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, Mar 01 '19 at 07:40
`for i in cnames` change it to `for i in range(len(cnames)):` — Rahil Hastu, Mar 01 '19 at 07:41
Can you add an explanation of what the loop should compute? Also, please update the title of your question according to the problem it describes. — Heiko Becker, Mar 01 '19 at 07:45
@Ev.Kounis I am trying to normalize the data. In the loop, there is an equation to do it. — HiMesh NaGar, Mar 01 '19 at 07:49
@RahilHastu I can't give a range as I only want those columns to include which are in the cnames. I do not want a range. type(absent_data) is pandas.core.frame.DataFrame — HiMesh NaGar, Mar 01 '19 at 07:51

Yuya Takashina · Accepted Answer · 2019-03-01T08:26:44.960

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 01 '19 at 08:26

answered Mar 01 '19 at 07:58

Yuya Takashina

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The same code is working fine for another data set and there too I have float values. – HiMesh NaGar Mar 01 '19 at 08:14
1

Is there any line like `min = ...` or `max = ...` in your notebook? This will override the function and cause `is not callable` error. – Yuya Takashina Mar 01 '19 at 08:20
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. – HiMesh NaGar Mar 01 '19 at 08:44

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

Now getting this error:

1 Answers1