E-Commerce Analysis

Personal project in which I analyse the data of an E-Commerce business. The project's Jupyter Notebook is uploaded above.

Language: Python

Packages/modules used:

• pandas
• numpy
• seaborn
• matplotlib.pyplot
• pyarrow
• warnings

Techniques/Concepts covered:

• Importing data (pd.read_feather)
• NULL/Duplicates handling
• Data manipulation: shape, split(), apply(), dtypes, astype(), unique(), groupby(), sum(), str.split(' '), str.get(), value_counts(), reset_index(), agg(), values, value_counts()[0:5].index, isin(), size(), unstack(), lambda, rename(), join(), merge()
• Data visualization: Bar charts, pie charts, twin axes plots, multi-line charts
• Defining functions
• Dataframe filtering
• E-Commerce analysis
• Sales analysis
• Frequency tables
• Pivoting dataframes
• Basket analysis/Reccommendation systems