Question

我有一个26列100行的PandasData帧。我想从第25列（称为未命名：24）第50行中提取特定值并将其放入列表中。有没有办法做到这一点？我的列名为Unnamed：0，Unnamed：1，...，Unnamed：25;行只是0到99：

     Unnamed 0:   .....     Unnamed: 24     Unnamed: 25
  0
  1
  .
  .
  50                              50
  .
  .
  99

和

Numbers = []

我想将此值50附加到第24行第50行的Numbers。

我的数据框是x = xls.parse（'excelfile1.xls'），我正在从Excel电子表格中解析数据框

Answer 1

您可以使用iloc：

Numbers = []
value =  df1.iloc[24,50]
Numbers.append(value)

或者作为更一般的例子：

import pandas as pd
import numpy as np

df = pd.DataFrame(index=range(0,5), data=[range(5*i,5*i+5) for i in range(0,5)])

df：

    0   1   2   3   4
0   0   1   2   3   4
1   5   6   7   8   9
2  10  11  12  13  14
3  15  16  17  18  19
4  20  21  22  23  24

并打印df.iloc[2,2]返回12

Answer 2

For selecting a single value from a DataFrame or Series, at (label based scalar indexing) and iat (index based scalar indexing) are generally the fastest.

numbers = []
numbers.append(df.iat(50, 24))

Lets say you had three pairs of numbers representing row and column index values where you want to lookup a value from your DataFrame. You could efficiently accomplish this goal as follows:

pairs = [(10, 20), (20, 25), (30, 30)]
[numbers.append(df.iat(row, col)) for row, col in pairs]

从pandas数据框中选择基于行和列的数据值以附加到列表

2 个答案: