Data Science Library

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  Tests running on the command line.

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  Code for our two biggest functions.

Inspiration

We wanted to create a library that helps with the management of files with a tremendous amount of data within a programming language and without the need for external software like Excel. We wanted to create an easy way for people to analyze their data efficiently and from the command line if they wish to do so.

What it does

Our project is a python library, so it can be installed on your local machine and be used in any application or program you are working on. What this library offers are functions for the analysis of CSV files. The functions included in the program are flexible regarding their parameters, which gives the user freedom to work in a cleaner way and without having to write a lot of messy code.

How we built it

We built it entirely with python and its native properties that let you create your own library and modules. The only other module that is used within our library is python's native csv module that helped us reading the files.

Challenges we ran into

The biggest challenge we had was getting started. Setting up the correct folders and files so python would recognize our project as a library and we could install with pip was our biggest challenge while building the project, but we just had to research everything we need and that was all.

Accomplishments that we're proud of

We are proud of having implemented functions that are very flexible and powerful at the same time. We say that they are flexible because they handle errors pretty well without stopping the whole program and their parameters let the user have the freedom to decide exactly what it wants to do. And we say that they are powerful because they are able to run on large data sets without compromising much time.

What we learned

We learned a lot about how python works, especially the libraries that we use every time we build a program. It was also a very good opportunity to learn about working with CSV files on python and concepts of data science.

What's next for Data Science Library

We want to continue working on this project and implementing many more functions that will be useful to people working with big sets of data. We hope that his library becomes something truly useful in a professional and educational environment.

Built With

• python