Can't import this excel file into R -


i'm having trouble importing file r. file obtained website: https://report.nih.gov/award/index.cfm, clicked "import table" , downloaded .xls file year 1992.

this image might describe how retrieved data image describing how retrieved data nih database

here's i've tried typing console, along results:

input:

> library('readxl') > data1992 <- read_excel("1992.xls")

output:

not excel file error in eval(substitute(expr), envir, enclos) :    failed open /home/chrx/documents/nih funding awards, 1992 - 2016/1992.xls

input:

> data1992 <- read.csv ("1992.xls", sep ="\t")

output:

error in read.table(file = file, header = header, sep = sep, quote = quote,  :    more columns column names

i'm not sure whether or not relevant, i'm using galliumos (linux). because i'm using linux, excel isn't installed on computer. libreoffice is.

why bother getting data in , out of .csv if it's right there on web page scrape?

# note query parameters in url when apply filter, e.g. fy= url <- 'http://report.nih.gov/award/index.cfm?fy=1992'  library('rvest') library('magrittr') library('dplyr') df <- url %>%         read_html() %>%         html_nodes(xpath='//*[@id="orgtable"]') %>%         html_table()%>%          extract2(1) %>%         mutate(funding = as.numeric(gsub('[^0-9.]','',funding)))  head(df)

returns

                              organization          city state       country awards funding 1 a.t. still university of health sciences    kirksville    mo united states      3  356221 2                     aac associates, inc.        vienna    va united states     10 1097158 3       aaron diamond aids research center      new york    ny united states      3  629946 4                      abbott laboratories north chicago    il united states      4 1757241 5                            abiomed, inc.       danvers    ma united states      6 2161146 6                     abratech corporation     sausalito    ca united states      1  450411

if need loop through years 1992 present, or similar, programmatic approach save lot of time versus handling bunch of flat files.


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