Extracting text from two column pdf using python - python

I am trying to extract text from a two-column pdf. On using pypdf2 and pdfplumber it is reading the page horizontally, i.e. after reading first line of column one it goes on to read first line of column two instead of second line of column one. I have also tried this code githubusercontent
as it is, but I have the same issue. I also saw this How to extract text from two column pdf with Python? but I dont want to convert to image as I have thousands of pages.
Any help will be appreciated. Thannnks!

You can check this blog here which uses PyMuPDF to extract two column pdfs like research papers.
https://towardsdatascience.com/read-a-multi-column-pdf-using-pymupdf-in-python-4b48972f82dc
From what I have tested so far, it works quite well. I would highly recommend the "blocks" option.
# OCR the PDF using the default 'text' parameter
with fitz.open(DIGITIZED_FILE_PATH) as doc:
for page in doc:
text = page.get_text("blocks")
print(text)
Note: It does not work for scanned images. It works only for searchable pdf files.

Related

How to extract a table without all borders into text with Python?

I am trying to extract a table like this into a Dataframe. How to do that (and extract even the names splitted on several lines) with Python?
Also, I want this to be general and to be applied on each table (even if it doesn't this structure), so giving the coordinates for each separate and different table won't work that well.
I don't know about your exact problem but if you want to extract data or tables from PDF then try the camelot-py library, it is easy and gives almost more than 90% accuracy.
I am also working on the same project.
import camelot
tables = camelot.read_pdf(PDF_file_Path, flavor='stream', pages='1', table_areas=['5,530,620,180'])
tables[0].parsing_report
df = tables[0].df
The parameters of camelot.read_pdf are:
PDF_File the give file path;
table_areas is optional if you get an exact table then provide a location otherwise it can get whole data & all tables;
pages number of pages.
.parsing_report show the result description, e.g., accuracy and whitespace.
.df can show the table as a data frame. Index 0 refer to the 1st table. It depends on your data.
You can read more about them in the camelot documentation.

How to extract data from messy PDF file with no standard formatting?

I am working on this PDF file to parse the tabular data out of it. I was hoping to use tabula or PyPDF2 to extract tables out of it but the data in PDF is not stored in tables. So, I chose pdfplumber to extract text out of it. Until now, I am able to read text line by line. But I can not figure out a universal pattern that I can use to extract the pricing list rows which I can store in a pandas dataframe and write to an excel file.
Can you help me if I should construct a regular expression or anything else that I can use to extract the pricing list out of this PDF? Because I can not think of any particular regular expression that would fit the messy nature of data inside the PDF, is there any better approach to take? Or simply it's not possible?
Code
Using the following code, I am able to extract all lines of text but the problem is, one price entry is spread across two rows. Consider current row is where most details about the entry are listed, how can I decide if the previous or next row also has information related to current entry.
If I could somehow figure that out, what might be the right approach to deal with the column values, they can be from 6-13 per line, how can I decide if at this particular location in current line, the column value resides?
import pdfplumber as scrapper
text = []
with scrapper.open('./report.pdf') as pdf:
for page in pdf.pages:
text.append(page.extract_text())
The PDF file I am working with:
https://drive.google.com/file/d/1GtjBf9FcKJCOJVNcGA9mvAshJ6t0oFca/view?usp=sharing
Sample Pictures demonstrating which data should fit in which fields:

Python Tabula for table with no distinct table lines

Recently I tried using tabula to parse a table in the pdf that contains no lines within each fields of the table.
This results in a creation of a list that combines all the different fields into one (example of output).
How do i convert this single string into a dataframe so i can manipulate the numbers? Thank you very much
There is no dummy file given in the question to test, but if there is no separation line in between columns of the pdf table, and the table is merging in one column after extracting from tabula, try to use parameter 'columns' in tabula.read_pdf.
According to Tabula Documentation, this parameter works like this:
columns (list, optional) –
X coordinates of column boundaries.
So, if the format of the PDF is same for every PDF, you can find X coordinates of columns from which you want to separate the data. For that you can use any PDF tool like Adobe, or you can hit and trial also.
Still doubt, please attach dummy PDF so one can look into it.

How to extract particular block of text from pdf file with Python?

I wanted to extract blocks of text as image (here the questions and options in pdf) from pdf and then store each block of text as a image separately.
The length of questions varies a lot, so using pyPDF2 for splitting the pdf at regular intervals is out of question.
Any suggestion? I have read few posts that mention using OCR to get question numbers and then splitting but I didn't completely get what they were trying to say. Is there any easier method?

How to extract charts/tables/graphs from PDF files using Python?

Searched quite a bit but as I couldn't find a solution for this kind of problem, hence posting a clear question on the same. Most answers cover image/text extraction which are comparatively easier.
I've a requirement of extracting tables and graphs as text (csv) and images respectively from PDFs.
Can anyone help me with an efficient python 3.6 code to solve the same?
Till now I could achieve extracting jpgs using startmark = b"\xff\xd8" and endmark = b"\xff\xd9", but not all tables and graphs in a PDF are plain jpgs, hence my code fails badly in achieving that.
Example, I want to extract table from page 11 and graphs from page 12 as image or something which is feasible from the below given link. How to go about it?
https://hartmannazurecdn.azureedge.net/media/2369/annual-report-2017.pdf
For extracting tables you can use camelot
Here is an article about it.
For images I've found this question and answer Extract images from PDF without resampling, in python?
Try using PyMuPdf(https://github.com/pymupdf/PyMuPDF/tree/1.18.3) for amalgamation of texts, bars, lines and axis. It has so many extra utilities.

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