Move first array element one row down-CodePudding

I am trying to implement the same python code for the following r code:

nm <- c("Sepal.Length" ,"Sepal.Width" , "Petal.Length", "Petal.Width", "Species")
nm_data <-
  sapply(1:length(nm), function(i)
    c(nm[-(0:i)], nm[0:i])) %>% data.frame()
comb_predictors <- list()
for (i in 1:length(nm_data)) {
  comb_predictors[[i]] <- nm_data[1:i, ]
}

It should move the first element in the list one row down, and for each column until the last column when it returns to the beginning.

As for nm_data, I have tried the following python attempt:

import pandas as pd
import numpy as np
nm = ["Sepal.Length" ,"Sepal.Width" , "Petal.Length", "Petal.Width", "Species"]


def tbl(data, x):
    df=np.transpose((data[::-x], data[0:x]))
    return(pd.DataFrame(df))
cnt = [x for x in range(0, len(nm))]
list(map(tbl, nm, cnt))

However, I get the following result:

[  0
 0  
 1  ,
    0
 0  S
 1  S,
     0
 0  Pe
 1  Pe,
      0
 0  Pet
 1  Pet,
       0
 0  Spec
 1  Spec]

If I do

tbl(nm, 1)


0   1
0   Species Sepal.Length
1   Petal.Width Sepal.Width
2   Petal.Length    Petal.Length
3   Sepal.Width Petal.Width
4   Sepal.Length    Species

however, I cannot get it like the expected output. I know that for comb_predictors I just run it in a for loop so thats easy enough to get. But I am having trouble with getting nm_data with python.

My expected result:

1  Sepal.Width Petal.Length  Petal.Width      Species Sepal.Length
2 Petal.Length  Petal.Width      Species Sepal.Length  Sepal.Width
3  Petal.Width      Species Sepal.Length  Sepal.Width Petal.Length
4      Species Sepal.Length  Sepal.Width Petal.Length  Petal.Width
5 Sepal.Length  Sepal.Width Petal.Length  Petal.Width      Species

CodePudding user response：

You overcomplicated it - you need only

data = [nm[x:]   nm[:x] for x in range(1, len(nm) 1)]

And eventually later you can convert it to DataFrame

Minimal working code

import pandas as pd

nm = ["Sepal.Length" ,"Sepal.Width" , "Petal.Length", "Petal.Width", "Species"]

data = [nm[x:]   nm[:x] for x in range(1, len(nm) 1)]

df = pd.DataFrame(data)

print(df)

Result:

              0             1             2             3             4
0   Sepal.Width  Petal.Length   Petal.Width       Species  Sepal.Length
1  Petal.Length   Petal.Width       Species  Sepal.Length   Sepal.Width
2   Petal.Width       Species  Sepal.Length   Sepal.Width  Petal.Length
3       Species  Sepal.Length   Sepal.Width  Petal.Length   Petal.Width
4  Sepal.Length   Sepal.Width  Petal.Length   Petal.Width       Species

EDIT:

You can also use collections.deque() to rotate list:

import pandas as pd
import collections

nm = ["Sepal.Length" ,"Sepal.Width" , "Petal.Length", "Petal.Width", "Species"]

data = []

d = collections.deque(nm)

for _ in range(len(nm)):
    d.rotate(-1)
    data.append(list(d))
    #print(list(d))

df = pd.DataFrame(data)

print(df)