![]() ![]() ![]() atof( "3,14") # and the conversion of the number works 3. If the file size isn't giant, then just splitlines () everything, and for each line, do your 1:-1 and then float conversion. localeconv() # therefore the standard point is set as a decimal separator It's better to use the function splitlines () 0 1:-1 rather than rstrip (' '), in case the line has a carriage return delimiter ('\r '). A possible workaround if you know you have 5 columns is: np.loadtxt ( 'test. LC_NUMERIC) # but the LC_NUMERIC is not set numpy.loadtxt, ValueError: could not convert string to float 104,688 Solution 1 You need to strip off the trailing ' ' from the lines. getlocale() # locale is set to de_DE which has in principle a comma as a decimal separator data np.loadtxt('/filepath/wagepan.txt') I get the following error: ValueError: could not convert string to float: '13,1980,0,1,0,0,14,0,1.1975401639938354,1' Does anyone have any idea how to fix this I tried looking at other posts, but the issue was not similar. In most Linux systems for instance you can just do something along the lines of this answerĮDIT: as suggested by in the comments section, different systems can have different ways of representing newlines, so a more robust solution would be: lines = loadtxt ('pred.txt', delimiter '\t') 1 2 3 : import numpy as np import os data1 np. numpy. If you dont need to do any type of numerical analysis, you can import the data as strings. The other way to go is modifying the data file to remove the parentheses, which you can do in many ways depending on the platform you are working on. np.loadtxt ()ValueError: could not convert string to float python numpy tensorflow : : import numpy as np import os data1 np. If you want to perform numerical operations on your data, youre going to need to remove the Time Freq header, and convert your times to numbers. lines is a list of the values on line 1). txt file that is not really written there but is copied when its content is loaded somewhere. ValueError: COULD NOT Convert String To Float The usual reason is: To convert som. In this way you end up with lines which is a list of lists of values (i.e. Row str(row).replace('\\', '') deleting backslash Path 'C:\\Users\\Souro\\Downloads\\AXISBANK.csv' I think it is better to first import your text in an array or a string and then split it and save into the dataframe specifically when your data is not too large. Intelligent Recommendation Error Solution: Valueerror: Could Not Convert String to Float Problem Description It is an error that occurs when the data operation is performed after Python reads the MySQL data. ![]() Line = line.rstrip('\n') # this removes first and last parentheses from the line code snippet convert X into dataframe Xpd pd.DataFrame(dataX) replace all instances of URC with 0 Xreplace Xpd.replace(' ',0, regexTrue) convert it back to numpy array Xnp Xreplace.values set the object type as float. Examples > from io import StringIO StringIO behaves like a file object > c StringIO('0 1 2 3') > np.loadtxt(c) array ( 0., 1., 2., 3. ![]() I think np.loadtxt expects numbers so it does not know how to convert a value which starts with a '(', I think you have two choices here: lines = Though not the best solution, I found some success by converting it into pandas dataframe and working along. The strings produced by the Python float.hex method can be used as input for floats. ![]()
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