> ## Content Index > Fetch the complete content index at: https://datascientyst.com/llms.txt > Use this file to discover other available public pages before exploring further. # How to Extract Table from PDF with Python and Pandas - URL: https://datascientyst.com/extract-table-from-pdf-with-python-pandas/ - Published: 2022-09-30T06:23:11.000Z - Updated: 2025-02-14T13:10:18.000Z - Author: John D K - Tags: Other In this short tutorial, we'll see how to **extract tables from PDF files with Python and Pandas**. We will cover two cases of table extraction from PDF: **(1) Simple table with tabula-py** ```python from tabula import read_pdf df_temp = read_pdf('china.pdf') ``` **(2) Table with merged cells** ```python import pandas as pd html_tables = pd.read_html(page) ``` Let's cover both examples in more detail as context is important. Nice video on the topic: [Easily extract tables from websites with pandas and python](https://www.youtube.com/watch?v=OXA%5FZD1gR6A&ref=datascientyst.com) Notebook: [Scrape wiki tables with pandas and python.ipynb](https://github.com/softhints/python/blob/master/notebooks/Scrape%20wiki%20tables%20with%20pandas%20and%20python.ipynb?ref=datascientyst.com) ## 1: Extract tables from PDF with Python In this example we will **extract multiple tables from remote PDF file**: [china.pdf](https://github.com/tabulapdf/tabula-java/blob/master/src/test/resources/technology/tabula/china.pdf?ref=datascientyst.com). We will use library called: [tabula-py](https://pypi.org/project/tabula-py/?ref=datascientyst.com) which can be installed by: ```bash pip install tabula-py ``` The .pdf file contains 2 table: - smaller one - bigger one with merged cells ```python from tabula import read_pdf file = 'https://raw.githubusercontent.com/tabulapdf/tabula-java/master/src/test/resources/technology/tabula/china.pdf' df_temp = read_pdf(file, stream=True) ``` After reading the data we can get a list of DataFrames which contain table data. Let's check the first one: | | FLA Audit Profile | Unnamed: 0 | | - | -------------------- | ------------------------------------------------- | | 0 | Country | China | | 1 | Factory name | 01001523B | | 2 | IEM | BVCPS (HK), Shen Zhen Office | | 3 | Date of audit | May 20-22, 2003 | | 4 | PC(s) | adidas-Salomon | | 5 | Number of workers | 243 | | 6 | Product(s) | Scarf, cap, gloves, beanies and headbands | | 7 | Production processes | Sewing, cutting, packing, embroidery, die-cutting | Which is the exact match of the first table from the PDF file. ![read-pdf-table-python-tabula](https://datascientyst.com/content/images/2022/09/read-pdf-table-python-tabula.png) While the second one is a bit weird. The reason is because of the merged cells which are extracted as `NaN` values: | | Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Findings | Unnamed: 3 | | - | -------------------------- | ----------------------------- | ------------- | ------------------ | ---------- | | 0 | FLA Code/ Compliance issue | Legal Reference / Country Law | FLA Benchmark | Monitor's Findings | NaN | | 1 | 1\. Code Awareness | NaN | NaN | NaN | NaN | | 2 | 2\. Forced Labor | NaN | NaN | NaN | NaN | | 3 | 3\. Child Labor | NaN | NaN | NaN | NaN | | 4 | 4\. Harassment or Abuse | NaN | NaN | NaN | NaN | ![read-pdf-table-python-tabula-merged-cells](https://datascientyst.com/content/images/2022/09/read-pdf-table-python-tabula-merged-cells.png) How to workaround this problem we will see in the next step. Some cells are extracted to multiple rows as we can see from the image: ## 2: Extract tables from PDF - keep format Often tables in PDF files have: - strange format - merged cells - strange symbols Most libraries and software are not able to extract them in a reliable way. To **extract complex table from PDF files with Python and Pandas** we will do: - download the file (it's possible without download) - convert the PDF file to HTML - extract the tables with Pandas ### 2.1 Convert PDF to HTML First we will download the file from: [china.pdf](https://github.com/tabulapdf/tabula-java/blob/master/src/test/resources/technology/tabula/china.pdf?ref=datascientyst.com). Then we will convert it to HTML with the library: [pdftotree](https://pypi.org/project/pdftotree/?ref=datascientyst.com). ```python import pdftotree page = pdftotree.parse('china.pdf', html_path=None, model_type=None, model_path=None, visualize=False) ``` library can be installed by: ```bash pip install pdftotree ``` ### 2.2 Extract tables with Pandas Finally we can read all the tables from this page with Pandas: ```python import pandas as pd html_tables = pd.read_html(page) html_tables[1] ``` Which will give us better results in comparison to `tabula-py` ![read-pdf-table-python-pandas-merged-cells](https://datascientyst.com/content/images/2022/09/read-pdf-table-python-pandas-merged-cells.png) ### 2.3 HTMLTableParser As alternatively to Pandas, we can use the library: [html-table-parser-python3](https://pypi.org/project/html-table-parser-python3/?ref=datascientyst.com) to parse the HTML tables to Python lists. ```python from html_table_parser.parser import HTMLTableParser p = HTMLTableParser() p.feed(page) print(p.tables[0]) ``` it convert the HTML table to Python list: ``` [['', ''], ['Country', 'China'], ['Factory name', '01001523B'], ['IEM', 'BVCPS (HK), Shen Zhen Office'], ['Date of audit', 'May 20-22, 2003'], ['PC(s)', 'adidas-Salomon'], ['Number of workers', '243'], ['Product(s)', 'Scarf, cap, gloves, beanies and headbands']] ``` Now we can convert the list to Pandas DataFrame: ```python import pandas as pd pd.DataFrame(p.tables[1]) ``` To install this library we can do: ```bash pip install html-table-parser-python3 ``` There are two differences to Pandas: - returns list of values - instead of NaN values - there are empty strings ## 3\. Python Libraries for extraction from PDF files Finally let's find a **list of useful Python libraries which can help in PDF parsing and extraction**: ### 3.1 Python PDF parsing - [tabula-py](https://pypi.org/project/tabula-py/?ref=datascientyst.com) \- Simple wrapper for tabula-java, read tables from PDF into DataFrame - [tabula-py example notebook](https://nbviewer.org/github/chezou/tabula-py/blob/master/examples/tabula%5Fexample.ipynb?ref=datascientyst.com) - [camelot-py](https://pypi.org/project/camelot-py/?ref=datascientyst.com) \- PDF Table Extraction for Humans - [pdfminer](https://pypi.org/project/pdfminer/?ref=datascientyst.com) \- PDF parser and analyzer - [PyPDF2](https://pypi.org/project/PyPDF2/?ref=datascientyst.com) \- A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files ### 3.2 Parse HTML tables - [html-table-parser-python3](https://pypi.org/project/html-table-parser-python3/?ref=datascientyst.com) \- parse HTML tables with Python 3 to list of values - [tablextract](https://pypi.org/project/tablextract/?ref=datascientyst.com) \- extracts the information represented in any HTML table - [pdftotree](https://pypi.org/project/pdftotree/?ref=datascientyst.com) \- convert PDF into hOCR with text, tables, and figures being recognized and preserved. - [pandas.read\_html](https://pandas.pydata.org/docs/reference/api/pandas.read%5Fhtml.html?ref=datascientyst.com) - [html-table-extractor](https://pypi.org/project/html-table-extractor/?ref=datascientyst.com) \- A python library for extracting data from html table - [py-html-table](https://pypi.org/project/py-html-table/?ref=datascientyst.com) \- Python library to extract data from HTML Tables with rowspan ### 3.3 Example PDF files Finally you can find example PDF files where you can test table extraction with Python and Pandas: [tabula test PDF files](https://github.com/tabulapdf/tabula-java/tree/master/src/test/resources/technology/tabula?ref=datascientyst.com) ![](https://datascientyst.com/content/images/2022/09/extract-table-from-pdf-with-python-pandas.png)