在维基百科中,您可以找到一些有趣的数据进行排序,过滤,…
这是一个可爱的样本
{| 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"
|-
|}
我正在寻找一种将这些数据导入Python Pandas DataFrame的方法
解决方法
以下是使用
py-wikimarkup和
PyQuery从wikimarkup字符串中将所有表提取为熊猫DataFrames的解决方案,忽略非表内容.
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
给出以下输入,
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返回以下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