如何在 r 数据框中应用模糊查找

Question

I have 2 data frames. 1. df1 is having sales data with unstructured headers, coming from OLAP cube.

df1 <- data.frame("[Time].[Fiscal Year].[Fiscal Year].[MEMBER_CAPTION]"= c("FY18","FY19","FY20"), "[Measures].[USD]"=c(100,200,300))
names(df1) <- c("[Time].[Fiscal Year].[Fiscal Year].[MEMBER_CAPTION]","[Measures].[USD]")

2. df2 is having list of unstructured headers and respective cleansed headers.

df2<- data.frame("RawHeaderName"=c("[Time].[Fiscal Year]","[Measures].[USD]"),"ReportDisplayName"=c("FiscalYear","USD"))

my requirement is when df2$RawHeaderName value matches (fuzzy matches) with df1 headers then i need to replace df1 headers with df2$ReportDisplayName value. Final out should be like below.

FinalOutput <- data.frame("FiscalYear" =c("FY18","FY19","FY20"),"USD"=c(100,200,300))

Please help me to solve the problem. I already tried with library("fuzzyjoin"),library("dplyr") libraries but no luck.

Answer 1

I think you're simply looking for names(df1) <- c('Fiscal Year', 'USD') which modifies df1 to:

  Fiscal Year USD
1        FY18 100
2        FY19 200
3        FY20 300

Answer 2

After speeding some time, below code is helping me to solve 50% problem only when match criteria exists. Still need to explore on fuzzy match.

library("dplyr")

df1 <- data.frame("[Time].[Fiscal Year].[Fiscal Year].[MEMBER_CAPTION]"= c("FY18","FY19","FY20"), "[Measures].[USD]"=c(100,200,300))
names(df1) <- c("[Time].[Fiscal Year].[Fiscal Year].[MEMBER_CAPTION]","[Measures].[USD]")


df2<- data.frame("RawHeaderName"=c("[Time].[Fiscal Year].[Fiscal Year].[MEMBER_CAPTION]","[Measures].[USD]"),"ReportDisplayName"=c("FiscalYear","USD"))


Extract_Headers <- (names(df1))
Extract_Headers <- data.frame("Headers"=as.character(Extract_Headers))
df2$RawHeaderName <- as.character(df2$RawHeaderName)
df2$ReportDisplayName <- as.character(df2$ReportDisplayName)
Cleansed_Headers <- Extract_Headers %>% inner_join (df2, by =c("Headers"="RawHeaderName"))
names(df1)<- Cleansed_Headers$ReportDisplay