Pandas!!! What I’ve Learned after my 1st On-site Technical Interview

Pandas!!! What I’ve Learned after my 1st On-site Technical Interview

Reflections on key text cleaning skills with Pandas str: I know a lot of people get nervous in interviews. Similarly, 8 out of 10 times in my interviews, I get ants in my pants.

Preface

I know a lot of people get nervous in interviews. Similarly, 8 out of 10 times in my interviews, I get ants in my pants. This meant forgetting the usual tricks I have in my pocket or missing some of the key knowledge I should have known. Recently, I did an on-site technical interview for a Business Intelligence internship role, and guess what? It was all: Pandas! Though the interview did not go as smoothly as I expected, I wanted to turn this experience into a reflection on what I think is crucial in Pandas, typically text data manipulation.

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Overview

This article will be on “Working with Text Data in Pandas, mainly functions in the “pandas.Series.str”. Most of the problem settings are similar to what I experience during the interview. As you go over the article, you will get the opportunity to review what you have learned and receive a friendly reminder if you are looking forward to a technical interview. If you are new to Pandas, I hope you can add the tricks illustrated in this article to your data science toolkit. Let’s get started and clean our way towards more structured data.

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FYI:

  • The article will be sorted into small problem sets and possible solutions following those problems (or what I used to tackle each problem).
  • This data set is a made-up sales data of “The Fruit” company to illustrate the possible scenarios you will be challenged in interviews, jobs, or data projects.

self-improvement interview tech data-science programming big data

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