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snambi
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dib-covid-dataset
forked from breno-madruga/dib-covid-dataset

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  1. preprocess:
    2. 

  2.   cmd: python scripts/preprocess.py
    3. 

  3.   deps:
    4. 

  4.   - path: data/raw/arxiv_raw.csv
    5. 

  5.     md5: 3443082586f8d4711b6f665dbc896193
    6. 

  6.   - path: data/raw/biorxiv_raw.csv
    7. 

  7.     md5: b46ccc80bc9fece6bd918399ce995ec8
    8. 

  8.   - path: data/raw/pubmed_raw.csv
    9. 

  9.     md5: 2ccc57c6adbb66463cb3ce9fd67f626a
    10. 

  10.   - path: data/raw/scopus_raw.csv
    11. 

  11.     md5: 578235ffff6979c4b5e105e18dda5402
    12. 

  12.   - path: scripts/preprocess.py
    13. 

  13.     md5: b42e563e13e6085d4c4ca4362f939780
    14. 

  14.   outs:
    15. 

  15.   - path: data/prepared/arxiv_covid_19.csv
    16. 

  16.     md5: af8015405b5af13109089eb61fc44180
    17. 

  17.   - path: data/prepared/biorxiv_covid_19.csv
    18. 

  18.     md5: 9cdd7b066d32b81a278f6023e5b17b99
    19. 

  19.   - path: data/prepared/pubmed_covid_19.csv
    20. 

  20.     md5: 18c6635458576c258d44c55689359dc4
    21. 

  21.   - path: data/prepared/scopus_covid_19.csv
    22. 

  22.     md5: 7f3f0f5c64066602673ff9068022ca11
    23. 

  23. merge:
    24. 

  24.   cmd: python scripts/merge_datasets.py
    25. 

  25.   deps:
    26. 

  26.   - path: data/prepared/arxiv_covid_19.csv
    27. 

  27.     md5: af8015405b5af13109089eb61fc44180
    28. 

  28.   - path: data/prepared/biorxiv_covid_19.csv
    29. 

  29.     md5: 9cdd7b066d32b81a278f6023e5b17b99
    30. 

  30.   - path: data/prepared/pubmed_covid_19.csv
    31. 

  31.     md5: 18c6635458576c258d44c55689359dc4
    32. 

  32.   - path: data/prepared/scopus_covid_19.csv
    33. 

  33.     md5: 7f3f0f5c64066602673ff9068022ca11
    34. 

  34.   - path: scripts/merge_datasets.py
    35. 

  35.     md5: 8e7e3476183171089a7735ddd30b1084
    36. 

  36.   outs:
    37. 

  37.   - path: data/raw/final_raw.csv
    38. 

  38.     md5: 7479ac0b6588f20016f9ebd090939f7f
    39. 

  39. preprocess_final:
    40. 

  40.   cmd: python scripts/preprocess.py final
    41. 

  41.   deps:
    42. 

  42.   - path: data/raw/final_raw.csv
    43. 

  43.     md5: 7479ac0b6588f20016f9ebd090939f7f
    44. 

  44.   - path: scripts/preprocess.py
    45. 

  45.     md5: b42e563e13e6085d4c4ca4362f939780
    46. 

  46.   outs:
    47. 

  47.   - path: data/prepared/final_covid_19.csv
    48. 

  48.     md5: 775fa35c47b032950b31890eba02bbce
    49.
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Integrate Azure Cloud Storage
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Use Azure Cloud Storage!

Browsing data directories saved to Azure Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your Azure Storage bucket

Access key (If needed)

Congratulations!

dib-covid-dataset is now integrated with Azure Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes