[英]Reading multiple CSV files with headers in python with numpy?
Currently I am using this code to read one complete csv file to my code:目前我正在使用此代码将一个完整的 csv 文件读取到我的代码中:
data = np.loadtxt('csv_Complete.csv', delimiter=',', skiprows=1)
However, Now I have multiple csv files that are in this format.但是,现在我有多个这种格式的 csv 文件。
Log1.csv日志1.csv
x1,x2,x3,x4....
1.5,3,5,7,8
2,5,1.2,5,2
1,3,3,5.5,6
log2.csv日志2.csv
x1,x2,x3,x4....
1,3.3,5,7,8
2,5.1,1,5.5,2
1,3,3,5,6
This is the method I am thinking of doing but it is not working.这是我正在考虑做的方法,但它不起作用。 Getting a ValueError: could not convert string to float:
获取 ValueError:无法将字符串转换为浮点数:
log1 = np.loadtxt('log1.csv', delimiter=',', skiprows=1)
log2 = np.loadtxt('log2.csv', delimiter=',', skiprows=1)
log3 = np.loadtxt('log3.csv', delimiter=',', skiprows=1)
data = np.append([log1, log2, log3])
The error I am getting is:我得到的错误是:
File "<ipython-input-6-6155c8de61ad>", line 1, in <module>
runfile('C:/Users/Mmyname/.spyder2-py3/setdataexp.py', wdir='C:/Users/myname/.spyder2-py3')
File "C:\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 714, in runfile
execfile(filename, namespace)
File "C:\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 89, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/Users/myname/.spyder2-py3/setdataexp.py", line 5, in <module>
log1 = np.loadtxt('log40a.csv', delimiter=',', skiprows=1)
File "C:\Anaconda3\lib\site-packages\numpy\lib\npyio.py", line 930, in loadtxt
items = [conv(val) for (conv, val) in zip(converters, vals)]
File "C:\Anaconda3\lib\site-packages\numpy\lib\npyio.py", line 930, in <listcomp>
items = [conv(val) for (conv, val) in zip(converters, vals)]
File "C:\Anaconda3\lib\site-packages\numpy\lib\npyio.py", line 659, in floatconv
return float(x)
ValueError: could not convert string to float:
It must be a missing value
in file log40a.csv
.它必须是文件
log40a.csv
的missing value
。
I have the same error for file like:我对文件有同样的错误,如:
x1,x2,x3,x4....
1,3.3,5,7,8
2,5.1,,5.5,2
1,3,3,5,6
Base on documentation if you have missing values you should use genfromtxt function .根据文档,如果您有缺失值,您应该使用genfromtxt 函数。
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