在 R 中使用 Python 代码来更改数据框答案

【问题标题】：Use Python code in R in order to change a dataframe在 R 中使用 Python 代码来更改数据框
【发布时间】：2021-06-04 03:50:11
【问题描述】：

我只是想知道是否可以在 R 中使用 python 代码来修改或创建新表？

这是我在 python 中使用的代码示例

这是一个数据框：

   species family    Events      groups
    1     SP1      A     10,22          G1
    2     SP1      B         7          G2
    3     SP1    C,D 4,5,6,1,3 G3,G4,G5,G6
    4     SP2      A     22,10          G1
    5     SP2    D,C 6,5,4,3,1 G4,G6,G5,G3
    6     SP3      C 4,5,3,6,1    G3,G6,G5
    7     SP3      E         7          G2
    8     SP3      A        10          G1
    9     SP4      C        7,22        G12

在 Python 中使用此代码：

g = df['groups'].apply(lambda x: set(x.split(',')))   # explode into sets
# keep the larger set from g containing the current one and make it back a string
g2 = g.apply(lambda s: ','.join(sorted(
    g[g.apply(lambda x: x.issuperset(s))].max())))

resul = df[['species', 'family', 'Events']].groupby(g2).agg(
    lambda x: ','.join(sorted(set((i for j in x for i in j.split(',')))))
    ).reset_index()

我可以将其转换为：

       species family     Events       groups
0  SP1,SP2,SP3      A      10,22           G1
1          SP4      C       22,7          G12
2      SP1,SP3    B,E          7           G2
3  SP1,SP2,SP3    C,D  1,3,4,5,6  G3,G4,G5,G6

我只是想知道是否有办法调用python 代码并直接在R 上生成它们？

事实上，我需要研究 R，但我更熟悉 Python 代码。

Python 字典等效数据框：

{'species': {1: 'SP1', 2: 'SP1', 3: 'SP1', 4: 'SP2', 5: 'SP2', 6: 'SP3', 7: 'SP3', 8: 'SP3', 9: 'SP4'}, 'family': {1: 'A', 2: 'B', 3: 'C,D', 4: 'A', 5: 'D,C', 6: 'C', 7: 'E', 8: 'A', 9: 'C'}, 'Events': {1: '10,22', 2: '7', 3: '4,5,6,1,3', 4: '22,10', 5: '6,5,4,3,1', 6: '4,5,3,6,1', 7: '7', 8: '10', 9: '7,22'}, 'groups': {1: 'G1', 2: 'G2', 3: 'G3,G4,G5,G6', 4: 'G1', 5: 'G4,G6,G5,G3', 6: 'G3,G6,G5', 7: 'G2', 8: 'G1', 9: 'G12'}}

r equivalent dataframe: 
structure(list(species = structure(c(1L, 1L, 1L, 2L, 2L, 3L, 
3L, 3L, 4L), .Label = c("SP1", "SP2", "SP3", "SP4"), class = "factor"), 
    family = structure(c(1L, 2L, 4L, 1L, 5L, 3L, 6L, 1L, 3L), .Label = c("A", 
    "B", "C", "C,D", "D,C", "E"), class = "factor"), Events = structure(c(2L, 
    7L, 5L, 3L, 6L, 4L, 7L, 1L, 8L), .Label = c("10", "10,22", 
    "22,10", "4,5,3,6,1", "4,5,6,1,3", "6,5,4,3,1", "7", "7,22"
    ), class = "factor"), groups = structure(c(1L, 3L, 4L, 1L, 
    6L, 5L, 3L, 1L, 2L), .Label = c("G1", "G12", "G2", "G3,G4,G5,G6", 
    "G3,G6,G5", "G4,G6,G5,G3"), class = "factor")), class = "data.frame", row.names = c(NA, 
-9L))

【问题讨论】：

标签： python r python-3.x

【解决方案1】：

您可以在下面给出的示例中像这样在 r 中使用 reticulate 包

Sys.setenv(RETICULATE_PYTHON = "C:\\Users\\anaconda3\\python.exe")
library(reticulate)

str1 = "

import pandas as pd
cars = {'Brand': ['Honda Civic','Toyota Corolla','Ford Focus','Audi A4'],
    'Price': [22000,25000,27000,35000]}

df = pd.DataFrame(cars, columns = ['Brand', 'Price'])

print (df)

"

py_run_string(str1)

【讨论】：

【解决方案2】：

您可以使用reticulate 包：https://rstudio.github.io/reticulate/

【讨论】：