如何修复“ValueError：无法将字符串转换为浮点数”

Question

I am going to train an SVM based on x dataframe and y series I have. X dataframe is shown below:

x:

Timestamp      Location of sensors       Pressure or Flow values

0.00000         138.22, 1549.64            28.92

0.08333         138.22, 1549.64            28.94

0.16667         138.22, 1549.64            28.96

In X dataframe, location of sensors are represented as the form of node coordinate. Y series is shown below:

y:

0
0
0

But when I fit svm to the training set, it returned an ValueError: could not convert string to float: '361.51,1100.77' and (361.51, 1100.77) are coordinates for a node. Could you please give me some ideas to fix this problem? Appreciate a lot if any advices.

Answer 1

I'm assuming that you are trying to convert the entire string "361.51,1100.77" into a float, and you can see why that's a problem because Python sees two decimal points and a comma inbetween, so it has no idea what to do. Assuming you want the numbers to be separate, you could do something like this:

myStr = "361.51,1100.77"
x = float(myStr[0:myStr.index(",")])
y = float(myStr[myStr.index(",")+1:])
print(x)
print(y)

Which would get you an output of

361.51
1100.77

Assigning x to be myStr[0:myStr.index(",")] takes a substring of the original string from 1 to the first occurrence of a comma, getting you the first number.

Assigning y to be myStr[myStr.index(",")+1:] takes a substring of the original string starting after the first comma and to the end of the string, getting you the second number.

Both can easily be converted to floats from here using the float(myStr) method, getting you two separate floats.

Here is a helpful link to understand string slicing: https://www.geeksforgeeks.org/string-slicing-in-python/

Answer 2

'361.51,1100.77' are actually two numbers right? A latitude (361.51) and a longitude (1100.77). You would first need to split it into two strings. Here is one way to do it:

data = pd.DataFrame(data=[[0, "138.22,1549.64", 28.92]], columns=["Timestamp", "coordinate", "flow"])

data["latitude"] = data["coordinate"].apply(lambda x: float(x.split(",")[0]))
data["longitude"] = data["coordinate"].apply(lambda x: float(x.split(",")[1]))

This will give you two new columns in your dataframe each with a float of the values in the string.