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交易官网（通用积分-论坛币）：https://bbs.pinggu.org/ext8_airdrop.php?ac=transaction

1. 通用积分数据爬取（Python）

import requests
import urllib
import pandas as pd
from bs4 import BeautifulSoup
from lxml import etree
def spider_pgc_translate():    
#     url='http://bbs.pinggu.org/ext8_airdrop.php?ac=transaction'
#     html = requests.get(url)
#     soup = BeautifulSoup(html.text, "lxml")
    url = "http://bbs.pinggu.org/ext8_airdrop.php?ac=transaction"
    html = urllib.request.urlopen(url).read()
    soup = BeautifulSoup(html, "lxml")
    
    trans=pd.DataFrame()
    trans['time_1'] = [i_1.string for i_1 in soup("i",attrs={"class":"jiaoyi-time1"})]
    trans['time_2'] = [i_2.string for i_2 in soup("i",attrs={"class":"jiaoyi-time2"})]
    trans['buy_sell'] =[j.img['src'].split('/images/')[1][:-4] for j in soup("div",attrs={"class":"jy-liat clearfix"})]
    trans['price'] = [l.get_text().split('论坛币')[0] for  l in soup("span",attrs={"class":"span-size span-width11"})]
    trans['pgc']=[k.get_text() for k in soup("span",attrs={"class":"span-size span-width00"})]
    trans['pgc']=trans['pgc'].map(float)
    return trans
trans=spider_pgc_translate()

2. 数据清洗-将数据清洗为股票交易数据（Python）

import pandas as pd
import datetime
trans.index=pd.DatetimeIndex(trans['time_1'])
trans['price']=trans['price'].map(float)
trans['pgc']=trans['pgc'].map(float)
trans=trans['2018-10-21':'2018-09-01']
trans= trans[trans['price']<trans['price'].mean()*6]
trans= trans[trans['price']<1000]
df_stock=pd.DataFrame()
df_stock['time']=trans[['price']].groupby('time_1').max().index
df_stock['open']=trans[['price']].groupby('time_1').head(1).values
df_stock['high']=trans[['price']].groupby('time_1').max().values
df_stock['low']=trans[['price']].groupby('time_1').min().values
df_stock['close']=trans[['price']].groupby('time_1').tail(1).values
df_stock['avg']=trans[['price']].groupby('time_1').mean().values
df_stock['vol']=trans[['pgc']].groupby('time_1').sum().values

DATE=str(datetime.datetime.now().date())[2:].replace("-",'_')


df_stock.tail()
df_stock.to_csv("df_stock_"+DATE+".csv",index=None)

3. 绘制通用积分的日K线图（R语言）

#------------------------------------------
# 绘制股票K线
#------------------------------------------
data_origin=read.csv("df_stock.csv",header = T)
data<-data.frame(Open=data_origin[,2],High=data_origin[,3],Low=data_origin[,4],Close=data_origin[,5],Volume=data_origin[,6],Adjusted=data_origin[,7])
rownames(data)<-apply(data_origin[1],1,as.character)
# data_origin[1]

library(quantmod) 
通用积分日K线图=data
chartSeries(通用积分日K线图,up.col='red', dn.col='green')
addEMA(); #指数平均数指标

addWMA(); #加权移动平均线指标
addWPR(); #威廉指标
addZLEMA(); #零滞后指数移动平均线
addSMA(); #简单移动平均指标

PS：又一波行情，还不快买入，别忘了点赞哈（注：非专业解读，投资需谨慎）~~~