Nlu

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30.4

27.3

| 26 | 4 | 120.3 | 91 | 4.43 | 2.14 | 16.7 | 0 | 1 | 5 |

22.8

21.4

Extract Tables from DOC/DOCX files as Pandas DataFrames

Sample DOCX:
![Sample DOCX](https://github.com/JohnSnowLabs/nlu/blob/4.0.0/docs/assets/images/ocr/nlu_ocr/tables/doc.png?raw=true)

python
nlu.load('doc2table').predict('/path/to/sample.docx')

**Output of DOCX Table OCR :**

| Screen Reader | Responses | Share |
|:----------------|------------:|:--------|
| JAWS | 853 | 49% |
| NVDA | 238 | 14% |
| Window-Eyes | 214 | 12% |
| System Access | 181 | 10% |
| VoiceOver | 159 | 9% |





Extract Tables from PPT files as Pandas DataFrame

Sample PPT with two tables:
![Sample PPT with two tables](https://github.com/JohnSnowLabs/nlu/blob/4.0.0/docs/assets/images/ocr/nlu_ocr/tables/ppt.png?raw=true)

python
nlu.load('ppt2table').predict('/path/to/sample.docx')


**Output of PPT Table OCR :**


| Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species |
|---------------:|--------------:|---------------:|--------------:|:----------|

19.7

| 15 | 8 | 301 | 335 | 3.54 | 3.57 | 14.6 | 0 | 1 | 5 |

19.2

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