Prikaz podataka i tehnike vizualizacije

• Main Author: Smajić, Alma
• Other Authors: Miličić, Siniša
• Format: Bachelor Thesis
• Language: Croatian
• Published: Sveučilište Jurja Dobrile u Puli. Fakultet informatike u Puli. 2021
• Subjects: statistika; računalni prikaz podataka; tehnike vizualizacije; Python; Jupyter Notebook; Anaconda; Matplotlib; Seaborn; Plotly; Numpy; Statistics; computer data visualization; visualization techniques; DRUŠTVENE ZNANOSTI. Informacijske i komunikacijske znanosti. Informacijski sustavi i informatologija; SOCIAL SCIENCES. Information and Communication Sciences. Information Systems and Information Science; sami
• Online Access: https://zir.nsk.hr/islandora/object/unipu:6042; https://urn.nsk.hr/urn:nbn:hr:137:561738; https://zir.nsk.hr/islandora/object/unipu:6042/datastream/PDF

Svjesno ili ne, oduvijek i konstantno smo izloženi podacima. Za one koji su nam poznatiji ili srodniji struci klasificiramo u informacije koje zatim plasiramo dalje. Ipak, nije uvijek tako jer ponekad imamo mnoštvo podataka za koje ni sami ne znamo kako iz njih dobiti nešto jasno, a samim time i korisno. U prilog tome, razvojem programskih jezika i pripadajućih biblioteka vizualizacija postaje ključna pri radu s podacima. Prikladno potrebama ovog rada koriste se platforma Anaconda i programski jezik Python (sa bibliotekama: Matplotlib, Plotly, Seaborn i Numpy). Sve vizualizacije sadrže popratni kod i teorijsko objašnjenje, odnosno tumač. Consciously or not, always and constantly, we are exposed to ample data. For those which are familiar to us or more related to the chosen profession, we have accurately classified them into valuable information that we then place further. However, this is not inevitably the case. Every so often we retain data for which we ourselves do not know how to get something clear from them, and in time valuable. In addition, with the gradual development of modern programming languages and associated libraries, visualization becomes crucial when properly working with data. Appropriately, the needs of this academic paper are adequately managed by the leading Anaconda platform and the Python programming language (With libraries: Matplotlib, Plotly, Seaborn, and Numpy). All visualizations precisely contain an accompanying code and a theoretical explanation.