Python 在计算期间将np.array重新排列为浮点64数据时出错

我从CSV文件中读取变量“RF”，然后我有一个“数组”数据。我想在两个变量之间建立一个等式。因此，我正在将阵列数据集转换为“RF”数据格式。在我的CSV文件中，我有8个变量，但目前我只读取一个变量。当我执行代码时，它给出了一些错误

import numpy as np 
import pandas as pd 
import csv
data_df = pd.read_csv('poly2_decpred_juneRF.csv', header=0, nrows=67)
y1 = data_df['RF']
y1.head(67)

finalpred1=[2.22, 2.33, 3.33, 1.21, 2.22, 2.33, 3.33, 1.21, 2.22, 2.33, 3.33, 1.21, 2.22, 2.33, 3.33, 1.21, 2.33]
s = pd.Series(finalpred1, name='RF')
print(s)
y111=y1[50:67]
print(y111)
diff = ((y111-s)/y111)*100
print(diff)

输出如下所示：

0    NaN
1    NaN
2    NaN
3    NaN
4    NaN
5    NaN
6    NaN
7    NaN
8    NaN
9    NaN
10   NaN
11   NaN
12   NaN
13   NaN
14   NaN
15   NaN
16   NaN
50   NaN
51   NaN
52   NaN
53   NaN
54   NaN
55   NaN
56   NaN
57   NaN
58   NaN
59   NaN
60   NaN
61   NaN
62   NaN
63   NaN
64   NaN
65   NaN
66   NaN
Name: RF, dtype: float64

CSV数据集的格式如下：

RF,Nino,IOD,SOI,NAO,TNA,TSA,MEI
103.77,-1.04,0.20,2.70,-1.02,0.18,-0.92,-1.26
83.99,0.71,0.16,-1.70,1.32,-0.07,0.00,0.48
86.97,-0.55,0.21,-1.30,-0.43,0.55,-0.14,-0.12
152.58,0.15,0.11,-1.00,-0.47,0.17,-0.41,0.32
230.83,-0.79,0.18,0.60,0.69,-0.30,-0.23,-1.11
223.45,-1.52,-0.06,-0.50,0.17,0.30,-0.57,-1.88
118.26,-0.58,0.08,1.50,0.10,0.05,-0.49,-1.02
93.58,1.18,-0.02,-0.60,0.12,0.17,-0.16,1.25
..........................................
132.30,2.56,0.49,0.10,2.24,0.42,0.70,2.11
110.00,-0.51,-0.07,0.40,0.48,0.52,0.67,-0.12

共有67行：

---

请帮帮我

我想你可以用

系列

：

s = pd.Series(finalpred1, name='RF')

numpy数组

：

s = np.array(finalpred1)

由于索引值不同且不匹配，因此输出为

NaN

s

但更好的方法是只过滤

RF

列并跳过第一行

50

行：

s = pd.read_csv('poly2_decpred_juneRF.csv', 
                header=0, 
                nrows=17, 
                skiprows=range(1, 50), 
                usecols=['RF'])

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你知道你正在使用的标签吗？