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PDF táblázatok pandas-ba való alakítása. Ez csak olyan PDF-ekre működik, amelyekben a táblázat valóban szöveg és nem kép. Tehát _Excel_ből vagy _Word_ból voltak exportálva.



In [1]:

    
import pandas as pd

Install dependencies https://camelot-py.readthedocs.io/en/master/user/install-deps.html
For Windows: https://www.ghostscript.com/download/gsdnld.html

Olvasd el: https://camelot-py.readthedocs.io/en/master/user/quickstart.html#read-the-pdf



In [2]:

    
!pip install camelot-py









    



Requirement already satisfied: camelot-py in c:\programdata\anaconda3\lib\site-packages (0.7.3)
Requirement already satisfied: PyPDF2>=1.26.0 in c:\programdata\anaconda3\lib\site-packages (from camelot-py) (1.26.0)
Requirement already satisfied: chardet>=3.0.4 in c:\programdata\anaconda3\lib\site-packages (from camelot-py) (3.0.4)
Requirement already satisfied: pdfminer.six>=20170720 in c:\programdata\anaconda3\lib\site-packages (from camelot-py) (20191110)
Requirement already satisfied: pandas>=0.23.4 in c:\programdata\anaconda3\lib\site-packages (from camelot-py) (0.25.1)
Requirement already satisfied: numpy>=1.13.3 in c:\programdata\anaconda3\lib\site-packages (from camelot-py) (1.16.5)
Requirement already satisfied: click>=6.7 in c:\programdata\anaconda3\lib\site-packages (from camelot-py) (7.0)
Requirement already satisfied: openpyxl>=2.5.8 in c:\programdata\anaconda3\lib\site-packages (from camelot-py) (3.0.0)
Requirement already satisfied: pycryptodome in c:\programdata\anaconda3\lib\site-packages (from pdfminer.six>=20170720->camelot-py) (3.9.4)
Requirement already satisfied: six in c:\programdata\anaconda3\lib\site-packages (from pdfminer.six>=20170720->camelot-py) (1.12.0)
Requirement already satisfied: sortedcontainers in c:\programdata\anaconda3\lib\site-packages (from pdfminer.six>=20170720->camelot-py) (2.1.0)
Requirement already satisfied: python-dateutil>=2.6.1 in c:\programdata\anaconda3\lib\site-packages (from pandas>=0.23.4->camelot-py) (2.8.0)
Requirement already satisfied: pytz>=2017.2 in c:\programdata\anaconda3\lib\site-packages (from pandas>=0.23.4->camelot-py) (2019.3)
Requirement already satisfied: et-xmlfile in c:\programdata\anaconda3\lib\site-packages (from openpyxl>=2.5.8->camelot-py) (1.0.1)
Requirement already satisfied: jdcal in c:\programdata\anaconda3\lib\site-packages (from openpyxl>=2.5.8->camelot-py) (1.4.1)

Olvasd el: https://stackoverflow.com/questions/44439443/python-how-to-pip-install-opencv2-with-specific-version-2-4-9



In [3]:

    
!pip install opencv-python









    



Requirement already satisfied: opencv-python in c:\programdata\anaconda3\lib\site-packages (4.1.2.30)
Requirement already satisfied: numpy>=1.14.5 in c:\programdata\anaconda3\lib\site-packages (from opencv-python) (1.16.5)



In [4]:

    
import camelot



In [9]:

    
tables = camelot.read_pdf('foo.pdf')



In [12]:

    
tables[0].df









    Out[12]:







  
    
      
      0
      1
      2
      3
      4
      5
      6
    
  
  
    
      0
      Cycle \nName
      KI \n(1/km)
      Distance \n(mi)
      Percent Fuel Savings
      
      
      
    
    
      1
      
      
      
      Improved \nSpeed
      Decreased \nAccel
      Eliminate \nStops
      Decreased \nIdle
    
    
      2
      2012_2
      3.30
      1.3
      5.9%
      9.5%
      29.2%
      17.4%
    
    
      3
      2145_1
      0.68
      11.2
      2.4%
      0.1%
      9.5%
      2.7%
    
    
      4
      4234_1
      0.59
      58.7
      8.5%
      1.3%
      8.5%
      3.3%
    
    
      5
      2032_2
      0.17
      57.8
      21.7%
      0.3%
      2.7%
      1.2%
    
    
      6
      4171_1
      0.07
      173.9
      58.1%
      1.6%
      2.1%
      0.5%

	0	1	2	3	4	5	6
0	Cycle \nName	KI \n(1/km)	Distance \n(mi)	Percent Fuel Savings
1				Improved \nSpeed	Decreased \nAccel	Eliminate \nStops	Decreased \nIdle
2	2012_2	3.30	1.3	5.9%	9.5%	29.2%	17.4%
3	2145_1	0.68	11.2	2.4%	0.1%	9.5%	2.7%
4	4234_1	0.59	58.7	8.5%	1.3%	8.5%	3.3%
5	2032_2	0.17	57.8	21.7%	0.3%	2.7%	1.2%
6	4171_1	0.07	173.9	58.1%	1.6%	2.1%	0.5%