mirror of
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(v2.1.1.9086) website update
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Package: AMR
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Version: 2.1.1.9084
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Date: 2024-09-30
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Version: 2.1.1.9086
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Date: 2024-10-02
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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data analysis and to work with microbial and antimicrobial properties by
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2
NEWS.md
2
NEWS.md
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# AMR 2.1.1.9084
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# AMR 2.1.1.9086
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*(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://msberends.github.io/AMR/#latest-development-version).)*
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@ -169,6 +169,7 @@ pre_commit_lst$MO_WHO_PRIORITY_GENERA <- c(
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"Coccidioides",
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"Cryptococcus",
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"Enterococcus",
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"Escherichia",
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"Fusarium",
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"Haemophilus",
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"Helicobacter",
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"B_ECRBM_RMSM" "Erythromicrobium ramosum" "synonym" "Bacteria" "Pseudomonadota" "Alphaproteobacteria" "Sphingomonadales" "Erythrobacteraceae" "Erythromicrobium" "ramosum" "" "species" "Yurkov et al., 1994" "LPSN" "776049" "515600" "12988" "3221406" 2 "434593006"
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"B_ERMNS" "Erythromonas" "synonym" "Bacteria" "Pseudomonadota" "Alphaproteobacteria" "Sphingomonadales" "Sphingomonadaceae" "Erythromonas" "" "" "genus" "Yurkov et al., 1997" "LPSN" "515601" "1302" "515246" "8926" 2 ""
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"B_ERMNS_URSN" "Erythromonas ursincola" "synonym" "Bacteria" "Pseudomonadota" "Alphaproteobacteria" "Sphingomonadales" "Sphingomonadaceae" "Erythromonas" "ursincola" "" "species" "Yurkov et al., 1997" "LPSN" "776051" "515601" "774092" 2 ""
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"B_ESCHR" "Escherichia" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "" "" "genus" "Castellani et al., 1919" "facultative anaerobe" "LPSN" "515602" "482" "11158430" 1.15 "407310004,407251000,407281008,407284000,407283006,407160000,407285004,407159005,407287007,407290001,407291002,407289005,407293004,407222004,407295006,407294005,407297003,407260008,407299000,407300008,407301007,103429008,124994003,407303005,407306002,407305003,407308001,407253002,407254008,407262000,407263005,407265003,407264004,407267006,407269009,407256005,407271009,407199008,407273007,407275000,407258006,407278003,407279006,407277008,407231004,407235008,407234007,407233001,407237000,407239002,407241001,407243003,407245005,407246006,407227005,407229008,715877003,407203008,407161001,407204002,407158002,407207009,407206000,407209007,407211003,407214006,407213000,407219001,407217004,407218009,407216008,407220007,407221006,407224003,407225002,414103002,407197005,407198000,407196001,407202003,407201005,407182007,407184008,407163003,407186005,407190007,407189003,407188006,407192004,407194003,407165005,407169004,407168007,407173001,407172006,407171004,407175008,406629008,406628000,407177000,407179002,407180004,407156003,407157007,116398008,417207000,64735005,713416009"
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"B_ESCHR_ADCR" "Escherichia adecarboxylata" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "adecarboxylata" "" "species" "Leclerc, 1962" "likely facultative anaerobe" "LPSN" "776052" "515602" "777447" 1.15 ""
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"B_ESCHR_ALBR" "Escherichia albertii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "albertii" "" "species" "Huys et al., 2003" "facultative anaerobe" "LPSN" "776053" "515602" "5427575" 1.15 "419388003"
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"B_ESCHR_BLTT" "Escherichia blattae" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "blattae" "" "species" "Burgess et al., 1973" "likely facultative anaerobe" "LPSN" "776056" "515602" "788468" 1.5 ""
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"B_ESCHR_COLI" "Escherichia coli" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "coli" "" "species" "Castellani et al., 1919" "facultative anaerobe" "LPSN" "776057" "515602" "11286021" 1.15 "1095001000112106,715307006,737528008,416989002,116397003,414097009,414098004,414099007,414100004,116395006,735270003,116396007,83285000,116394005,112283007,710886005,710887001,710888006,710889003,414132004,721892009,416812001,416740004,417216001,457541006,710253004,416530004,417189006,409800005,713925008,444771000124108,838549008"
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"B_ESCHR_COLI_COLI" "Escherichia coli coli" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "coli" "coli" "subspecies" "GBIF" "776057" "12233256" "11286021" 1.15 ""
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"B_ESCHR_COLI_EXPR" "Escherichia coli expressing" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "coli" "expressing" "subspecies" "AmSOD" "GBIF" "776057" "12239548" "11286021" 1.15 ""
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"B_ESCHR_DYSN" "Escherichia dysenteriae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "dysenteriae" "" "species" "likely facultative anaerobe" "GBIF" "515602" "10862979" 1.5 ""
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"B_ESCHR_FRGS" "Escherichia fergusonii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "fergusonii" "" "species" "Farmer et al., 1985" "facultative anaerobe" "LPSN" "776059" "515602" "5427571" 1.15 "72461005"
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"B_ESCHR_HRMN" "Escherichia hermannii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "hermannii" "" "species" "Brenner et al., 1983" "facultative anaerobe" "LPSN" "776060" "515602" "5427572" 1.5 "85786000"
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"B_ESCHR_MRMT" "Escherichia marmotae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "marmotae" "" "species" "Liu et al., 2015" "likely facultative anaerobe" "LPSN" "792928" "515602" "8869052" 1.5 "14961000146107"
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"B_ESCHR_RUYS" "Escherichia ruysiae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "ruysiae" "" "species" "Van der Putten et al., 2021" "likely facultative anaerobe" "LPSN" "17322" "515602" "11776954" 1.5 ""
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"B_ESCHR_VLNR" "Escherichia vulneris" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "vulneris" "" "species" "Brenner et al., 1983" "likely facultative anaerobe" "LPSN" "776063" "515602" "796273" "5427573" 1.15 ""
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"B_ESCHR" "Escherichia" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "" "" "genus" "Castellani et al., 1919" "facultative anaerobe" "LPSN" "515602" "482" "11158430" 1 "407310004,407251000,407281008,407284000,407283006,407160000,407285004,407159005,407287007,407290001,407291002,407289005,407293004,407222004,407295006,407294005,407297003,407260008,407299000,407300008,407301007,103429008,124994003,407303005,407306002,407305003,407308001,407253002,407254008,407262000,407263005,407265003,407264004,407267006,407269009,407256005,407271009,407199008,407273007,407275000,407258006,407278003,407279006,407277008,407231004,407235008,407234007,407233001,407237000,407239002,407241001,407243003,407245005,407246006,407227005,407229008,715877003,407203008,407161001,407204002,407158002,407207009,407206000,407209007,407211003,407214006,407213000,407219001,407217004,407218009,407216008,407220007,407221006,407224003,407225002,414103002,407197005,407198000,407196001,407202003,407201005,407182007,407184008,407163003,407186005,407190007,407189003,407188006,407192004,407194003,407165005,407169004,407168007,407173001,407172006,407171004,407175008,406629008,406628000,407177000,407179002,407180004,407156003,407157007,116398008,417207000,64735005,713416009"
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"B_ESCHR_ADCR" "Escherichia adecarboxylata" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "adecarboxylata" "" "species" "Leclerc, 1962" "likely facultative anaerobe" "LPSN" "776052" "515602" "777447" 1 ""
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"B_ESCHR_ALBR" "Escherichia albertii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "albertii" "" "species" "Huys et al., 2003" "facultative anaerobe" "LPSN" "776053" "515602" "5427575" 1 "419388003"
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"B_ESCHR_BLTT" "Escherichia blattae" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "blattae" "" "species" "Burgess et al., 1973" "likely facultative anaerobe" "LPSN" "776056" "515602" "788468" 1 ""
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"B_ESCHR_COLI" "Escherichia coli" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "coli" "" "species" "Castellani et al., 1919" "facultative anaerobe" "LPSN" "776057" "515602" "11286021" 1 "1095001000112106,715307006,737528008,416989002,116397003,414097009,414098004,414099007,414100004,116395006,735270003,116396007,83285000,116394005,112283007,710886005,710887001,710888006,710889003,414132004,721892009,416812001,416740004,417216001,457541006,710253004,416530004,417189006,409800005,713925008,444771000124108,838549008"
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"B_ESCHR_COLI_COLI" "Escherichia coli coli" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "coli" "coli" "subspecies" "GBIF" "776057" "12233256" "11286021" 1 ""
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"B_ESCHR_COLI_EXPR" "Escherichia coli expressing" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "coli" "expressing" "subspecies" "AmSOD" "GBIF" "776057" "12239548" "11286021" 1 ""
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"B_ESCHR_DYSN" "Escherichia dysenteriae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "dysenteriae" "" "species" "likely facultative anaerobe" "GBIF" "515602" "10862979" 1 ""
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"B_ESCHR_FRGS" "Escherichia fergusonii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "fergusonii" "" "species" "Farmer et al., 1985" "facultative anaerobe" "LPSN" "776059" "515602" "5427571" 1 "72461005"
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"B_ESCHR_HRMN" "Escherichia hermannii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "hermannii" "" "species" "Brenner et al., 1983" "facultative anaerobe" "LPSN" "776060" "515602" "5427572" 1 "85786000"
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"B_ESCHR_MRMT" "Escherichia marmotae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "marmotae" "" "species" "Liu et al., 2015" "likely facultative anaerobe" "LPSN" "792928" "515602" "8869052" 1 "14961000146107"
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"B_ESCHR_RUYS" "Escherichia ruysiae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "ruysiae" "" "species" "Van der Putten et al., 2021" "likely facultative anaerobe" "LPSN" "17322" "515602" "11776954" 1 ""
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"B_ESCHR_VLNR" "Escherichia vulneris" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Escherichia" "vulneris" "" "species" "Brenner et al., 1983" "likely facultative anaerobe" "LPSN" "776063" "515602" "796273" "5427573" 1 ""
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"P_ESTST" "Estiastra" "accepted" "Protozoa" "" "" "" "" "Estiastra" "" "" "genus" "Eisenack, 1959" "GBIF" "3208159" "7" 2 ""
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"P_ESTST_MAGN" "Estiastra magna" "accepted" "Protozoa" "" "" "" "" "Estiastra" "magna" "" "species" "Eisenack, 1959" "GBIF" "4918097" "3208159" 2 ""
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"P_ESTST_MINM" "Estiastra minima" "accepted" "Protozoa" "" "" "" "" "Estiastra" "minima" "" "species" "Volkova, 1969" "GBIF" "4918094" "3208159" 2 ""
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index.md
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index.md
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* Integrates with **WHONET**, ATC, **EARS-Net**, PubChem, **LOINC**, **SNOMED CT**, and **NCBI**
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* 100% free of costs and dependencies, highly suitable for places with **limited resources**
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<a href="https://chatgpt.com/g/g-M4UNLwFi5-amr-for-r-assistant"><img src="../AMRforRGPT.svg" style="min-width: 300px; width: 10%;" /></a>
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<div style="display: flex; font-size: 0.8em;">
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<p style="text-align:left; width: 50%;"><small><a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR</a></small></p>
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<p style="text-align:right; width: 50%;"><small><a href="https://doi.org/10.18637/jss.v104.i03" target="_blank">https://doi.org/10.18637/jss.v104.i03</a></small></p>
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@ -207,7 +207,7 @@ Furthermore,
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When calculating the matching score, all characters in \eqn{x} and \eqn{n} are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.
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All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.598}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.381}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
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All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.381}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
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}
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\section{Reference Data Publicly Available}{
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When calculating the matching score, all characters in \eqn{x} and \eqn{n} are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.
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All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.598}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.381}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
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All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.381}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
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}
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\section{Reference Data Publicly Available}{
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--bs-dropdown-link-hover-color: var(--amr-green-light) !important;
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--bs-dropdown-link-hover-bg: var(--amr-green-dark) !important;
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--bs-dropdown-link-active-color: white !important;
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}
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/* Python page */
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body.amr-for-python * {
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--amr-green-light: #FFD43B; /* Python yellow */
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--amr-green-light-rgb: 255, 212, 59;
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--amr-green-dark: #306998; /* Python blue */
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--amr-green-dark-rgb: 48, 105, 152;
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--amr-green-middle: #b1bc5e; /* Adjusted middle yellow */
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--amr-green-middle-rgb: 177, 188, 94;
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--bs-success: var(--amr-green-dark) !important;
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--bs-light: var(--amr-green-light) !important;
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--bs-info: var(--amr-green-middle) !important;
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--bs-link-color: var(--amr-green-dark) !important;
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--bs-link-color-rgb: var(--amr-green-dark-rgb) !important;
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--bs-primary: var(--amr-green-dark) !important;
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--bs-primary-color: var(--amr-green-dark) !important;
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--bs-primary-rgb: var(--amr-green-dark-rgb) !important;
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--bs-secondary-color: var(--amr-green-dark) !important;
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--bs-navbar-active-color: var(--amr-green-light) !important;
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--bs-dropdown-bg: var(--amr-green-dark) !important;
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--bs-dropdown-link-hover-color: var(--amr-green-light) !important;
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--bs-dropdown-link-hover-bg: var(--amr-green-dark) !important;
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}
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.nav-text.text-muted,
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.bg-primary .navbar-nav .show>.nav-link,
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.bg-primary .navbar-nav .nav-link.active,
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// make Python part more fancy - prepare for CSS
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if (window.location.href.includes('AMR_for_Python')) {
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$('body').addClass('amr-for-python');
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$('img[src="logo.svg"]').attr('src', 'logo_python.svg');
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$('img[src="../logo.svg"]').attr('src', '../logo_python.svg');
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}
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// add doctoral titles to authors
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<?xml version="1.0" encoding="utf-8"?>
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<browserconfig>
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<msapplication>
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<tile>
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<square150x150logo src="/mstile-150x150.png?v=newlogo"/>
|
||||
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</svg>
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|
Before Width: | Height: | Size: 34 KiB |
@ -1,19 +0,0 @@
|
||||
{
|
||||
"name": "AMR for R",
|
||||
"short_name": "AMR for R",
|
||||
"icons": [
|
||||
{
|
||||
"src": "/android-chrome-192x192.png?v=newlogo",
|
||||
"sizes": "192x192",
|
||||
"type": "image/png"
|
||||
},
|
||||
{
|
||||
"src": "/android-chrome-512x512.png?v=newlogo",
|
||||
"sizes": "512x512",
|
||||
"type": "image/png"
|
||||
}
|
||||
],
|
||||
"theme_color": "#128f76",
|
||||
"background_color": "#128f76",
|
||||
"display": "standalone"
|
||||
}
|
||||
@ -26,7 +26,9 @@ knitr::opts_chunk$set(
|
||||
|
||||
The `AMR` package for R is an incredible tool for antimicrobial resistance (AMR) data analysis, providing extensive functionality for working with microbial and antimicrobial properties. But what if you're working in Python and still want to benefit from the robust features of `AMR`?
|
||||
|
||||
Luckily, there is no need to port the package to Python! With the help of `rpy2`, a powerful Python package, you can easily access R from Python and call functions from the `AMR` package to process your own data. This post will guide you through setting up `rpy2` and show you how to use R functions from `AMR` in Python to supercharge your antimicrobial resistance analysis.
|
||||
The best way is to access R directly from Python with the help of `rpy2`, a simple yet powerful Python package. You can easily call functions from the `AMR` package to process your own data in your own Python environment. This post will guide you through setting up `rpy2` and show you how to use R functions from `AMR` in Python to supercharge your antimicrobial resistance analysis.
|
||||
|
||||
<a href="https://chatgpt.com/g/g-M4UNLwFi5-amr-for-r-assistant"><img src="../AMRforRGPT.svg" style="min-width: 300px; width: 10%;" /></a>
|
||||
|
||||
# What is `rpy2`?
|
||||
|
||||
@ -43,17 +45,37 @@ Before diving into the examples, you’ll need to install both R and `rpy2`. Her
|
||||
|
||||
## Step 1: Install R
|
||||
|
||||
Ensure that you have R installed on your system. You can download R from [CRAN](https://cran.r-project.org/).
|
||||
Ensure that R is installed on your system. R has minimal dependencies and is very simple to install:
|
||||
|
||||
* **Linux**
|
||||
* Ubuntu / Debian:
|
||||
`sudo apt install r-base`
|
||||
* Fedora:
|
||||
`sudo dnf install R`
|
||||
* CentOS/RHEL:
|
||||
`sudo yum install R`
|
||||
* Arch Linux:
|
||||
`sudo pacman -S r`
|
||||
* **macOS** (with Homebrew):
|
||||
`brew install r`
|
||||
* **Other Systems:**
|
||||
Visit the [CRAN download page](https://cran.r-project.org).
|
||||
|
||||
## Step 2: Install the `AMR` package in R
|
||||
|
||||
Once you have R installed, open your R console and install the `AMR` package:
|
||||
On Linux and macOS, open Terminal and run:
|
||||
|
||||
```bash
|
||||
Rscript -e 'install.packages("AMR")'
|
||||
```
|
||||
|
||||
For other systems, open your R console and install the `AMR` package by running:
|
||||
|
||||
```r
|
||||
install.packages("AMR")
|
||||
```
|
||||
|
||||
You can also install the latest development version of the `AMR` package if needed:
|
||||
On any system, you can also install the latest development version of the `AMR` package by setting `repos` to our beta channel:
|
||||
|
||||
```r
|
||||
install.packages("AMR", repos = "https://msberends.r-universe.dev")
|
||||
@ -69,7 +91,7 @@ pip install rpy2
|
||||
|
||||
## Step 4: Test `rpy2` Installation
|
||||
|
||||
To ensure everything is set up correctly, you can test your installation by running the following Python script:
|
||||
To ensure everything is set up correctly, you can test your installation by running the following Python script, which essentially runs R in the background:
|
||||
|
||||
```python
|
||||
import rpy2.robjects as ro
|
||||
@ -80,11 +102,11 @@ ro.r('1 + 1')
|
||||
|
||||
If this returns `2`, you're good to go!
|
||||
|
||||
# Working with AMR in Python using `rpy2`
|
||||
# Working with `AMR` in Python
|
||||
|
||||
Now that we have `rpy2` set up, let’s walk through some practical examples of using the `AMR` package within Python.
|
||||
|
||||
## Example 1: Loading `AMR` and Example Data
|
||||
## Example 1: Converting Taxonomic Data
|
||||
|
||||
Let’s start by converting taxonomic user input to valid taxonomy using the `AMR` package, from within Python:
|
||||
|
||||
@ -94,9 +116,6 @@ import rpy2.robjects as ro
|
||||
from rpy2.robjects.packages import importr
|
||||
from rpy2.robjects import pandas2ri
|
||||
|
||||
# Enable conversion between pandas and R data frames
|
||||
pandas2ri.activate()
|
||||
|
||||
# Load the AMR package from R
|
||||
amr = importr('AMR')
|
||||
|
||||
@ -105,15 +124,12 @@ data = pd.DataFrame({
|
||||
'microorganism': ['E. coli', 'S. aureus', 'P. aeruginosa', 'K. pneumoniae']
|
||||
})
|
||||
|
||||
# Convert the Python DataFrame to an R DataFrame
|
||||
r_data = pandas2ri.py2rpy(data)
|
||||
|
||||
# Apply mo_name() from the AMR package to the 'microorganism' column
|
||||
ro.globalenv['r_data'] = r_data
|
||||
ro.globalenv['r_data'] = data
|
||||
ro.r('r_data$mo_name <- mo_name(r_data$microorganism)')
|
||||
|
||||
# Retrieve and print the modified R DataFrame in Python
|
||||
result = ro.r('as.data.frame(r_data)')
|
||||
result = ro.r('r_data')
|
||||
result = pandas2ri.rpy2py(result)
|
||||
print(result)
|
||||
```
|
||||
|
||||
Loading…
Reference in New Issue
Block a user