Question

我有一个简单的.csv格式数据需要先操作才能创建符合此数据的绘图。但是，我理解如何从python中操作.csv格式数据。我想在R中应用相同的逻辑，但我不知道如何做到这一点。

以下是来自.csv文件的示例数据，但加载到R.我已经为我们创建了代码来讨论这个问题。

df <- data.frame(Name = c("AC", "AC", "PT", "PT", "OR", "OR"),
    useless_column = c("","","A",3,4," "),
  measurement = c("H", "", "K", "M", "", "H"),
  amount = c(12, 54, 20, 87, 75, 22),
    useless_column = c("","","A",3,4," "))

在python中，我通常会这样做：

import csv
import os
import glob
import sys
fileList = glob.glob("R:xxxxxxxxxxxxxxxxxxxxx\*.csv")
for inputFile in fileList:
        outputFilename = inputFile + "output.csv"
        csvInput = csv.reader(open(inputFile,'r'),delimiter=",")
        outputFile = open(outputFilename,'w')
        outputFile.write("Name,measurement,amount\n")
        csvInput.next()
        for line in csvInput:
            if line[2] == "H":
               meas = "100"
            elif line[2] == "K":
               meas = "1000"
            elif line[2] == "M":
               meas = "1000000"
            else:
               meas = "1"
            amount = int(meas) * line[3]

            outputFile.write(",".join(line[0],line[2],amount+"\n"]))
outputFile.close()

在python中，我可以加载csv然后使用for循环来识别csv文件中的每一行。然后在继续我的分析之前定制我的输出文件。从上面，我希望我的输出类似于下面的代码是R格式：

    df <- data.frame(Name = c("AC", "AC", "PT", "PT", "OR", "OR"),
  measurment = c("H", "", "K", "M", "", "H"),
  amount = c(1200, 54, 20000, 87000000, 75, 2200))

我想知道在R中这样做吗？我有一个小的R代码，任何人都可以指导我进入正确的方向：

x <- read.csv("xxxx.csv", header=T,sep=",")
xC = ncol(x)
xR = nrow(x)
op = data.frame(matrix(data = x, nrow= xR, ncol=3,byrow=T))
for (x in :xC)
{
    for (r in 1:xR)
    {
    xxxxxxxx

    }

Answer 1

在R中调整python代码意味着放弃循环以支持向量化操作。在这里，我们可以根据命名向量创建meas，然后计算金额：

# dictionnary of measurement values:
m <- c(H = 100, K = 1000, M = 1000000)

# create meas based on measurement
df$meas <- m[df$measurment]
df$meas[is.na(df$meas)] <- 1
# compute amount
df$amount <- df$meas * df$amount

数据

df <- data.frame(Name = c("AC", "AC", "PT", "PT", "OR", "OR"),
                 measurment = c("H", "", "K", "M", "", "H"),
                 amount = c(1200, 54, 20000, 87000000, 75, 2200))

Answer 2

您是否尝试过使用pandas.read_csv？或者csv文件是如此不规则，以至于您无法使用pandas的read_csv方法来阅读它们？

您可以执行for循环来操作每个文件中的数据，然后将其附加到主文件DataFrame。

示例：

import pandas as pd

PATH = '/home/data/' # Example path

master_df = pd.DataFrame()
for inputFile in fileList:
    csv_file = pd.read_csv(path + inputFile, sep=',')
    H_index = csv_file[csv_file.loc[:, 2] == 'H'].index
    csv_file.loc[H_index, 3] = csv_file.loc[H_index, 3] * 100
    master_df = master_df.append(csv_file)

我已跳过操作的K和M部分。

您可以通过执行类似

的操作直接从master_df绘图

master_df.plot()

Answer 3

你已经获得了读取数据的代码（read.csv），所以我认为你的主要斗争是在manimpuation本身吗？

如果是这样，你可以继续使用批量if和for循环，但我认为有更简单的方法。类似的东西：

df <- read.csv("xxxx.csv", header=T,sep=",")
df$meas <- df$measurement # Create a new column called 'meas' by copying column 'measurement'
df$meas[df$meas == "H"] <- 100 # Replace H's with 100
df$meas[df$meas == "K"] <- 1000
df$meas[df$meas == "M"] <- 1000000
df$value <- df$meas * df$amount

R中的.csv数据操作而不是python

3 个答案: