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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.
# enable python in RMarkdown
library(reticulate)
import pandas as pd
df = pd.DataFrame([[6, 5, 10],
[5, 8, 6],
[5, 10, 6],
[4, 7, 10]],
columns = ["Maths", "Science", "English"])
print(df)
Maths Science English
0 6 5 10
1 5 8 6
2 5 10 6
3 4 7 10
df <- py$df #access df as saved in Python(py) above
print(df)
Maths Science English
1 6 5 10
2 5 8 6
3 5 10 6
4 4 7 10
use unique() to find unique values, and nunique() for the number of unique values
df['Maths'].unique() # get unique values in the 'Maths' column
array([6, 5, 4], dtype=int64)
df['English'].unique() # get unique values in the 'English' column
array([10, 6], dtype=int64)
df['Maths'].nunique() # get the number of unique values in the 'Maths' column
3
df['English'].nunique() # get the number of unique values in the 'English' column
2
To get unique values of a column, we select the column then apply the unique() function. This can also be used to find unique value combinations across multiple variables. To count the number of unique values or value combinations, just apply length() function to count its length.
For python, unique() can’t be used to get unique value combinations across multiple variables. If this is what you seek to do, please refer to method 26 in Avi’s article which we will get to translate soon.
library(dplyr)
# unique values in one single column
df |>
select(Maths) |>
unique()
Maths
1 6
2 5
4 4
# unique combination of values across multiple columns
df |>
select(Maths, English) |>
unique()
Maths English
1 6 10
2 5 6
4 4 10
# count the number of unique values or value combination
df |>
select(Maths, English) |>
unique() |>
length()
[1] 2
sessionInfo()
R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
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_1.1.2 reticulate_1.30
loaded via a namespace (and not attached):
[1] Rcpp_1.0.11 pillar_1.9.0 compiler_4.2.1 bslib_0.5.0
[5] later_1.3.1 jquerylib_0.1.4 git2r_0.32.0 workflowr_1.7.0
[9] tools_4.2.1 digest_0.6.33 lattice_0.20-45 jsonlite_1.8.7
[13] evaluate_0.21 lifecycle_1.0.3 tibble_3.2.1 png_0.1-8
[17] pkgconfig_2.0.3 rlang_1.1.1 Matrix_1.4-1 cli_3.6.1
[21] rstudioapi_0.15.0 yaml_2.3.7 xfun_0.39 fastmap_1.1.1
[25] withr_2.5.0 stringr_1.5.0 knitr_1.43 generics_0.1.3
[29] fs_1.6.2 vctrs_0.6.3 sass_0.4.7 tidyselect_1.2.0
[33] grid_4.2.1 rprojroot_2.0.3 glue_1.6.2 R6_2.5.1
[37] fansi_1.0.4 rmarkdown_2.23 magrittr_2.0.3 whisker_0.4.1
[41] promises_1.2.0.1 htmltools_0.5.5 renv_1.0.0 httpuv_1.6.11
[45] utf8_1.2.3 stringi_1.7.12 cachem_1.0.8