Analysing business detais for improvements Python is a very dynamic tool used in analyzing data. It is used globally by Data Analyst for givung busines insignts and making deductions to tell a story about a business records over time. The first thing to be done ids setting up your work environment. Jupyter Notebook is a very popular and very easy workspace for analysing data. There are other packages ie Pycharm, Spyder ets that are also used There are various steps involved in Data processing. These steps ate otherwise onown as Data Pre-processing. the steps include:
- Import libray/data sets: Before emberking on a project at all,pythin has some built in libraries which you have to import into your workspace for data preprocessing. You also need a dataset to tell a story about. This dataset could be retrived by various means.You also hav to determine which type of data you arre working in ie .xlsx,csv,html,sql etc.
- Clean and prepare data for analysis: Usually dataset are not clean. What we mean by not clean is that datasets might consist of empty cells which you can either fill up or drop. this step is very vital in data preprecessing.
- Manipulate pandas DataFrame There are a lot of libraries in python. In data pre processing ,Pandas is a very helpful library thar helps to reshape, reference, index, clean, fill etc our dataset .
- Summarize data:You need to to also summarise data to give insignt and to give approach of what to do with dataset
- Build machine learning models using scikit-learn: You also need to bud models to help in improving your results for beter prediction s and accuracy
Ive provided some Models here which you can look through and learn from. you can contact me via the details belor Contact: +2348178907119 E-Mail: mubarakshuaib3@gmail.com Profession:Data Analyst &Python developer