老鱼Python数据分析 |
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老鱼Python数据分析
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使用Python操作CSV文件非常方便，三行代码搞定。 一、向文件中追加数据 import csv # 将数据写入文件 with open("d:\\data.csv", "a", newline="") as cf: w = csv.writer(cf) w.writerow([1001, "北京"]) w.writerow([1002, "上海"]) w.writerow([1003, "广州"]) cf.close()结果：
二、从文件中读取数据 # 将数据从文件读出 with open("d:\\data.csv", "r") as cf: d = csv.reader(cf) for row in d: print(row)结果：
三、如果将代码多执行一次，就会变成这样：
所以最好判断文件是否存在，如果存在则删除，代码如下： import csv import os # 判断文件是否存在 if os.path.exists("d:\\data.csv"): os.remove("d:\\data.csv") # 将数据写入文件 with open("d:\\data.csv", "a", newline="") as cf: w = csv.writer(cf) w.writerow([1001, "北京"]) w.writerow([1002, "上海"]) w.writerow([1003, "广州"]) cf.close() # 将数据从文件读出 with open("d:\\data.csv", "r") as cf: d = csv.reader(cf) for row in d: print(row)OK，现在已经学会CSV文件的操作了，将从网页爬到的动态数据保存到CSV文件完整代码如下： # 先安装selenium，再安装chromeDriver from selenium import webdriver from bs4 import BeautifulSoup import time import csv from Items import FuPanData import os def saveFuPan(): try: browser = webdriver.Chrome() browser.get("https://xuangubao.cn/dingpan") page = browser.page_source soup = BeautifulSoup(page,"lxml") # 得到日期 # today = soup.find("div", attrs={"class", "ban-chart-date-container"}).find_all("p") # print(today[0].get_text().strip(),today[1].get_text().strip(),"日") date = time.strftime('%Y-%m-%d',time.localtime(time.time())) print(date) # 查询涨跌数据 spans = soup.find("div", attrs={"class":"ban-chart"}).find_all("span") up = spans[3].get_text().strip() down = spans[4].get_text().strip() limitUp = spans[6].get_text().strip() limitDown = spans[7].get_text().strip() bomb = spans[8].get_text().strip() print("涨：",up) print("跌：",down) print("涨停：",limitUp) print("跌停：",limitDown) print("炸板率：", bomb) # 创建每天复盘数据对象 todayData = FuPanData(date, up, down,limitUp, limitDown, bomb, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) # 连板个股相关操作 listCount = [] # 连板个数 guList = soup.find("table", attrs={"class", "table hit-pool__table"}).find_all("tr") # 判断当天连板个股是否保存 if os.path.exists("d:\\" + date + ".csv"): os.remove("d:\\" + date + ".csv") # 循环读取连板个股 for gu in guList[1:]: tds = gu.find_all("td") guName = tds[1].find_all("span")[0].get_text().strip() guCode = tds[1].find_all("a")[0].get_text().strip()[-6:] # print(guName,"(",guCode,")","：",tds[12].get_text().strip()) listCount.append(tds[12].get_text().strip()) # 将连接数据保存到list # 将个股保存到CSV文件 if tds[12].get_text().strip()!="首板": with open("d:\\"+date+".csv", "a", newline="") as apdFile: w = csv.writer(apdFile) w.writerow([guName,guCode,tds[12].get_text().strip()]) # 显示不同连板的个数 for i in set(listCount): print("{0}：{1}".format(i, listCount.count(i))) if i == "首板": todayData.ban1 = listCount.count(i) elif i =="2连板": todayData.ban2 = listCount.count(i) elif i =="3连板": todayData.ban3 = listCount.count(i) elif i =="4连板": todayData.ban4 = listCount.count(i) elif i =="5连板": todayData.ban5 = listCount.count(i) elif i =="6连板": todayData.ban6 = listCount.count(i) elif i =="7连板": todayData.ban7 = listCount.count(i) elif i =="8连板": todayData.ban8 = listCount.count(i) elif i =="9连板": todayData.ban9 = listCount.count(i) elif i =="10连板": todayData.ban10 = listCount.count(i) else: todayData.ban10s = listCount.count(i) # 判断是否保存过数据 state为True表示已保存过 with open("d:\\dapanData.csv", "r") as csvfile: line = csvfile.readlines()[-1] d = line.split(",")[0] state = False # 判断是否有历史数据，如果有历史数据，是否有今天的数据 if(len(d.strip())>0): state = int(date.split("-")[0])==int(d.split("/")[0]) and \ int(date.split("-")[1])==int(d.split("/")[1]) and \ int(date.split("-")[2])==int(d.split("/")[2]) # 将数据保存到csv文件 if not state: dapanData = [todayData.date, todayData.up, todayData.down, todayData.limitUp, todayData.limitDown, todayData.bomb, todayData.ban1, todayData.ban2, todayData.ban3, todayData.ban4, todayData.ban5, todayData.ban6, todayData.ban7, todayData.ban8, todayData.ban9, todayData.ban10, todayData.ban10s] # print(dapanData) with open("d:\\dapanData.csv", "a", newline="") as apdFile: w = csv.writer(apdFile) w.writerow(dapanData) except Exception as e: print("出错了") print ("str(e):\t", str(e)) browser.close() else: print("今天数据已保存") browser.close() if __name__ == "__main__": saveFuPan()结果如下：
数据完美保存，谢谢大家的阅读,欢迎留言交流！
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