June 3, 2019


エクセルの応用スキルは、特に金融セクターでは未だに高い需要を誇るが、データサイエンスの分野では、Python がエクセルに対抗できるツールとして大きく伸びている。本記事ではこれまで議論されてこなかったであろう Python とエクセルの比較を行い、主にデータサイエンティストの目線に立ってPythonがエクセルよりも優れている点について考える。

Python が好まれる理由




Advanced Excel skills are still in high demand, especially in the financial sector. But, in the data science industry, Python is fast picking up as a competing tool against Excel. While there can be no grounds for comparing the two, in this article we set out the many overlapping areas that make Python a much-favoured tool over Excel, especially for data scientists.

Hence Comes Python

We have assiduously covered how Python is becoming one of the most preferred tools for data scientists. Python has different functionality when compared to Excel but can prove to be much more powerful when it comes to data analysis. While Python needs coding skills, it has been looked upon as a prerequisite for many quantitative roles. Companies are looking to hire new roles with Python skills with at least beginner-level proficiency. Though it involves coding, many experts believe that it is picking up fast an alternative for Excel. For instance, Excel user can sum up numbers in a column by using =SUM or sum up cells which meet specific criteria by using =IF or =IFS statement. All this can be done in Python as well, and a lot of other functionalities that Excel boasts.

Easy To Read: For many business users and data scientists, it may be quite difficult to read someone else’s spreadsheet. It becomes even more difficult for a person who has never used Excel in their life ever. If data analysts and data scientists use Python, it will allow for an easy preparation, analysis and visualisation in Python. If someone has left working on it at a certain point, someone else can easily pick it up as it involves universally defined coding.

Is Python The New MS Excel In Data Science?

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