peep

R's default head or tail functions print 6 or so rows and all columns. When you have a dataset that has a rather large number of columns, printing can be very poor, spilling over several rows.

The default output would look like

> dim(xy)
[1]  43 205

> head(xy)
    Sample   SLC25A5      MEOX1       CD4       HFE     GABRA3     RNH1        VIM       MYOC
1 sample 1 169.28930 0.08670971 18.975543 14.149516 0.10174355 5.021980 1674.99418  0.2268739
2 sample 2 122.55490 0.11898911 16.644021  5.116629 0.06980979 4.246349  610.15708  0.9339964
3 sample 3  13.49505 0.39190042  7.006248  8.686389 0.61902692 1.242957   88.91675 11.1807812
4 sample 4 111.84583 0.07831660  8.329725  2.129984 0.34920184 8.478207  194.47382  0.0000000
       CAPG      ZIC2       EPHA3      ELN      NTN1     ABCC9    CYBRD1      NTN4    NUAK1  SLC25A3
1 48.951242 0.9216751  5.97980198 3.591096 4.5935819 12.916405 45.980617 10.402553 6.992939 81.73932
2 10.396297 1.0434491 19.52954610 4.078562 5.2744688 40.005469 17.813941 15.819005 9.638139 60.31633
3  2.468217 3.6529801  2.96681949 5.578765 0.5051865  6.682470  1.563846  1.976812 2.269706 11.34410
4 24.162310 3.4463885  0.07879854 3.225239 2.1506768  1.343375 20.593887  4.886979 3.763131 56.44569
...

spilling columns over several lines with no end in sight for data with large number of colums (think expressions in bioinformatics).

It came down to typing xy[1:5, 1:5] for the rest of my life or develop a function that would make this easier. Enter peep. It prints a few first and last rows and columns. If any columns or rows have been omitted, it adds a horizontal or vertical delimiter of dots to indicate that there's something there.

> peep(xy)
       Sample SLC25A5   MEOX1    CD4    HFE  GABRA3    MMP12 SPON1   MSMB  CCL4  CCL3
01:  sample 1   169.3 0.08671  18.98  14.15  0.1017  ·  5.77 45.49  8.803 77.19 76.08
02:  sample 2   122.6   0.119  16.64  5.117 0.06981  · 114.9 274.7 0.2449 44.92 41.04
03:  sample 3    13.5  0.3919  7.006  8.686   0.619  · 4.861 2.803    278 9.299 5.599
04:  sample 4   111.8 0.07832   8.33   2.13  0.3492  · 146.8 560.5      0 25.22 16.66
05:  sample 5   92.04       0 0.9135 0.8531  0.8672  · 91.63 8.617  4.848 8.899  6.03
06:  sample 6   63.44  0.3779  4.487  11.16   4.573  · 273.6  7.65  20.03 15.84 9.727
            ·       ·       ·      ·      ·       ·  ·     ·     ·      ·     ·     ·
38: sample 38   119.9 0.06032  2.194  8.856       0  · 1.158 4.308      0 8.464 19.14
39: sample 39   83.36       0  5.265  1.505       0  · 7.512 225.4      0 17.25 16.83
40: sample 40   100.1       0  4.783  1.692       0  · 88.81 18.54      0 55.66 5.438
41: sample 41   77.02 0.01632  14.92  3.389 0.01915  ·     0 68.71      0 18.79  11.5
42: sample 42   39.37  0.1706  4.553  4.284  0.2891  · 6.476 20.21  8.893 21.19 9.978
43: sample 43   36.44       0  1.064  4.322  0.4157  · 0.544 5.627      0 5.444 2.933

This works has been inspired by data.table and pandas, a package for working with DataFrames in Python.

Installation

To install from GitHub, try using package remotes

remotes::install_github("romunov/peep")