While normalizing the data in python, getting this error:Error evaluating factor: TypeError: list indices must be integers or slices, not str

Question

My data:

absent_data.head()

My data

Before it was running smooth, this is my code:

cnames = ['Transportation expense', 'Distance from Residence to Work',
   'Service time', 'Age', 'Work load Average/day ', 'Hit target',
   'Son', 'Pet', 'Weight','Body mass index',
   'Absenteeism time in hours']

#Nomalization
for i in cnames:
    print(i)
    absent_data[i] = (absent_data[i] - min(absent_data[i]))/(max(absent_data[i]) - min(absent_data[i]))

Now getting this error:

TypeError Traceback (most recent call last) in () 2 for i in cnames: 3 print(i) ----> 4 absent_data[i] = (absent_data[i] - min(absent_data[i]))/(max(absent_data[i]) - min(absent_data[i]))

TypeError: 'numpy.float64' object is not callable

It was float before too.

and what do you expect to happen when doing absent_data['Transportation expense'] for example? Because that is what you are doing.. — Ma0
– Ma0, Commented Mar 1, 2019 at 7:40
for i in cnames change it to for i in range(len(cnames)): — Rahil Hastu
– Rahil Hastu, Commented Mar 1, 2019 at 7:41

Yuya Takashina · Accepted Answer · 2019-03-01 08:26:44Z

1

I guess you are assigning a float value to min or max, and min or max function is overridden. Restart your notebook & remove the overriding part, then you would get the expected result.

Otherwise, just use sklearn.preprocessing.MinMaxScaler instead of implementing it by yourself.

Normalize columns of pandas data frame

edited Mar 1, 2019 at 8:26

answered Mar 1, 2019 at 7:58

Yuya Takashina

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3 Comments

HiMesh NaGar Over a year ago

The same code is working fine for another data set and there too I have float values.

Yuya Takashina Over a year ago

Is there any line like min = ... or max = ... in your notebook? This will override the function and cause is not callable error.

HiMesh NaGar Over a year ago

There was min=.. max=... in my notebook, that was after normalization code. That is the reason it worked well 1st time and after running the whole code again it was giving an error. Yes, I will do it using the sklearn library. Thank you so much.

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