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Reads all CSV files from a directory

Source: R/read_csv_files_from_dir.R
read_csv_files_from_dir.Rd

read_csv_files_from_dir reads all csv files from the "~/data" directory and returns an appended dataframe. The resulting dataframe will be in the same order as the CSV files in the directory.

Usage

read_csv_files_from_dir(dir_path = ".", col_types = NULL, .id = NULL)

Arguments

dir_path

Path to the directory containing the CSV files.

col_types

One of NULL, a cols() specification, or a string. See vignette("readr") for more details.

If NULL, all column types will be inferred from guess_max rows of the input, interspersed throughout the file. This is convenient (and fast), but not robust. If the guessed types are wrong, you'll need to increase guess_max or supply the correct types yourself.

Column specifications created by list() or cols() must contain one column specification for each column. If you only want to read a subset of the columns, use cols_only().

Alternatively, you can use a compact string representation where each character represents one column:

  • c = character

  • i = integer

  • n = number

  • d = double

  • l = logical

  • f = factor

  • D = date

  • T = date time

  • t = time

  • ? = guess

  • _ or - = skip

By default, reading a file without a column specification will print a message showing what readr guessed they were. To remove this message, set show_col_types = FALSE or set options(readr.show_col_types = FALSE).

.id

The name of a column in which to store the file path. This is useful when reading multiple input files and there is data in the file paths, such as the data collection date. If NULL (the default) no extra column is created.

Value

A tibble. If there is any column type mismatch during data frames row binding, an error will occur. This is because R cannot combine columns of different types. For example, you cannot combine a column of integers with a column of characters.

See also

read_excel_files_from_dir() which reads Excel workbooks data from a directory.

Examples


directory <- system.file("csvfolder",  package = "bulkreadr")

read_csv_files_from_dir(dir_path = directory, .id = "cut")
#> # A tibble: 260 × 10
#>    cut                   carat color clarity depth table price     x     y     z
#>    <chr>                 <dbl> <chr> <chr>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 /home/runner/work/_t…  2    I     SI1      65.9    60 13764  7.8   7.73  5.12
#>  2 /home/runner/work/_t…  0.7  H     SI1      65.2    58  2048  5.49  5.55  3.6 
#>  3 /home/runner/work/_t…  1.51 E     SI1      58.4    70 11102  7.55  7.39  4.36
#>  4 /home/runner/work/_t…  0.7  D     SI2      65.5    57  1806  5.56  5.43  3.6 
#>  5 /home/runner/work/_t…  0.35 F     VVS1     54.6    59  1011  4.85  4.79  2.63
#>  6 /home/runner/work/_t…  0.5  E     VS2      64.9    56  1397  5.01  4.95  3.23
#>  7 /home/runner/work/_t…  1    E     SI1      65.1    61  4435  6.15  6.08  3.98
#>  8 /home/runner/work/_t…  1.09 J     VS2      64.6    58  3443  6.48  6.41  4.16
#>  9 /home/runner/work/_t…  0.98 H     SI2      67.9    60  2777  6.05  5.97  4.08
#> 10 /home/runner/work/_t…  0.7  F     SI1      65.3    54  1974  5.58  5.54  3.63
#> # ℹ 250 more rows

# Column types mismatch error --------------------------------------
# If the `read_csv_files_from_dir()` function complains about a data type mismatch,
# then set the `col_types` argument to `"c"`.
# This will make all the column types in the resulting dataframe be characters.