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Week 6
18 July to 24 July 2022
- Weekly meet on 19 July.
- Agenda:
- Resolve all bugs as discussed in the call.
Tasks accomplished
- Resolving bugs and initiating PRs for the same.
- occurrence pagination (use default size 5000)
- wrote a new function to enable fetching occurrence records iteratively, w/ and w/o user-specified limits
- MoF accessibility (duplicate columns)
- resolved duplicate column issue when fetching MoF records. Some columns like
scientificName and eventID were being repeated when performing inner_join on normalized and non-normalized DataFrame.
- MoF Null Records
- Added a null-check function when accessing MoF records. Previously, accessing MoF records for species without any occurrence records resulted in an error.
- added progress bar to occurrences.search function, so that when the records fetching process is informative.
- Completing 1st Jupyter Notebook Analysis -
occurrence_ocean_sunfish.ipynb.
- completed writing notebook with experiments on ocean sunfish occurrence records.
- Adding more information to the README and making it more beginner friendly
- Since
pyobis is an open-source project, there is a strong need to expand the README to include information related to, but not limited to:
- Data Quality Issues reporting: If any user finds some issues with the data grabbed from
pyobis it will be a natural instinct for him/her to open issues here. Therefore, README must contain relevant information regarding the right place to open issues.
- Data Related Queries: If any user has some queries related to the data being returned by
pyobis say pertaining to the fields returned with occurrence records then it might be wise to include links to the OBIS main page, contact page or some forum.
- Update short examples contained in the README
- Add link to
usage_guide.ipynb and to /notebooks/ folder for sample use case-analysis
- Other changes: Changing the links that have gone obsolete, adding Further Reading material, adding link to CONTRIBUTING.md guide.
Tasks working on
- writing a progress bar to occurrence records fetch process.
- Debugging flake8 linting
- creating
depth_time_series.ipynb - a time-series analysis for average depth for some species
- an elaborate line plot with 3 or 5-year average also depicted.