对多个 geojson 文件运行分析

Question

我有大约 113 个 geojson 文件，我以前主要在 QGIS 中处理过这些文件。我现在的目标是能够同时将所有文件导入 R 并对附加到每个相应层的基础属性表进行分析。我已经找到了导入一个文件并在转换为数据框后进行任何所需分析的最佳方法。我在文件夹中的文件都如下所示：0cfb16c1-90c2-412d-bb60-2fec34c75e9a.geojson

我用于这一步的代码是：

library(rgdal)
map1 <- readOGR(dsn = "/Users/chris/Documents/GeorgetownMPPMSFS/McCourtMPP/BIGWork/BIGDataFiles/maps/sampled_maps/0cfb16c1-90c2-412d-bb60-2fec34c75e9a.geojson", layer = "0cfb16c1-90c2-412d-bb60-2fec34c75e9a")
summary(map1)
map1 <- as.data.frame(map1)

我想在所有 geojson 文件上运行我在该地图上所做的相同分析，而不必一一进行。我进行的与选举重新划分指标相关的分析包括在此处：

cfbdata$reptotal <- (cfbdata$surveyed_republican_percentage/100)*cfbdata$surveyed_total
cfbdata$demtotal <- (cfbdata$surveyed_democrat_percentage/100)*cfbdata$surveyed_total
cfbdata$NAME <- NULL
aggdata <-aggregate(cfbdata, by=list(cfbdata$cluster), 
                    FUN=sum, na.rm=TRUE)
# Rep district victory is 1 and Dem district victory is 0
aggdata$result <- ifelse(aggdata$reptotal > aggdata$demtotal,1, ifelse(aggdata$demtotal > aggdata$reptotal,0, NA))

EffGapCalc <- subset(aggdata, select=c("cluster","reptotal","demtotal","surveyed_total", "result"))

# Step 1: Calculate Dem Wasted, Rep Wasted, and Net Wasted

EffGapCalc$repwasted <- ifelse(EffGapCalc$result == 1, EffGapCalc$reptotal - (.51*EffGapCalc$surveyed_total), ifelse(EffGapCalc$result == 0, EffGapCalc$reptotal, NA))

EffGapCalc$demwasted <- ifelse(EffGapCalc$result == 0, EffGapCalc$demtotal - (.51 * EffGapCalc$surveyed_total), ifelse(EffGapCalc$result == 1, EffGapCalc$demtotal, NA))

EffGapCalc$netwasted <- abs(EffGapCalc$repwasted - EffGapCalc$demwasted)

# Step 2: Sum Total Wasted Rep and Dem Votes
totrepwasted <- sum(EffGapCalc$repwasted)
totdemwasted <- sum(EffGapCalc$demwasted)
netwaste <- ifelse(totrepwasted>totdemwasted, totrepwasted-totdemwasted, ifelse(totrepwasted<totdemwasted, totdemwasted-totrepwasted))
netwaste
# Democrats had a net waste (more wasted votes) of 74289.6

# Step 3: Divide Net Wasted by Total Number of Votes Case
sum(EffGapCalc$surveyed_total)
totalsurvtot <- sum(EffGapCalc$surveyed_total)
netwaste/totalsurvtot
# Efficiency Gap = .0359 [3.60%]

目标是对所有 113 个 GEOJSON 文件运行相同的分析，并获得 113 个“效率差距”数字的列表，如上面的 .0359。

我在 stackoverflow 和其他地方搜索了许多问题，但没有找到合适的解决方案。虽然我最初认为 for 循环最适合这个，但根据我在其他地方读到的内容，lapply() 实际上可能是更好的选择。我面临的挑战是确保正确导入作为 'lapply()' 的一部分

我尝试使用失败的代码是：

library(rgdal)
fileNames <- list.files(path = "/Users/chris/Documents/GeorgetownMPPMSFS/McCourtMPP/BIGWork/BIGDataFiles/maps/sampled_maps", pattern="*.geojson", full.names = TRUE)

lapply(fileNames, function(x) {
  map1 <- readOGR(dsn = x, layer = x)
  map1 <- as.data.frame(map1)
  out <- map1$reptotal <- (map1$surveyed_republican_percentage/100)*map1$surveyed_total;
  map1$demtotal <- (map1$surveyed_democrat_percentage/100)*map1$surveyed_total;
  map1$NAME <- NULL;
  aggdata <-aggregate(map1, by=list(map1$cluster), 
                      FUN=sum, na.rm=TRUE);
  aggdata$result <- ifelse(aggdata$reptotal > aggdata$demtotal,1, ifelse(aggdata$demtotal > aggdata$reptotal,0, NA));

  EffGapCalc <- subset(aggdata, select=c("cluster","reptotal","demtotal","surveyed_total", "result"));
  # Step 1: Calculate Dem Wasted, Rep Wasted, and Net Wasted
  EffGapCalc$repwasted <- ifelse(EffGapCalc$result == 1, EffGapCalc$reptotal - (.51*EffGapCalc$surveyed_total), ifelse(EffGapCalc$result == 0, EffGapCalc$reptotal, NA));

  EffGapCalc$demwasted <- ifelse(EffGapCalc$result == 0, EffGapCalc$demtotal - (.51 * EffGapCalc$surveyed_total), ifelse(EffGapCalc$result == 1, EffGapCalc$demtotal, NA));

  EffGapCalc$netwasted <- abs(EffGapCalc$repwasted - EffGapCalc$demwasted);

  # Step 2: Sum Total Wasted Rep and Dem Votes
  totrepwasted <- sum(EffGapCalc$repwasted);
  totdemwasted <- sum(EffGapCalc$demwasted);
  netwaste <- ifelse(totrepwasted>totdemwasted, totrepwasted-totdemwasted, ifelse(totrepwasted<totdemwasted, totdemwasted-totrepwasted));
  netwaste

  # Step 3: Divide Net Wasted by Total Number of Votes Case
  totalsurvtot <- sum(EffGapCalc$surveyed_total);
  netwaste/totalsurvtot;

  write.table(out, "/Users/chris/Documents/GeorgetownMPPMSFS/McCourtMPP/BIGWork/BIGDataFiles", sep="\t", quote=F, row.names=F, col.names=T)
})

在这一点上，我已经尝试了两天来解决这个问题，但只会变得更加困惑。任何帮助将不胜感激！

Answer 1

简单的测试代码：

lapply(fileNames, function(x) {
  map1 <- readOGR(dsn = x, layer = x)
}

假设您的案例失败了，我们知道问题出在这一行。这使得这里的人更容易看到它是一个更简单的问题。请始终尝试尽量减少您的问题，这将帮助我们帮助您，并且在许多情况下它可以让您自己解决。进行中...

readOGR 对于 geoJSON 需要一个文件路径和一个图层名称，并且该代码将使用 geojson 包中的测试文件将文件路径作为图层名称提供，如下所示：：

> testfile <- list.files(path = path, pattern="*.geojson", full.names = TRUE)[5]

快速检查我们已经得到它：

> file.exists(testfile)
[1] TRUE

然后尝试阅读：

> d = readOGR(dsn=testfile, layer=testfile)
Error in ogrInfo(dsn = dsn, layer = layer, encoding = encoding, use_iconv = use_iconv,  : 
  Cannot open layer

那么我们如何从文件路径中获取层名呢？为此我们有ogrListLayers：

> ogrListLayers(testfile)
[1] "OGRGeoJSON"
attr(,"driver")
[1] "GeoJSON"
attr(,"nlayers")
[1] 1

现在看起来很奇怪，但它是图层名称和一些额外属性的向量，您可以为此忽略它们。此测试层的层名称为“OGRGeoJSON”。假设您的 geoJSON 仅是您可以执行的一层：

> d = readOGR(dsn=testfile, layer=ogrListLayers(testfile))
OGR data source with driver: GeoJSON 
Source: "/home/rowlings/R/x86_64-pc-linux-gnu-library/3.4/geojson/examples/linestring_one.geojson", layer: "OGRGeoJSON"
with 1 features
It has 2 fields
Warning message:
In readOGR(dsn = testfile, layer = ogrListLayers(testfile)) :
  Z-dimension discarded

现在我认为 geoJSON 只能有一层，或者 readOGR 默认为第一层，所以如果您知道 geoJSON 中只有一层，您可以省略 @ 987654331@ 参数并返回相同的对象：

> d2 = readOGR(dsn=testfile)
OGR data source with driver: GeoJSON 
Source: "/home/rowlings/R/x86_64-pc-linux-gnu-library/3.4/geojson/examples/linestring_one.geojson", layer: "OGRGeoJSON"
with 1 features
It has 2 fields
Warning message:
In readOGR(dsn = testfile) : Z-dimension discarded