Reports

Guessing by the screenshot, the error seems to caused because the header has 7 fields and the rest of the data has 8 (probably a trailing comma). This causes read.csv to use the first field (Date) as the "row name" of the dataset.

From the help page for read.csv (to access use ?read.csv):

If there is a header and the first row contains one fewer field than the number of columns, the first column in the input is used for the row names. Otherwise if row.names is missing, the rows are numbered.

Try to verify if your original CSV files looks something similar to the csv_text I created below.

  # Header has 7 fields, data rows have 8 (trailing comma)
  # → First field (Date) becomes row names (per read.csv docs)
  # → Trailing empty field gets assigned to "Volume"

  csv_text <- 'Date,Name,Close,High,Low,Open,Volume
08/31/2015,eBay Inc,27.11,28.935,23.23,28.09,271799372,
09/30/2015,eBay Inc,24.44,27.60,23.76,26.54,267684281,'

  read.csv(text = csv_text)
#>                Date  Name  Close  High   Low      Open Volume
#> 08/31/2015 eBay Inc 27.11 28.935 23.23 28.09 271799372     NA
#> 09/30/2015 eBay Inc 24.44 27.600 23.76 26.54 267684281     NA

The best solution I can suggest is to use {readr} and read_csv which will correctly import the data while also warning you about the error. Note that I added locale to properly parse your date which seems to be in the MM/DD/YYYY format.

  library(readr)
  # The I(...) function is used only because my csv is a 'string' and not an actual
  # csv file stored in my computer.
  read_csv(I(csv_text), locale = locale(date_format = "%m/%d/%Y"))
#> Warning: One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> Rows: 2 Columns: 7
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr  (1): Name
#> dbl  (4): Close, High, Low, Open
#> num  (1): Volume
#> date (1): Date
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> # A tibble: 2 × 7
#>   Date       Name     Close  High   Low  Open    Volume
#>   <date>     <chr>    <dbl> <dbl> <dbl> <dbl>     <dbl>
#> 1 2015-08-31 eBay Inc  27.1  28.9  23.2  28.1 271799372
#> 2 2015-09-30 eBay Inc  24.4  27.6  23.8  26.5 267684281

So, your final solution should be this:

library(readr)
ebay <- read_csv("EBAY.csv", locale = locale(date_format = "%m/%d/%Y"))

Please let me know if this fixes your issue. In the future, use something like dput(head(ebay)) to output a small version of your dataset.

^{Created on 2025-12-04 with}^{reprex v2.1.1}

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