Question

以 R 演示为例：

df <- matrix(1:100, nrow = 10, ncol = 10)

df ：

> df
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    1   11   21   31   41   51   61   71   81    91
 [2,]    2   12   22   32   42   52   62   72   82    92
 [3,]    3   13   23   33   43   53   63   73   83    93
 [4,]    4   14   24   34   44   54   64   74   84    94
 [5,]    5   15   25   35   45   55   65   75   85    95
 [6,]    6   16   26   36   46   56   66   76   86    96
 [7,]    7   17   27   37   47   57   67   77   87    97
 [8,]    8   18   28   38   48   58   68   78   88    98
 [9,]    9   19   29   39   49   59   69   79   89    99
[10,]   10   20   30   40   50   60   70   80   90   100

现在我要删除2:8行和3:7列，所以我做了：

> eliminated.rows <- 2:8
> eliminated.cols <- 3:7
> df <- df[-eliminated.rows, -eliminated.cols]

然后我得到了我想要的东西：

> df
     [,1] [,2] [,3] [,4] [,5]
[1,]    1   11   71   81   91
[2,]    9   19   79   89   99
[3,]   10   20   80   90  100

问题是：

如何使用Python实现我的目标？

修改

具体来说，如果我得到要删除的行和列的列表，比如eliminated_rows = list(), eliminated_cols = list()，我希望结果df = df[-eliminated_rows, -eliminated_cols]与python一起使用。

任何帮助将不胜感激。

Answer 1

你可以这样做：

df = pd.DataFrame(np.random.randint(0,100,size=(10, 10)), columns=list('ABCDEFGHIJ'))
row_i= df.index.isin(range(1,8))
col_i=df.index.isin(range(2,7))
df.iloc[~row_i,~col_i]

在python中从0开始时要小心索引。

Answer 2

试试这个（小心索引）：

Try this:

matrix = []
for row in range(0,100,10):
    column = [i for i in range(row,row+10)]
    matrix.append(column)
columns_to_remove = [1,2,8]
rows_to_remove = [4,5,9]
for i in rows_to_remove:
    matrix.pop(i)
for remaining_rows in matrix:
    for remove_column in matrix:
        matrix.pop(matrix[remaining_rows][remove_column])

Answer 3

检查select data from data frame后，我认为此解决方案可能更容易理解：

E.g。 3 * 3 DataFrame，消除行1,2，列0,1：

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randint(0, 9, size = (3, 3)))

#print df

eliminated_rows = [1, 2] #rows to eliminated
eliminated_cols = [0, 1] #cols to eliminated

range_rows = range(0, df.shape[0])
remaining_rows = [row for row in range_rows if row not in eliminated_rows]

range_cols = range(0, df.shape[1])
remaining_cols = [col for col in range_cols if col not in eliminated_cols]

df = df.iloc[remaining_rows, remaining_cols]

#print df

原始数据框3 * 3：

结果：

   2
0  3

R-Python：如何消除特定的行和列？

3 个答案: