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πŸ“ˆ eganalze is a tool/library for analyzing Estateguru portfolios

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πŸ“ˆ eganalyze

eganalyze is a tool/library for analyzing Estateguru portfolios. It is still very much work in progress, check the open issues to see planned features or to contribute.

There is a web version that you can try here!

This tool is NOT affiliated or endorsed by, or in any way officially connected with Estateguru. The tool is provided without any warranty and does not guarantee correctness, see the license.

What can it do?

At this point the functionality is very limited. Currently it can

  • Enrich the CSV with

    • normalize column names
    • add column with loan ID (e.g. "EE6452")
    • add column with loan URL
  • Calculate the following key performance indicators

    • mean ltv
    • outstanding mean ltv
    • outstanding weighted mean ltv
    • mean interest rate
    • outstanding mean interest rate
    • outstanding weighted mean interest rate

How do i install it?

pip install eganalyze

Don't have Python? Don't want to install anything? Check the web version!

How do i use it?

  1. Change your Estateguru interface to english πŸ‡¬πŸ‡§

  2. Go to your Portfolio Overview and download the CSV file

  3. Run eganalyze on the file to print key performance indicators:

$ eganalyze analyze portfolio.csv
Mean interest rate: 11.04%
Outstanding mean interest rate: 10.79%
Outstanding weighted mean interest rate: 10.75%
Mean LTV: 54.23%
Outstanding mean LTV: 54.35%
Outstanding weighted mean LTV: 54.11%

Advanced usage

$ eganalyze --help
Usage: eganalyze [OPTIONS] COMMAND [ARGS]...

Options:
  --version  Show the version and exit.
  --help     Show this message and exit.

Commands:
  analyze  Analyze given portfolio and print key performance indicators
  process  Normalize, enrich, process CSV and output to file

Use as a library

Simply pass a pandas dataframe of the CSV to the EgData class:

>>> import pandas as pd
>>> from eganalyze.lib import EgData
>>> df = pd.read_csv('/path/to/your/portfolio.csv')
>>> data = EgData(df)
>>> data.outstanding_mean_interest_rate
11.353522000232

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