How to convert Wikipedia wikitable to Python Pandas DataFrame?

Question

In Wikipedia, you can find some interesting data to be sorted, filtered, ...

Here is a sample of a wikitable

{| class="wikitable sortable"
|-
! Model !! Mhash/s !! Mhash/J !! Watts !! Clock !! SP !! Comment
|-
| ION || 1.8 || 0.067 || 27 ||  || 16 || poclbm;  power consumption incl. CPU
|-
| 8200 mGPU || 1.2 || || || 1200 || 16 || 128 MB shared memory, "poclbm -w 128 -f 0"
|-
| 8400 GS || 2.3 || || ||  ||  || "poclbm -w 128"
|-
|}

I'm looking for a way to import such data to a Python Pandas DataFrame

Answer 1

Here's a solution using py-wikimarkup and PyQuery to extract all tables as pandas DataFrames from a wikimarkup string, ignoring non-table content.

import wikimarkup
import pandas as pd
from pyquery import PyQuery

def get_tables(wiki):
    html = PyQuery(wikimarkup.parse(wiki))
    frames = []
    for table in html('table'):
        data = [[x.text.strip() for x in row]
                for row in table.getchildren()]
        df = pd.DataFrame(data[1:], columns=data[0])
        frames.append(df)
    return frames

Given the following input,

wiki = """
=Title=

Description.

{| class="wikitable sortable"
|-
! Model !! Mhash/s !! Mhash/J !! Watts !! Clock !! SP !! Comment
|-
| ION || 1.8 || 0.067 || 27 ||  || 16 || poclbm;  power consumption incl. CPU
|-
| 8200 mGPU || 1.2 || || || 1200 || 16 || 128 MB shared memory, "poclbm -w 128 -f 0"
|-
| 8400 GS || 2.3 || || || || || "poclbm -w 128"
|-
|}

{| class="wikitable sortable"
|-
! A !! B !! C
|-
| 0
| 1
| 2
|-
| 3
| 4
| 5
|}
"""

get_tables returns the following DataFrames.

       Model Mhash/s Mhash/J Watts Clock  SP                                     Comment
0        ION     1.8   0.067    27        16        poclbm;  power consumption incl. CPU
1  8200 mGPU     1.2                1200  16  128 MB shared memory, "poclbm -w 128 -f 0"
2    8400 GS     2.3                                                     "poclbm -w 128"

 

   A  B  C
0  0  1  2
1  3  4  5

Answer 2

You can use pandas directly. Something like this...

pandas.read_html(url, attrs={"class": "wikitable"})