dpguthrie / dpguthrie/yahooquery

Why is the last indice of daily price data a datetime and all the rest are date!!! ANSWERED...

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Python
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Description

Since 2.3.0 there have been a few of issues raised that have this change at their root, including [here](https://github.com/dpguthrie/yahooquery/issues/169#issuecomment-1481837966) in #169, #175 and I feel like I've discussed it many times besides. So here's the answer in one place...

`yahooquery` indexes daily price data with date objects. However, if data is requested that includes a session that has yet to close then the last indice is a datetime object. One reason is that this removes the ambiguity of whether the row represents the end-of-day price or merely a price during the session. The more important reason is that I don't believe that **generally** it's possible to evaluate what date (i.e. session) the live indice datetime relates to without knowing the symbol's trading hours (this is explained in more detail [here](https://github.com/dpguthrie/yahooquery/issues/127#issuecomment-1324395424)).

@dpguthrie, to avoid this issue repeating I was thinking of offering a PR adding an explanation to the README? Ideally I'd include a link to [market_prices](https://github.com/maread99/market_prices) which sits on top of `yahooquery` and does resolve the live indice to a date (which it does by mapping symbols to calendars from [exchange_calendars](https://github.com/gerrymanoim/exchange_calendars) and then querying the trading hours). Perhaps you'd let me know if you think the addition to the README would be useful and if you have any objections to including a link to [market_prices](https://github.com/maread99/market_prices).

Or maybe leaving this as an open issue suffices?

Cheers
Marcus

Contributor guide

Open the contributing guide

Research direction

Review the README and the existing daily price-data documentation. Explain why completed sessions use date indices while an open session uses a datetime, and consider linking to market_prices and exchange_calendars as proposed. Done means the behavior and rationale are documented clearly without reopening the underlying issue.

Written by the indexing model from the issue text.

Assessment

Tech stack
pandas, python
Domain
documentation
Issue type
Documentation
Difficulty
1/5
Estimated time
Under an hour
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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