Financedatabase

Latest version: v2.2.2

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2.2.0

This release features the introduction of the **FinanceFrame**. This is a DataFrame with extras, namely the function `to_toolkit`. As also visible in [this example](https://github.com/JerBouma/FinanceDatabase#perform-a-dupont-analysis-on-railroad-companies), the Finance Database can now directly convert the symbols to the [Finance Toolkit 🛠️](https://github.com/JerBouma/FinanceToolkit) making it possible to do combine the exploration of tickers from the Finance Database with the in-depth financial analysis from the Finance Toolkit.

As an example, it is possible to use both `.select()` and `.search()` and combine this with `.to_toolkit()`.

<img width="1463" alt="image" src="https://github.com/JerBouma/FinanceDatabase/assets/46355364/1e646236-8283-42f6-8a8c-0644bc7f0fec">

For fundamental data, you need to obtain an API Key from FinancialModelingPrep. This is used to gain access to 30+ years of financial statement both annually and quarterly. Note that the Free plan is limited to 250 requests each day, 5 years of data and only features companies listed on US exchanges.
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<b><div align="center">Obtain an API Key from FinancialModelingPrep <a href="https://site.financialmodelingprep.com/developer/docs/pricing/jeroen/">here</a>.</div></b>
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Through the link you are able to subscribe for the free plan and also premium plans at a **15% discount**. This is an affiliate link and thus supports the project at the same time. I have chosen FinancialModelingPrep as a source as I find it to be the most transparent, reliable and at an affordable price. I have yet to find a platform offering such low prices for the amount of data offered.

2.1.1

This release makes it possible to filter by multiple criteria for the same columns. Next to that, many company names are adjusted in the database that contained accented characters.

<img width="1122" alt="image" src="https://github.com/JerBouma/FinanceDatabase/assets/46355364/b88aa063-0863-4f11-81d3-b0cbc52f73af">

2.1.0

This release includes over 9.000 ISIN codes, more than 25.000 FIGI codes and more than 2.000 CUSIP codes. This is a start to not only allowing you to work with tickers (like MSFT which is Microsoft Corporation) but also with ISIN (US5949181045), FIGIs (BBG000BPHFS9) and CUSIP (594918104) codes.

Furthermore, I have also updated the exchange names being much more clear now. Lastly, made a small bug fix when you wish to work with the database locally.

2.0.0

I've improved this database not only by increasing the amount of symbols (from 180k to 300k) but also:

- Approximated the The Global Industry Classification Standard (GICS®), a standard used for sectors and industries everywhere. Note that this was approximated and therefore no actual data is collected. Furthermore, not all categories are included.
- Updated and removed tickers that either no longer exist or had outdated information.
- Made the package itself object orientated making data collecting and searching much more efficient and logical. (shoutout to [Colin Delahunty](https://github.com/colin99d) for the help here too)
- The database initially featured thousands of JSON files. At the time it made sense also given my rather novice background in programming. However, a much more efficient (and manageable way) is to work with CSV files. So instead, one CSV file per asset class
- Due to using CSV files, it becomes really easy to update accordingly.
- To make loading data itself still quick, it automatically compresses the data so that loading in data is not slowed down by using a format that is more easy to update.
- Updated the README, Contributing Guidelines and overal documentation.

1.0.0

Added market cap to Equities and total assets to ETFs and Funds. Furthermore, renamed the package to financedatabase (from FinanceDatabase) to be more in line with PEP8.

0.1.11

In this release I have included a parameter called _exclude_exchanges_. By default this paramater is set to True which means all exchanges are excluded from the selection (via for example `select_equities`). This is done to prevent the user from receiving several times the same ticker (but in different exchanges). Setting this parameter to False returns the amount of tickers as listed in the Key Statistics in README.md

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