spending_analyzer spending_analyzer/spending_analyzer.ipynb.
Jupyter, Python and Pandas spending view and analyzer. Load and combine statements downloaded from banks and credit card companies. Autocategorize from transaction description with user created keyword/category tables. Further filter,group,calculate and pivot data in Jupyter display.
- Load CSV statements into combined pandas DataFrame
- Provide mechanism to identify different statement types by known column names.
- Provide Adapter interface
- Provide mechanism to add new statement types and adapter interface
- Provide adapter implemtations for different statement types
- parse statements into required columns. rename columns etc...
- parse transaction descriptions or transaction category into 'AutoCategory' column
- With 12+ months of data Calculate previous calendar year's monthy mean per 'AutoCategory'
- Calculate current calendar year's monthy mean per 'AutoCategory'
- Pandas Pivot table, show current calendar years monthy spending per 'AutoCategory' with mean columns
Input
- Bank or credit card statements in CSV format
- Required columns(can be named differently): Date,Description,Amount
Output
- Combined Pandas DataFrame with required output columns: Date,Description,Amount,AutoCategory
- Jupyter displays of Pandas DataFrames