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Introduction

Python to R translation of 30 essential Pandas methods introduced by Avi Chawla in The Only 30 Methods You Should Master To Become A Pandas Pro published on TowardsDataScience.

Set up

# enable python in RMarkdown
library(reticulate)

Method #6. Viewing Top N Rows

Python

Use head() to show the top N rows.

import pandas as pd

df = pd.read_csv('data/iris.csv')

# print the top 3 rows in the dataframe
print(df.head(3))
   Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species
0           5.1          3.5           1.4          0.2  setosa
1           4.9          3.0           1.4          0.2  setosa
2           4.7          3.2           1.3          0.2  setosa

We can also sort the dataframe first then show the top N. For more on sorting a dataframe, please refer to method 13.

# to sort the dataframe first then check out the top N
df.sort_values('Sepal.Length')\
  .head(5)
    Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species
13           4.3          3.0           1.1          0.1  setosa
42           4.4          3.2           1.3          0.2  setosa
38           4.4          3.0           1.3          0.2  setosa
8            4.4          2.9           1.4          0.2  setosa
41           4.5          2.3           1.3          0.3  setosa

R

To do these tasks in R is pretty straightforward.

df <- py$df # get the dataframe from python

# print the top 3 rows in the dataframe
print(df |>  head(3))
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa

To sort first, we can use the arrange() function in the dplyr package.

library(dplyr) 

# to sort the dataframe first then check out the top N
df |> 
  arrange(Sepal.Length) |> 
  head(5)
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          4.3         3.0          1.1         0.1  setosa
2          4.4         2.9          1.4         0.2  setosa
3          4.4         3.0          1.3         0.2  setosa
4          4.4         3.2          1.3         0.2  setosa
5          4.5         2.3          1.3         0.3  setosa

sessionInfo()
R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19043)

Matrix products: default

locale:
[1] LC_COLLATE=English_Australia.utf8  LC_CTYPE=English_Australia.utf8   
[3] LC_MONETARY=English_Australia.utf8 LC_NUMERIC=C                      
[5] LC_TIME=English_Australia.utf8    

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
[1] dplyr_1.0.10    reticulate_1.26

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.9       pillar_1.8.1     compiler_4.2.1   bslib_0.4.0     
 [5] later_1.3.0      jquerylib_0.1.4  git2r_0.30.1     workflowr_1.7.0 
 [9] tools_4.2.1      digest_0.6.29    lattice_0.20-45  jsonlite_1.8.2  
[13] evaluate_0.17    lifecycle_1.0.3  tibble_3.1.8     png_0.1-7       
[17] pkgconfig_2.0.3  rlang_1.0.6      Matrix_1.4-1     DBI_1.1.3       
[21] cli_3.4.1        rstudioapi_0.14  yaml_2.3.5       xfun_0.33       
[25] fastmap_1.1.0    stringr_1.4.1    knitr_1.40       generics_0.1.3  
[29] fs_1.5.2         vctrs_0.4.2      sass_0.4.2       tidyselect_1.2.0
[33] grid_4.2.1       rprojroot_2.0.3  glue_1.6.2       R6_2.5.1        
[37] fansi_1.0.3      rmarkdown_2.17   magrittr_2.0.3   whisker_0.4     
[41] promises_1.2.0.1 htmltools_0.5.3  assertthat_0.2.1 renv_0.16.0     
[45] httpuv_1.6.6     utf8_1.2.2       stringi_1.7.8    cachem_1.0.6