For example, Recommend:python - Pandas: Read CSV: ValueError: could not convert string to float. 2. Valueerror: could not convert string to float pandas read_csv. To convert this to a floating-point number, i.e., float object, we will pass the string to the float() function. Yet there are lines in my frame which have a string "p-" … For that you can use the concept of categorical variable. Suppose we have a string ‘181.23’ as a Str object. So, I have a dataframe with more that 10^6 lines in it and I am just doing a simple conversion of lat (degrees min) to lat (degrees only). ... First load the csv or text file using pandas.It’s pretty simple. ValueError: could not convert string to float: id Somewhere in your text file, a line has the word id in it, which can’t really be converted to a number. The text was updated successfully, but these errors were encountered: 1 df ['Column'] = df ['Column']. ValueError: could not convert string to float: 'stop talking to other peoples girlfriends' It is fairly obvious that the above string cannot be converted to a float value. 0.42353321,45.12412141 When writing the CSV file, most numbers were below thousand and were correctly Pandas: Read CSV: ValueError: could not convert string to float. ValueError: Exception in remote process could not convert string to float: '94103-2585' An easy workaround for me was to include a dtype arg (dtype={"Zip Code" : "object"}. Also if I convert pandas to values it does not work either! Now the problem is, when I'm selecting those date features to train my model, it gives me an error: Could not convert string to float: 'Thu Apr 16 23:58:58 2015' Viewed 7k times 2. Using asType(float) method. Ask Question Asked 4 years, 3 months ago. Based on the input string, there are various possible outcomes of this function. ValueError: could not convert string to float: RandomCoder: 3: 908: Jul-27-2020, 07:38 AM Last Post: ndc85430 : Why int() cannot pass a string representation of a float into int? I am trying to perform a comparison between 5 algorithms against the KDD Cup 99 dataset and the NSL-KDD datasets using Python and I am having an issue when trying to build and evaluate the models against the KDDCup99 dataset and the NSL-KDD dataset. Then you are able to transfer by OneHotEncoder as you wish. Put all source into a directory named src; Create another directory at same node named backup. This method is useful if you need to perform a mathematical operation on a value. I appreciate your help in advance. “ValueError: could not convert string to float” may happen during transform. Dont have anything with errors(i think) so i dont know how to solve this. y is just a list of integers that are 1 or 0. This is a “non-breaking Latin1 ( ISO 8859-1) space”. Just remove your string column and pass that column in dummy variable function. ValueError: could not convert string to float in... ValueError: could not convert string to float in Machine learning. ValueError: could not convert string to float: '$23,000.00' df ... on this column would produce an error, but the pd.to_numeric() function built in to pandas will convert the numeric values to numbers and any other values to the “not a number” or ... You can apply dtype and converters in the pd.read_csv() function. As mentioned above you have to convert your string data to float. The problem was a thousand separator. You have to convert time date from string to pandas timestamp. Here is the syntax: 1. $ pd.get_dummies(string column) The two arrays are equal. Trouble converting string to float in python, As you guessed, ValueError: could not convert string to float: '13.75%' indicates that the % character blocks the convertion. In this programme i'm trying to solve a mathematical ratio problem, then calculate the squareroot, however, whenever i try to give it input like this: 2.5, it throws out the following error: Error:ValueError: could not convert string to float: . However the numpy one is dtype "