Inspiration
We sought to create something that allows individuals who aren't so data-savvy to work with and better understand their datasets.
What it does
Our program enables non tech professionals to get data driven result from csv files. DataLens allows the user to view the analytical usability of the columns, simple summary statistics, and a graphical analysis of their selected data. DataLens provides the mean, median, mode and standard deviation of a users selected dataset. Additionally, DataLens allows the user to choose between a histogram, box blot or scatter plot for graphical analysis. Everything is conducted locally, so any and all private data remains safe and confidential.
How we built it
We first integrated pandas and matplotlib into python. Next, we used pandas to generate the usability function, as well as the summary statistics. Then we used matplotlib to produce the different graphical views of the data. Finally, we did a lot of work to format the data to make it easier to understand and ensure the program could be used from the terminal.
Challenges we ran into
We ran into many challenges, from difficulties integrating the python libraries to creative blocks on what to even create for the Hackathon. While these problems have little connection to each other, they taught us that we often have to take a step back, breathe, and take a moment before returning to the problem.
Accomplishments that we're proud of
We created a functional way to analyze and work with large datasets despite no prior experience. Before this event, our only expertise was in vanilla python and we had no idea how to work with libraries or non .txt files. However we've surprised ourselves and learned an incredible amount about python through this event and we're very proud of that.
What we learned
We learned how to use python libraries, specifically pandas and matplotlib, and we learned how to think outside the box while thinking inside our capabilities. Most importantly, we learned that not every complex problem requires a complex solution
What's next for DataLens
In the future, we plan to integrate more options for our users to choose from to view their data graphically. Additionally, we plan to include more statistics on the analysis view and provide an option for more advanced users to perform more in-depth data analyses.
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