我尝试从包含我的数据的P-I curve.txt文件中导入浮点数。但是，将其转换为float时出现错误。我用下面的代码。
with open('C:/Users/Kevin/Documents/4e Jaar/fotonica/Metingen/P-I curve.txt') as csvfile:
data= csv.reader(csvfile, delimiter = '\t')
current=[]
P_15=[]
P_20=[]
P_25=[]
P_30=[]
P_35=[]
P_40=[]
P_45=[]
P_50=[]
for row in data:
current.append(float(row[0].replace(',','.')))
P_15.append(float(row[2].replace(',','.')))
P_20.append(float(row[4].replace(',','.')))
P_25.append(float(row[6].replace(',','.')))
P_30.append(float(row[8].replace(',','.')))
P_35.append(float(row[10].replace(',','.')))
P_40.append(float(row[12].replace(',','.')))
P_45.append(float(row[14].replace(',','.')))
P_50.append(float(row[16].replace(',','.')))
使用此代码，我得到以下错误，我知道第2行是一个字符串，但是如果是这样，为什么对于第1行却没有发生此错误？是否有其他数据可以在不使用csv import的情况下导入浮点数？我已经将数据从excel复制并粘贴到.txt文件中。
返回错误：
File "C:/Users/Kevin/Documents/Python Scripts/P-I curves.py", line 29, in <module>
P_15.append(float(row[2].replace(',','.')))
ValueError: could not convert string to float:
我尝试了另一个以下代码：
import pandas as pd
df=pd.read_csv('C:/Users/Kevin/Documents/4e Jaar/fotonica/Metingen/P-I curve.txt', decimal=',', sep='\t',header=0,names=['current','15','20','25','30','35','40','45','50'] )
#curre=df['current']
print(current)
txt文件具有标题，如下所示：
1.8 1.9 0.4 1.9 0.4 1.9 0.4 1.9 0.4
3.8 1.9 1.3 1.9 1.3 1.9 1.3 1.9 1.2
5.8 2.0 2.5 2.0 2.4 2.0 2.3 2.0 2.2
7.8 2.0 3.7 2.0 3.6 2.0 3.5 2.0 3.4
9.8 2.1 5.2 2.0 5.1 2.0 4.9 2.0 4.7
11.8 2.1 6.9 2.1 6.7 2.1 6.4 2.1 6.1
13.8 2.1 9.0 2.0 8.6 2.1 8.2 2.1 7.8
15.8 2.1 11.5 2.1 10.8 2.1 10.2 2.1 9.7
17.8 2.2 14.7 2.2 13.7 2.2 12.7 2.2 11.8
19.8 2.2 19.5 2.2 17.5 2.2 15.9 2.2 14.5
21.8 2.2 28.9 2.2 23.6 2.2 20.3 2.2 17.9
23.8 2.3 125.8 2.2 38.4 2.2 27.8 2.2 22.8
25.8 2.3 1669.0 2.3 634.0 2.3 51.7 2.3 31.4
27.8 2.3 3142.0 2.3 2154.0 2.3 982.0 2.3 62.2
29.8 2.3 4560.0 2.3 3594.0 2.3 2460.0 2.3 1075.0
31.8 2.3 5950.0 2.3 5010.0 2.3 3872.0 2.3 2540.0
33.8 2.4 7320.0 2.4 6360.0 2.4 5230.0 2.3 3880.0
35.8 2.4 8670.0 2.4 7700.0 2.4 6550.0 2.4 5210.0
37.8 NaN NaN NaN NaN 2.4 7850.0 2.4 6480.0
39.8 NaN NaN NaN NaN NaN NaN NaN NaN
41.8 NaN NaN NaN NaN NaN NaN NaN NaN
Name: current, dtype: float64
python似乎正在返回所有内容，而不仅仅是返回我要打印的当前行头的第一行。我只想采取这一行，这样我就可以将其保存为数组。但是，我该如何从数据中具体绘制带有标头电流的线呢？
我不确定为什么它会返回所有内容，但我认为编码存在问题，因为我从excel复制并粘贴了数据。
请查看从excel复制时.txt的外观图像。
我尝试了另一个短代码（我也手动删除了.txt文件的标题！），请参见以下说明：
data=np.loadtxt('C:/Users/Kevin/Documents/4e Jaar/fotonica/Metingen/ttest.txt',delimiter='\t')
data=float(data.replace(',','.'))
print(data[0])
与此代码，我得到跟随错误。
ValueError: could not convert string to float: b'1,8'
我发现这很奇怪。浮动和替换不足以解决此问题
最佳答案
我认为您需要省略header=0：
df=pd.read_csv('C:/Users/Kevin/Documents/4e Jaar/fotonica/Metingen/P-I curve.txt',
decimal=',',
sep='\t',
names=['current','15','20','25','30','35','40','45','50'])
编辑：
df=pd.read_csv('ttest.txt',
decimal=',',
sep='\t',
names=['current','15','20','25','30','35','40','45','50'])
print (df)
current 15 20 25 30 35 40 45 50
0 1.8 0.4 0.4 0.4 0.4 0.4 0.4 0.3 0.3
1 3.8 1.3 1.3 1.3 1.2 1.2 1.1 1.1 1.1
2 5.8 2.5 2.4 2.3 2.2 2.2 2.1 2.0 1.9
3 7.8 3.7 3.6 3.5 3.4 3.3 3.1 3.0 2.9
4 9.8 5.2 5.1 4.9 4.7 4.5 4.3 4.1 4.0
5 11.8 6.9 6.7 6.4 6.1 5.9 5.6 5.3 5.1
6 13.8 9.0 8.6 8.2 7.8 7.4 7.0 6.6 6.3
7 15.8 11.5 10.8 10.2 9.7 9.1 8.6 8.0 7.6
8 17.8 14.7 13.7 12.7 11.8 11.0 10.3 9.6 9.0
9 19.8 19.5 17.5 15.9 14.5 13.3 12.2 11.3 10.5
10 21.8 28.9 23.6 20.3 17.9 16.0 14.5 13.2 12.2
11 23.8 125.8 38.4 27.8 22.8 19.6 17.2 15.4 14.1
12 25.8 1669.0 634.0 51.7 31.4 24.5 20.6 17.9 16.2
13 27.8 3142.0 2154.0 982.0 62.2 33.1 25.3 21.0 18.5
14 29.8 4560.0 3594.0 2460.0 1075.0 60.0 32.6 25.0 21.3
15 31.8 5950.0 5010.0 3872.0 2540.0 903.0 49.9 30.8 24.6
16 33.8 7320.0 6360.0 5230.0 3880.0 2294.0 387.0 40.9 28.8
17 35.8 8670.0 7700.0 6550.0 5210.0 3621.0 1733.0 71.0 34.8
18 37.8 NaN NaN 7850.0 6480.0 4880.0 3026.0 751.0 44.6
19 39.8 NaN NaN NaN NaN 6100.0 4240.0 1998.0 70.2
20 41.8 NaN NaN NaN NaN NaN NaN 3161.0 650.0
#list from column 15 with all values include NaNs
L1 = df['15'].tolist()
print (L1)
[0.4, 1.3, 2.5, 3.7, 5.2, 6.9, 9.0, 11.5, 14.7, 19.5, 28.9, 125.8, 1669.0,
3142.0, 4560.0, 5950.0, 7320.0, 8670.0, nan, nan, nan]
#list from column 15 with removing NaNs
L2 = df['15'].dropna().tolist()
print (L2)
[0.4, 1.3, 2.5, 3.7, 5.2, 6.9, 9.0, 11.5, 14.7, 19.5, 28.9, 125.8, 1669.0,
3142.0, 4560.0, 5950.0, 7320.0, 8670.0]
#convert all NaNs in all columns to 0
df = df.fillna(0)
print (df)
current 15 20 25 30 35 40 45 50
0 1.8 0.4 0.4 0.4 0.4 0.4 0.4 0.3 0.3
1 3.8 1.3 1.3 1.3 1.2 1.2 1.1 1.1 1.1
2 5.8 2.5 2.4 2.3 2.2 2.2 2.1 2.0 1.9
3 7.8 3.7 3.6 3.5 3.4 3.3 3.1 3.0 2.9
4 9.8 5.2 5.1 4.9 4.7 4.5 4.3 4.1 4.0
5 11.8 6.9 6.7 6.4 6.1 5.9 5.6 5.3 5.1
6 13.8 9.0 8.6 8.2 7.8 7.4 7.0 6.6 6.3
7 15.8 11.5 10.8 10.2 9.7 9.1 8.6 8.0 7.6
8 17.8 14.7 13.7 12.7 11.8 11.0 10.3 9.6 9.0
9 19.8 19.5 17.5 15.9 14.5 13.3 12.2 11.3 10.5
10 21.8 28.9 23.6 20.3 17.9 16.0 14.5 13.2 12.2
11 23.8 125.8 38.4 27.8 22.8 19.6 17.2 15.4 14.1
12 25.8 1669.0 634.0 51.7 31.4 24.5 20.6 17.9 16.2
13 27.8 3142.0 2154.0 982.0 62.2 33.1 25.3 21.0 18.5
14 29.8 4560.0 3594.0 2460.0 1075.0 60.0 32.6 25.0 21.3
15 31.8 5950.0 5010.0 3872.0 2540.0 903.0 49.9 30.8 24.6
16 33.8 7320.0 6360.0 5230.0 3880.0 2294.0 387.0 40.9 28.8
17 35.8 8670.0 7700.0 6550.0 5210.0 3621.0 1733.0 71.0 34.8
18 37.8 0.0 0.0 7850.0 6480.0 4880.0 3026.0 751.0 44.6
19 39.8 0.0 0.0 0.0 0.0 6100.0 4240.0 1998.0 70.2
20 41.8 0.0 0.0 0.0 0.0 0.0 0.0 3161.0 650.0
#list from column 15
L3 = df['15'].tolist()
print (L3)
[0.4, 1.3, 2.5, 3.7, 5.2, 6.9, 9.0, 11.5, 14.7, 19.5, 28.9, 125.8, 1669.0,
3142.0, 4560.0, 5950.0, 7320.0, 8670.0, 0.0, 0.0, 0.0]
关于python - python:从文本导入数据，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/48204730/