Last updated: 2022-12-02

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Introduction

Provide a 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)

Create the dataframe in Python

In the simple dataframe below, the 1st and 3rd row are the same.

import pandas as pd

df = pd.DataFrame([[1, 'A'], 
                   [2, 'B'], 
                   [1, 'A']], 
                  columns = ["col1", "col2"])

print(df)
   col1 col2
0     1    A
1     2    B
2     1    A

Load the dataframe into R

df <- py$df #access df as saved in Python(py) above

print(df)
  col1 col2
1    1    A
2    2    B
3    1    A

Method #25-26. Handling Duplicates

Python

In Python, we can use duplicated() to identify duplicated rows.

df.duplicated() #the default setting only marks the second appearance of the duplicated rows
0    False
1    False
2     True
dtype: bool
df.duplicated(keep=False) #add `keep = False` to identify all appearances of the duplicated rows
0     True
1    False
2     True
dtype: bool

The above result can be used to identify duplicated rows in a dataframe. Check out how the results below are slightly different.

df[df.duplicated(keep=False)]
   col1 col2
0     1    A
2     1    A
df[df.duplicated()]
   col1 col2
2     1    A

To drop duplicated rows in Python, we can use the drop_duplicates() method as follows.

df.drop_duplicates()
   col1 col2
0     1    A
1     2    B

R

In base R, we also have a duplciated() function, notice that only one of the row [1, 'A'] was marked as duplicated.

df |> duplicated()
[1] FALSE FALSE  TRUE
# use the result to identify duplicated rows
df[duplicated(df),]
  col1 col2
3    1    A

To drop duplicated rows in R, we can use the unique() method in base R.

df |> unique()
  col1 col2
1    1    A
2    2    B

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] 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     cli_3.4.1       
[21] rstudioapi_0.14  yaml_2.3.5       xfun_0.33        fastmap_1.1.0   
[25] stringr_1.4.1    knitr_1.40       fs_1.5.2         vctrs_0.4.2     
[29] sass_0.4.2       grid_4.2.1       rprojroot_2.0.3  glue_1.6.2      
[33] R6_2.5.1         fansi_1.0.3      rmarkdown_2.17   magrittr_2.0.3  
[37] whisker_0.4      promises_1.2.0.1 htmltools_0.5.3  renv_0.16.0     
[41] httpuv_1.6.6     utf8_1.2.2       stringi_1.7.8    cachem_1.0.6