AttributeError: 'DataFrame' object has no attribute 'target_names'- scikit

Question

I am trying to build a logistic regression model. After reading the data set . I am getting

AttributeError                            Traceback (most recent call last)
<ipython-input-1-b1fbf288405a> in <module>()
     21 df.head(10)  #This should print 10 rows
     22 
---> 23 df.target_names
     24 df.feature_names
     25 

C:\Users\HP\Anaconda2\lib\site-packages\pandas\core\generic.pyc in __getattr__(self, name)
   3612             if name in self._info_axis:
   3613                 return self[name]
-> 3614             return object.__getattribute__(self, name)
   3615 
   3616     def __setattr__(self, name, value):

AttributeError: 'DataFrame' object has no attribute 'target_names'

This is what I have done

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from sklearn import preprocessing

# create header for dataset
header = ['age','bp','sg','al','su','rbc','pc','pcc',
    'ba','bgr','bu','sc','sod','pot','hemo','pcv',
    'wbcc','rbcc','htn','dm','cad','appet','pe','ane',
    'classification']
# read the dataset
df = pd.read_csv("C:\Users\HP\Documents\machine learning project\Chronic_Kidney_Disease\chronic_kidney_disease_full.arff",
        header=None,
        names=header
       )
# dataset has '?' in it, convert these into NaN
df = df.replace('?', np.nan)
# drop the NaN
df = df.dropna(axis=0, how="any")
df.head(10)  #This should print 10 rows

df.target_names
df.feature_names

Can any one tell me why I am getting this error

You don't have attributes called target_names or feature_names. If you share a few sample rows of the Data Set and explain what you mean by target_names and feature_names (Is this the header or values), it will be easier to answer the question you have. — user2510479
– user2510479, Commented Apr 22, 2018 at 15:00

Eric Hullander · Accepted Answer · 2018-04-22 22:10:58Z

3

You would have to define feature_names and target_names, as they are not native pandas attributes. If you wanted df.feature_names and df.target_names to return a select group of columns instead, you will need to create a multiindex and set df.columns equal to that. A multiindex allows you to create multiple-row-headers or indices. This is described here and can be applied to either rows or columns.

https://pandas.pydata.org/pandas-docs/stable/advanced.html

answered Apr 22, 2018 at 22:10

Eric Hullander

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