Question

我有一个程序在csv文件上运行，以创建如下所示的输出：

我想用一些简单的数学运算来修改脚本，以便它可以渲染输出：

724, 1.5
725, 3
726, 0.5

我目前使用的脚本在这里：

lines=open("1.txt",'r').read().splitlines()
for l in lines:
    data = l.split('"Overall evaluation:')
    if len(data) == 2:
        print(data[0] + ", " + data[1])

如何向该管道添加简单的平均和切片操作？

我想我需要创建一些临时变量，但它应该在遍历行的循环之外？

也许是这样的：

lines=open("EasyChairData.csv",'r').read().splitlines()

for l in lines:
    data = l.split('"Overall evaluation:')

    submission_number_repo = data[0]

    if len(data) == 2:
        print(data[0] + ", " + data[1])

        if submission_number_repo != data[0]
            submission_number_repo = data[0]

编辑

该功能只是一个简单的平均值

Answer 1

您可以使用将键映射到总计和计数的字典，然后将其打印出来：

map = {}
lines=open("1.txt",'r').read().splitlines()
for l in lines:
    data = l.split('"Overall evaluation:')
    if len(data) == 2:
        if data[0] not in map.keys():
            map[data[0]] = (0,0)
        map[data[0]] = (map[data[0]][0]+int(data[1]) , map[data[0]][1]+1)
for x, y in map.items():
    print(str(x) + ", " + str(y[0]/y[1]))

Answer 2

我只想用密钥存储一个值列表。然后在读取文件时取平均值。

lines=open("1.txt",'r').read().splitlines()
results = {}
for l in lines:
    data = l.split('"Overall evaluation:')
    if len(data) == 2:
        if data[0] in results: 
            results[data[0]].append(data[1])
        else: 
            results[data[0]] = [data[1]]
for k,v in results.iteritems():
    print("{} , {}".format(k, sum(v)/len(v) ))

Answer 3

（编辑以避免存储值）

我爱# install.packages("neuralnet") library(neuralnet) # adapted iris data(iris) iris2 <- iris iris2$setosa <- c(iris2$Species == 'setosa') iris2$versicolor <- c(iris2$Species == 'versicolor') iris2$virginica <- c(iris2$Species == 'virginica') # iris2$Species <- NULL # training and validation subsets train.samples <- sample(nrow(iris), nrow(iris)*0.5) train <- iris2[train.samples,] valid <- iris2[-train.samples,] # fit model inet <- neuralnet(setosa + versicolor + virginica ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width, train, hidden=3, lifesign="full") # prediction pred <- compute(inet, valid[,1:4]) head(pred$net.result) # only one level (probability of each category) predspp <- factor(c("setosa" , "versicolor", "virginica"))[apply(pred$net.result, MARGIN=1, FUN=which.max)] table(predspp, valid$Species) # predspp setosa versicolor virginica # setosa 19 0 0 # versicolor 0 24 4 # virginica 0 2 26：

defaultdict

Answer 4

一种简单的方法是保持状态存储当前数量，当前总和和项目数，并且仅在当前数字改变时打印它（不要忘记打印最后状态！）。代码可以是：

lines=open("1.txt",'r')  # .read().splitlines() is useless and only force a full load in memory
state = [None]
for l in lines:
    data = l.split('"Overall evaluation:')
    if len(data) == 2:
        if data[0] != state[0]:
            if state[0] is not None:
                average = state[1]/state[2]
                print(state[0] + ", " + str(average))
            state = [data[0], 0., 0]
        state[1] += float(data[1])
        state[2] += 1
if state[0] is not None:
    average = state[1]/state[2]
    print(data[0] + ", " + str(average))

向python脚本添加简单的数学运算

4 个答案: