Determine the data types of a data frame s columns

Question

I m using R and have loaded data into a dataframe using read csv    How do I determine the data type of each column in the data frame

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Since it wasn t stated clearly  I just add this    I was looking for a way to create a table which holds the number of occurrences of all the data types    Say we have a data frame with two numeric and one logical column  dta  lt - data frame a   c 1 2 3                      b   c 4 5 6                      c   c TRUE  FALSE  TRUE     You can summarize the number of columns of each data type with that  table unlist lapply dta  class      logical numeric          1       2    This comes extremely handy  if you have a lot of columns and want to get a quick overview    To give credit  This solution was inspired by the answer of  Cybernetic

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Another option is using the map function of the purrr package   library purrr  map df class

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If you import the csv file as a data frame  and not matrix   you can also use summary default  summary default mtcars        Length Class  Mode    mpg  32     -none- numeric cyl  32     -none- numeric disp 32     -none- numeric hp   32     -none- numeric drat 32     -none- numeric wt   32     -none- numeric qsec 32     -none- numeric vs   32     -none- numeric am   32     -none- numeric gear 32     -none- numeric carb 32     -none- numeric

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Your best bet to start is to use  str     To explore some examples  let s make some data     set seed 3221     this makes the example exactly reproducible my data  lt - data frame y rnorm 5                          x1 c 1 5                          x2 c TRUE  TRUE  FALSE  FALSE  FALSE                         X3 letters 1 5      Wilmer E Henao H s solution is very streamlined     sapply my data  class          y        x1        x2        X3   numeric   integer   logical    factor     Using str   gets you that information plus extra goodies  such as the levels of your factors and the first few values of each variable      str my data   data frame    5 obs  of  4 variables    y   num  1 03 1 599 -0 818 0 872 -2 682   x1  int  1 2 3 4 5   x2  logi  TRUE TRUE FALSE FALSE FALSE   X3  Factor w  5 levels  a   b   c   d      1 2 3 4 5    Gavin Simpson s approach is also streamlined  but provides slightly different information than class       sapply my data  typeof         y        x1        x2        X3   double   integer   logical   integer    For more information about class  typeof  and the middle child  mode  see this excellent SO thread  A comprehensive survey of the types of things in R   mode  and  class  and  typeof  are insufficient

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Here is a function that is part of the helpRFunctions package that will return a list of all of the various data types in your data frame  as well as the specific variable names associated with that type    install package  devtools     Only needed if you dont have this installed  library devtools  install github  adam-m-mcelhinney helpRFunctions   library helpRFunctions  my data  lt - data frame y rnorm 5                      x1 c 1 5                      x2 c TRUE  TRUE  FALSE  FALSE  FALSE                     X3 letters 1 5   t  lt - list df var types my data  t factor t integer t logical t numeric   You could then do something like var my data t numeric     Hope this is helpful

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I would suggest  sapply foo  typeof    if you need the actual types of the vectors in the data frame  class   is somewhat of a different beast   If you don t need to get this information as a vector  i e  you don t need it to do something else programmatically later   just use str foo    In both cases foo would be replaced with the name of your data frame

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For small data frames   library tidyverse   as tibble mtcars    gives you a print out of the df with data types    A tibble  32 x 11      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb     lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   1  21       6  160    110  3 9   2 62  16 5     0     1     4     4  2  21       6  160    110  3 9   2 88  17 0     0     1     4     4  3  22 8     4  108     93  3 85  2 32  18 6     1     1     4     1   For large data frames   glimpse mtcars    gives you a structured view of data types   Observations  32 Variables  11   mpg   lt dbl gt  21 0  21 0  22 8  21 4  18 7  18 1  14 3  24 4  22 8  19 2  17 8  16 4  17       cyl   lt dbl gt  6  6  4  6  8  6  8  4  4  6  6  8  8  8  8  8  8  4  4  4  4  8  8  8  8        disp  lt dbl gt  160 0  160 0  108 0  258 0  360 0  225 0  360 0  146 7  140 8  167 6  167 6      hp    lt dbl gt  110  110  93  110  175  105  245  62  95  123  123  180  180  180  205  215      drat  lt dbl gt  3 90  3 90  3 85  3 08  3 15  2 76  3 21  3 69  3 92  3 92  3 92  3 07  3 0      wt    lt dbl gt  2 620  2 875  2 320  3 215  3 440  3 460  3 570  3 190  3 150  3 440  3 440      qsec  lt dbl gt  16 46  17 02  18 61  19 44  17 02  20 22  15 84  20 00  22 90  18 30  18 90      vs    lt dbl gt  0  0  1  1  0  1  0  1  1  1  1  0  0  0  0  0  0  1  1  1  1  0  0  0  0        am    lt dbl gt  1  1  1  0  0  0  0  0  0  0  0  0  0  0  0  0  0  1  1  1  0  0  0  0  0        gear  lt dbl gt  4  4  4  3  3  3  3  4  4  4  4  3  3  3  3  3  3  4  4  4  3  3  3  3  3        carb  lt dbl gt  4  4  1  1  2  1  4  2  2  4  4  3  3  3  4  4  4  1  2  1  1  2  2  4  2        To get a list of the columns  data type  as said by  Alexandre above    map mtcars  class    gives a list of data types    mpg  1   numeric    cyl  1   numeric    disp  1   numeric    hp  1   numeric    To change data type of a column   library hablar   mtcars   gt      convert chr mpg  am             int carb     converts columns mpg and am to character and the column carb to integer     A tibble  32 x 11    mpg     cyl  disp    hp  drat    wt  qsec    vs am     gear  carb     lt chr gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt chr gt   lt dbl gt   lt int gt   1 21        6  160    110  3 9   2 62  16 5     0 1         4     4  2 21        6  160    110  3 9   2 88  17 0     0 1         4     4  3 22 8      4  108     93  3 85  2 32  18 6     1 1         4     1  4 21 4      6  258    110  3 08  3 22  19 4     1 0         3     1

User · Answer

Simply pass your data frame into the following function    data types  lt - function frame      res  lt - lapply frame  class    res frame  lt - data frame unlist res     barplot table res frame   main  Data Types   col  steelblue   ylab  Number of Features       to produce a plot of all data types in your data frame  For the iris dataset we get the following    data types iris

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sapply yourdataframe  class    Where yourdataframe is the name of the data frame you re using

[r] Determine the data types of a data frame's columns

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