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.
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.
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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