使用 R（基礎(chǔ)版本 3.5.2）包 LME4 擬合混合效果模型，通過 Python 3.6 的 rpy2 2.9.4 運(yùn)行能夠?qū)㈦S機(jī)效應(yīng)打印為索引數(shù)據(jù)幀，其中索引值是用于定義組的分類變量的值（使用 氡數(shù)據(jù)）：import rpy2.robjects as rofrom rpy2.robjects import pandas2ri, default_converterfrom rpy2.robjects.conversion import localconverterfrom rpy2.robjects.packages import importrlme4 = importr('lme4')mod = lme4.lmer(**kwargs) # Omitting arguments for brevityr_ranef = ro.r['ranef']re = r_ranef(mod)print(re[1]) Uppm (Intercept) floor (Intercept)AITKIN -0.0026783361 -2.588735e-03 1.742426e-09 -0.0052003670ANOKA -0.0056688495 -6.418760e-03 -4.482764e-09 -0.0128942943BECKER 0.0021906431 1.190746e-03 1.211201e-09 0.0023920238BELTRAMI 0.0093246041 8.190172e-03 5.135196e-09 0.0164527872BENTON 0.0018747838 1.049496e-03 1.746748e-09 0.0021082742BIG STONE -0.0073756824 -2.430404e-03 0.000000e+00 -0.0048823057BLUE EARTH 0.0112939204 4.176931e-03 5.507525e-09 0.0083908075BROWN 0.0069223055 2.544912e-03 4.911563e-11 0.0051123339將其轉(zhuǎn)換為 Pandas DataFrame，分類值將從索引中丟失并替換為整數(shù)：pandas2ri.ri2py_dataframe(r_ranef[1]) # r_ranef is a dict of dataframes Uppm (Intercept) floor (Intercept)0 -0.002678 -0.002589 1.742426e-09 -0.0052001 -0.005669 -0.006419 -4.482764e-09 -0.0128942 0.002191 0.001191 1.211201e-09 0.0023923 0.009325 0.008190 5.135196e-09 0.0164534 0.001875 0.001049 1.746748e-09 0.0021085 -0.007376 -0.002430 0.000000e+00 -0.0048826 0.011294 0.004177 5.507525e-09 0.0083917 0.006922 0.002545 4.911563e-11 0.005112如何保留原始索引的值？該文檔建議as.data.frame可能包含grp，這可能是我所追求的值，但我正在努力通過 rpy2 實(shí)現(xiàn)它；例如，r_ranef = ro.r['ranef.as.data.frame']不起作用
2 回答
qq_遁去的一_1
TA貢獻(xiàn)1725條經(jīng)驗(yàn) 獲得超8個(gè)贊
考慮row.names在 R 數(shù)據(jù)框中添加一個(gè)新列，然后將此列用于set_indexPandas 數(shù)據(jù)框中：
base = importr('base')
# ADD NEW COLUMN TO R DATA FRAME
re[1] = base.transform(re[1], index = base.row_names(re[1]))
# SET INDEX IN PANDAS DATA FRAME
py_df = (pandas2ri.ri2py_dataframe(re[1])
.set_index('index')
.rename_axis(None)
)
要對列表中的所有數(shù)據(jù)框執(zhí)行此操作，請使用 R 的lapply循環(huán)，然后使用 Python 的列表理解來獲取 Pandas 索引數(shù)據(jù)框的新列表。
base = importr('base')
mod = lme4.lmer(**kwargs) # Omitting arguments for brevity
r_ranef = lme4.ranef(mod)
# R LAPPLY
new_r_ranef = base.lapply(r_ranef, lambda df:
base.transform(df, index=base.row_names(df)))
# PYTHON LIST COMPREHENSION
py_df_list = [(pandas2ri.ri2py_dataframe(df)
.set_index('index')
.rename_axis(None)
) for df in new_r_ranef]
烙印99
TA貢獻(xiàn)1829條經(jīng)驗(yàn) 獲得超13個(gè)贊
import rpy2.robjects as ro
from rpy2.robjects import pandas2ri, default_converter
from rpy2.robjects.conversion import localconverter
r_dataf = ro.r("""
data.frame(
Uppm = rnorm(5),
row.names = letters[1:5]
)
""")
with localconverter(default_converter + pandas2ri.converter) as conv:
pd_dataf = conv.rpy2py(r_dataf)
# row names are "a".."f"
print(r_dataf)
# row names / indexes are now 0..4
print(pd_dataf)
這可能是 rpy2 中的一個(gè)小錯(cuò)誤/缺失功能，但解決方法相當(dāng)簡單：
with localconverter(default_converter + pandas2ri.converter) as conv:
pd_dataf = conv.rpy2py(r_dataf)
pd_dataf.index = r_dataf.rownames
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