Python 畅销价格 python画图

import csvimport matplotlibmatplotlib.use('Qt5Agg')from collections import Counterimport matplotlib.pyplot as pltimport xlrddef getgo(sku , bestprice):    result = []    ebaylist = []    with open("sku\\window regulator-oe\\feedback_"+sku+".csv", newline="") as f:        reader = csv.reader(f)        k = 0        prices = []        for row1 in reader:            if k == 0:  # 去掉列名                k = 1                continue            if len(row1) == 0:                break            if round(float((row1[5]))) == bestprice:                sku = row1[0]                kind = row1[1]                ebayId = row1[2]                ebayno = row1[3]                price = row1[5]                currency = row1[6]                shop_name = row1[8]                ebay_close_p = row1[9]                ebay_close_c = row1[10]                if len(ebaylist) != 0 and ebayno in ebaylist:                    continue                ebaylist.append(ebayno)                result.append([sku , kind , ebayId , ebayno,price , currency , shop_name, ebay_close_p, ebay_close_c])    return resultout = open("figure\\feedback.csv", "w", newline="")  #写入数据csv_writer = csv.writer(out)csv_writer.writerow(["sku", "kind" , "ebayId","ebayno", "price", "currency",  "shop_name","ebay_close_p","ebay_close_c"])data = xlrd.open_workbook("window regulator-OE.xlsx")  # 打开excel,读入skutable = data.sheet_by_index(0)  # 读sheetnrows = table.nrows  # 获得行数result = []for i in range(1, nrows):  #    rows = table.row_values(i)  # 行的数据放在数组里    sku = rows[0]    print(sku)    with open("sku\\window regulator-oe\\feedback_"+sku+".csv", newline="") as f:        reader = csv.reader(f)        k = 0        prices = []        for row1 in reader:            if k == 0:  # 去掉列名                k = 1                continue            if len(row1) == 0:                break            y = round(float((row1[5]))) #四舍五入            prices.append(y) #将价格提取出来成列表        prices.sort() #对价格排序        count = Counter(prices)  #返回counter对象，是字典的子类，可以采用字典的方法        price = []        sale = []        maxsale = 0        for key, value in count.items():            price.append(key)            sale.append(value)            if value > maxsale:                maxsale = value                bestprice = key        print(bestprice)   #找到销量最高的价格        re = getgo(sku, bestprice)        for i in range(len(re)):  #把销量最好的价格对应的ebayno写入数据            row = re[i]            csv_writer.writerow([row[0], row[1],row[2],row[3],row[4],row[5],row[6],row[7],row[8]])        #画图        plt.figure(str(sku))        p1 = plt.plot(price, sale, 'r', label="sales")        for xy in zip(price, sale):            plt.annotate(xy[0], xy=xy, xytext=(-10, 10), textcoords='offset points')        plt.grid(True)        plt.xlabel("price")        plt.ylabel("sale")        plt.title(sku)        plt.legend(loc=1)  # 图例        plt.savefig("figure\\"+str(sku)+".png")

pandas读入excel表格数据

import pandas as pdimport numpy as npfrom collections import Counterimport matplotlib.pyplot as pltdf = pd.read_csv("together_tag.csv")print(df.head())skunodf = pd.read_excel("skuno_tag.xlsx" , sheetname="Sheet1")print(skunodf.head())for rows in skunodf.values:    print(rows)    id = rows[1]    skuno = rows[2]    motor = rows[3]    group = rows[4]    fr = rows[5]    lr = rows[6]    print(skuno , motor , group , fr , lr)    #在数据表中寻找满足条件的数据    dfsku = df[(df.sku == skuno) & (df.motor == str(motor)) &(df.group == group) &(df.fr == fr) & (df.lr == lr)]    sumlen = len(dfsku)    # print(dfsku.describe())    prices = dfsku["price"].values    prices = np.round(prices,0)    # print(prices)    prices.sort()  # 对价格排序    count = Counter(prices)  # 返回counter对象，是字典的子类，可以采用字典的方法    price = []    sale = []    maxsale = 0    for key, value in count.items():        price.append(key)        sale.append(value)        if value > maxsale:            maxsale = value            bestprice = key    print(bestprice)  # 找到销量最高的价格    print(sumlen)    # 画图    plt.figure(str(id))    p1 = plt.plot(price, sale, 'r', label="sales")    for xy in zip(price, sale):        plt.annotate(xy[0], xy=xy, xytext=(-10, 10), textcoords='offset points')    plt.grid(True)    plt.xlabel("price")    plt.ylabel("sale--sum:" + str(sumlen))    plt.title(str(id))    plt.legend(loc=1)  # 图例    plt.savefig("sku\\tag\\" + str(id) + ".png")