group a table of transactions, distinguishing a strict threshold from an inclusive one - Choose between an inner join and a left join according to the question asked - Calculate a total before and after a join and identify the cause of a gap End-of-module questions (Answer in writing, with figures.) : 1. What is the export total before the join, and what is the total after your corrected join? Give both amounts in PHP. 2. Why does the total sometimes go up after a join? Explain the cause in one sentence. 3. How many identifiers of the export are missing from the customers table in your exercise? Give a number. Module deliverables : - Your five-point reconciliation table on the twelve transactions - Your three-check join control sheet - Your corrected SQL query for subscribers, complaints and transactions

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