From the course: Python vs. R for Data Science
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Data exploration in Python vs. R
From the course: Python vs. R for Data Science
Data exploration in Python vs. R
- Data exploration is an important part of a data pipeline, as getting to know your data helps you make informed decisions on how to use the data and what actions need to be taken to prepare the data for your task. Let's say that you have a CSV file representing a grade book containing student's exam grades in a particular class. For some context, the teacher records each student's grade into the grade book after each exam. If a student misses an exam, the teacher does not record anything for that student leaving the corresponding cell empty and the student is given an opportunity to make it up. If they don't show up to the make-up, the corresponding cell remains empty. And at the end of the term, the teacher will replace it with a zero. Here's how that would look in Python. First, I've gone ahead and imported Python's pandas library and loaded in exam_grades.csv into a pandas data frame. By the way, I've included the CSV…
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