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Update Side Panel Tile Data (#866)

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* Update Side Panel Tile Data

* Update Side Panel Tile Data

* Correct indicator names to match csv

* Replace Score with Rate

* Comment out FEMA Loss Rate to troubleshoot

* Removes all "FEMA Loss Rate" array elements

* Revert FEMA to Score

* Remove expected loss rate

* Remove RMP and NPL from BASIC array

* Attempt to make shape mismatch align

- update README typo

* Add Score L indicators to TILE_SCORE_FLOAT_COLUMNS

* removing cbg references

* completes the ticket

* Update side panel fields

* Update index file writing to create parent dir

* Updates from linting

* fixing missing field_names for island territories 90th percentile fields

* Update downloadable fields and fix field name

* Update file fields and tests

* Update ordering of fields and leave TODO

* Update pickle after re-ordering of file

* fixing bugs in etl_score_geo

* Repeating index for diesel fix

* passing tests

* adding pytest.ini

Co-authored-by: Vim USDS <vimal.k.shah@omb.eop.gov>
Co-authored-by: Shelby Switzer <shelby.switzer@cms.hhs.gov>
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
This commit is contained in:
Jorge Escobar 2021-12-13 14:53:50 -05:00 • committed by GitHub
commit 9709d08ca3
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13 changed files with 328 additions and 141 deletions
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4
data/data-pipeline/README.md
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@ -159,7 +159,7 @@ We use Docker to install the necessary libraries in a container that can be run
To build the docker container the first time, make sure you're in the root directory of the repository and run `docker-compose build --no-cache`.
Once completed, run `docker-compose up`. Docker will spin up 3 containers: the client container, the static server container and the data container. Once all data is generated, you can see the application using a browser and navigating to `htto://localhost:8000`.
Once completed, run `docker-compose up`. Docker will spin up 3 containers: the client container, the static server container and the data container. Once all data is generated, you can see the application using a browser and navigating to `http://localhost:8000`.
If you want to run specific data tasks, you can open a terminal window, navigate to the root folder for this repository and then execute any command for the application using this format:
@ -322,7 +322,7 @@ score_initial_df = pd.read_csv(score_csv_path, dtype={"GEOID10_TRACT": "string"}
score_initial_df.to_csv(data_path / "data_pipeline" / "etl" / "score" / "tests" / "sample_data" /"score_data_initial.csv", index=False)
```
Now you can move on to updating inidvidual pickles for the tests. Note that it is helpful to do them in this order:
Now you can move on to updating individual pickles for the tests. Note that it is helpful to do them in this order:
We have four pickle files that correspond to expected files:
- `score_data_expected.pkl`: Initial score without counties