在 sqldf 中处理 CSV 文件中的逗号

Question

我在这里sqldf returns zero observations 用一个可重复的例子来跟进我的问题。

我发现问题可能来自其中一个单元格中的“逗号”（“1,500+”），我认为我必须使用此处建议的过滤器sqldf, csv, and fields containing commas，但我不知道如何定义我的过滤器。下面是代码：

library(sqldf)

df <- data.frame("a" = c("8600000US01770" , "8600000US01937"),
             "b"= c("1,500+" , "-"),
             "c"= c("***" , "**"),
             "d"= c("(x)" , "(x)"),
             "e"= c("(x)" , "(x)"),
             "f"= c(992 , "-"))

write.csv(df, 'df_to_read.csv')  

# 'df_to_read.csv' looks like this:
"","a","b","c","d","e","f"
1,8600000US01770,1,500+,***,(x),(x),992
2,8600000US01937,-,**,(x),(x),-

Housing <- file("df_to_read.csv")
Housing_filtered <- sqldf('SELECT * FROM Housing', file.format = list(eol="\n"))

当我运行此代码时，我收到以下错误：

connection_import_file(conn@ptr, name, value, sep, eol, skip) 中的错误：RS_sqlite_import: df_to_read.csv 第 2 行预期有 7 列数据，但找到了 8 列

Answer 1

最好的方法是清理您的文件一次，这样您以后就不必再担心同一问题的分析了。这应该可以帮助您：

Housing <- readLines("df_to_read.csv")                            # read the file

n <- 6             # number of separators expected = number of columns expected - 1

library(stringr)
ln_idx <- ifelse(str_count(Housing, pattern = ",") == n, 0 , 1)
which(ln_idx == 1)               # line indices with issue, includes the header row
#[1] 2

检查具体问题并在相同的索引处写回您的文件。例如第 (2) 行：

Housing[2]
#[1] "1,8600000US01770,1,500+,***,(x),(x),992"            # hmm.. extra comma

Housing[2] = "1,8600000US01770,1500+,***,(x),(x),992"     # removed the extra comma
writeLines(Housing, "df_to_read.csv")

现在一切正常，一切顺利：

Housing <- file("df_to_read.csv")
Housing_filtered <- sqldf('SELECT * FROM Housing') 

# Housing_filtered 
#               a      b   c   d   e   f
# 1 8600000US01770  1500+ *** (x) (x) 992
# 2 8600000US01937      -  ** (x) (x)   -

Answer 2

问题来自阅读df$b 创建的专栏。该列中的第一个值包含逗号，因此sqldf() 函数将其视为分隔符。 解决此问题的一种方法是删除逗号或使用其他符号（如空格）。您也可以使用read.csv2.sql 函数：

library(sqldf)

df <- data.frame("a" = c("8600000US01770" , "8600000US01937"),
                 "b"= c("1,500+" , "-"),
                 "c"= c("***" , "**"),
                 "d"= c("(x)" , "(x)"),
                 "e"= c("(x)" , "(x)"),
                 "f"= c("992" , "-"))

write.csv(df, 'df_to_read.csv',row.names = FALSE )


Housing_filtered <- read.csv2.sql("df_to_read.csv", sql = "select * from file", header=TRUE)