We live in a time where data and data analysis are more and more activities such as trading, as data tells us a lot, e.g., which service is the most sought after or needed on the market, which trends are changing, or short-term predictions. The data is usually published online or in various digital formats. However, when we have access to vast amounts of data, the problem of their analysis arises. For my diploma work, I decided to create a web application to obtain data on politicians' speeches from the online platform parlameter.si and offer various means of analysis and visualizations of fetched data, considering the political affiliations of the individuals.
I developed the planned web application using the Python programming language. It is easy to use and enables fast development compared to other languages, also due to the many libraries of helpful software solutions. Python is also suitable for working with databases. I use the Python Dash library to build an online user interface for data analysis and visualization. It relies on a combination of the data we provide (Dash components), plotting data (Plotly graphs), and the connection between these two components (Callback). I use SQLite for building the database, as writing and searching for data in the database is very fast based on the data I will obtain from the website in the “.json” format. The developed web page with components in HTML markup language allows us to filter the data necessary for analysis and visualization. I will use Cascading Style Sheets (CSS) to design the look of the components of the web application.
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