{"id":2377,"date":"2022-07-06T16:55:18","date_gmt":"2022-07-06T11:25:18","guid":{"rendered":"https:\/\/codequotient.com\/blog\/?p=2377"},"modified":"2024-02-14T17:31:23","modified_gmt":"2024-02-14T12:01:23","slug":"python-interview-questions-data-science","status":"publish","type":"post","link":"https:\/\/codequotient.com\/blog\/python-interview-questions-data-science\/","title":{"rendered":"6 Python Interview Questions You Must Know Before Attending Data Science Interview"},"content":{"rendered":"

Do you want to be at the top tier of the Tech World?<\/strong> If yes, then we strongly recommend pursuing a career in Data Science.<\/p>\n

Data Scientist is the fastest-growing job opportunity today. With a bit of research<\/a>, we found out that Python<\/b> is important to nearly 90% of Data Scientist recruiters. All the recruiters are looking for basic to intermediate level knowledge of Python in the candidates. Now, this raises an interesting question.<\/p>\n

Why does a Data Scientist require Python?<\/b><\/h2>\n

\"Why-does-a-Data-Scientist-require-Python\"<\/p>\n

Those who are well versed in Data Science will have the answer already. But even if you aren’t, we’re here to the rescue. Data Science is not merely about compiling and analysing data<\/b>. It goes much deeper. Everything from handling enormous amounts of data to finding unique patterns, using advanced tools, and making typical decisions based on derived information comes under Data Science.<\/p>\n

As we said, a good Data Scientist<\/a> must be able to work with multiple tools on an advanced level. Therefore, when it comes to extensive data analysis or plotting, Python is the way. Python compiles large data<\/b> easily and even assists in creating sophisticated yet attractive plots.<\/p>\n

The simple syntax of Python makes it the easiest programming language. In addition, it has a plethora of libraries and built-in data types that make the tasks much more manageable.<\/p>\n

Top 6 Python Interview Questions for Data Science Interview<\/b><\/h2>\n

Assuming that you have a good grasp of Python and are ready to ace that interview, but they throw a spin ball! The problem with going for an interview without practising frequently asked questions is getting caught by surprise. It is possible that even though you know the answer to the interviewer’s question, you are stuck on how to phrase it.<\/p>\n

These are some common problems that all of us are bound to face, but only when we lack preparation. But there’s no need to panic as we’re here with the top Python interview questions<\/b> that a Data Scientist applicant can expect at the interview.<\/p>\n

1. Enlist the Data Types used in Python.<\/b><\/h3>\n

Python has a total of 6 built-in data types. These are –<\/p>\n