Mini-project made during Ironhack's Data Analytics Bootcamp with the goal of showcasing data manipulation and cleaning techniques and also a brief part of Exploratory Data Analysis. After receiving a raw and messy .csv file, data wrangling techniques were used to prove if a few hypothesis set in the beggining were true or false, with the help of EDA. Set an hypothetical case study for and Environmental Agency to identify the US State with more shark attacks incidents and procceed with recomendations on how to act.
- Data Cleaning and Manipulation: checking and dropping null values / rows / columns, dealing with duplicates, formatting and filtering data;
- Combining and Structuring Data:
- Data Aggregation and Filtering;
- Libraries imported:
- Pandas: import, export the shark_attack.csv - baseline for the project - and manipulate data;
- matplotlib: plotting histograms to verify hypothesis;
- Numpy;
- Statistics.
- Pandas Documentation
- matplotlib Documentation
- .csv File with data;
- Duration: 5 minutes;
- Setting and verifying hypothesis;
- Technical process and mejor obstacles;
- Done with Microsoft Power Point