Last updated: 2022-11-12
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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)We can use the df.fillna() method to replace missing values with a specific value. Let’s start by creating a dataframe with missing values.
import pandas as pd
import numpy as np
df = pd.DataFrame({'col1': [1,2],
'col2': [3,np.nan],
'col3': ['A',np.nan]})
print(df) col1 col2 col3
0 1 3.0 A
1 2 NaN NaNTo replace the missing value with 0, just do .fillna(0).
# replace all NA values with 0, inplace = True means df itself will be modefied
df.fillna(0, inplace = True)
print(df) col1 col2 col3
0 1 3.0 A
1 2 0.0 0Or if you only wnat to replace missing values in one particular column, simply select it first
df2 = df.copy()
df2['col2'].fillna(0, inplace = True)
print(df2) col1 col2 col3
0 1 3.0 A
1 2 0.0 0We can use either replace() in base R to replace all missings in a dataframe with a specific value, or replace_na in tidyr to offer tailored replacement for each specific column.
df = data.frame(col1 = c(1,2),
col2 = c(3, NA),
col3 = c('A',NA))
print(df) col1 col2 col3
1 1 3 A
2 2 NA <NA># use replace() in base R to replace all missings to 0
replace(df, is.na(df), 0) col1 col2 col3
1 1 3 A
2 2 0 0library(tidyr)
# or use replace_na() in tidyverse to offer tailored replacement for each column.
df |> replace_na(list(col2=0,col3="Unknown")) col1 col2 col3
1 1 3 A
2 2 0 Unknown
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] tidyr_1.2.1 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 DBI_1.1.3
[21] cli_3.4.1 rstudioapi_0.14 yaml_2.3.5 xfun_0.33
[25] fastmap_1.1.0 dplyr_1.0.10 stringr_1.4.1 knitr_1.40
[29] generics_0.1.3 fs_1.5.2 vctrs_0.4.2 sass_0.4.2
[33] tidyselect_1.2.0 grid_4.2.1 rprojroot_2.0.3 glue_1.6.2
[37] R6_2.5.1 fansi_1.0.3 rmarkdown_2.17 purrr_0.3.5
[41] magrittr_2.0.3 whisker_0.4 ellipsis_0.3.2 promises_1.2.0.1
[45] htmltools_0.5.3 assertthat_0.2.1 renv_0.16.0 httpuv_1.6.6
[49] utf8_1.2.2 stringi_1.7.8 cachem_1.0.6