Data Analysis Project in Python
Using pandas to Explore a Dataset: • Calculate metrics about your data. • Perform basic queries and aggregations. • Discover and handle incorrect data, inconsistencies, and missing values. • Visualise your data with plots.
Task1: Setting up the Environment. Task2: Using the pandas Python Library. Task3: Get to Know Your Data. Task4: Data Access methods (loc and iloc). Task5: Querying the Dataset. Task6: Grouping and Aggregating your Data. Task7: Manipulating Columns. Task8: Specifying Data Types. Task9: Cleaning the Data. Task10: Data Visualisation.
References: pandas Docs: https://pandas.pydata.org/pandas-docs/stable/index.html Download Python: https://www.python.org/downloads/ How to install pip: https://www.liquidweb.com/kb/install-pip-windows/ Jupyter Notebook: https://realpython.com/jupyter-notebook-introduction/ Install pandas Python: https://pandas.pydata.org/pandas-docs/stable/getting_started/install.html Install Matplotlib: https://matplotlib.org/users/installing.html#installing-from-source Visualisation with pandas: https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html Tutorial inspiration (Real Python): https://realpython.com/pandas-python-explore-dataset/ Data Source: https://fivethirtyeight.com/ The raw data: https://raw.githubusercontent.com/fivethirtyeight/data/master/nba-elo/nbaallelo.csv