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

[islrnd]

AttributeError                            Traceback (most recent call last)
<ipython-input-32-8d38637b6cc6> in <module>
      6 
      7 oversampler=SMOTE(random_state=42)
----> 8 smote_train, smote_target = oversampler.fit_resample(X,y)
      9 
     10 print("Before OverSampling, counts of label '0', '1':", smote_target['label'].value_counts())

~\Anaconda3\lib\site-packages\imblearn\base.py in fit_resample(self, X, y)
     73         """
     74         check_classification_targets(y)
---> 75         X, y, binarize_y = self._check_X_y(X, y)
     76 
     77         self.sampling_strategy_ = check_sampling_strategy(

~\Anaconda3\lib\site-packages\imblearn\base.py in _check_X_y(self, X, y, accept_sparse)
    148         if hasattr(y, "loc"):
    149             # store information to build a series
--> 150             self._y_name = y.name
    151             self._y_dtype = y.dtype
    152         else:

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __getattr__(self, name)
   5065             if self._info_axis._can_hold_identifiers_and_holds_name(name):
   5066                 return self[name]
-> 5067             return object.__getattribute__(self, name)
   5068 
   5069     def __setattr__(self, name, value):

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

[chkoar]

@glemaitre I think that is related with the sanity check that we were discussing about, no? The user passes something that has .loc but it is not a Series as we expect. It is a DataFrame.

[glemaitre]

Yes but this is not pythonic to type check. We should probably look at attributes that are "couacing" better for Series.

[glemaitre]

@islrnd you should pass a numpy array or a pandas series, not a dataframe.

[00krishna]

This is a confusing issue. If I pass in a DataFrame then I get the error about no attribute name. If I pass in a Series I get a different error about ValueError: Found array with 0 feature(s) (shape=(7788867, 0)) while a minimum of 1 is required. So no matter how I am putting the data in, it generates a critical error.

[chkoar]

@00krishna post a sample code to reproduce you error.

[00krishna]

@chkoar Sorry, I realized I have all categorical features and that is causing the problem.

[parth-radonc]

@00krishna I am facing the similar issue.. Can you help me with it?

[chkoar]

@parth-mango You probably pass a data frame in y. You should pass a Series object. If you want provide a minimal reproducible code.

[flowersw]

I had the same issue, and was accidentally passing in a DataFrame for y instead of Series

[chkoar]

@flowersw #673 or a post PR hopefully will solve this problem.

[serjko]

Hi there,

I'm facing a similar issue that wasn't resolved after converting the initial DataFrame to Series. Please take a look at my question on SO https://datascience.stackexchange.com/questions/67141/passing-data-to-smote-after-applying-train-test-split

[chkoar]

@serjko please post a minimal reproducible example and your package versions.

[serjko]

Hi @chkoar, Thanks for jumping in so quickly. This is a false alarm. The root cause was my dataset and not SMOTE. I made it work after cleaning up the data and passing Series as 2nd variable for fit_sample. Apologies for bothering you and thanks again for the answer!

[ertanuj96]

@chkoar , Hey I am facing similar issue when I am using regex a string on entire dataframe .
#Note :: xlsx - you can ask me in private ,cannot expose xlsx here.
Code snippet here -
'import os
import time
import sys
import subprocess
import re
import pandas as pd
from openpyxl import load_workbook
import pyperclip

from tkinter import Tk
from tkinter.filedialog import askopenfilename

def get_lookup_excel_path():
parent_dir = '/root/Desktop/lookup.xlsx'
return parent_dir

def upload_spreadsheet(path, active_sheet_only = True):
'''Returns pandas dataframe. Returns empty dataframe if fails'''
#check if file exists
if not os.path.isfile(path):
return pd.DataFrame()

#check file type
file_type = os.path.splitext(path)[1]

if file_type == '.csv':
    df = pd.read_csv(path)
elif file_type in ['.xlsx','.xlsm','.xltx','.xltm']:
    wb = load_workbook(path)

    #convert sheets to pandas dataframe
    if active_sheet_only:
        df = pd.DataFrame(wb.active.values)
    else:
        #combine all sheets into one dataframe
        frames = [pd.DataFrame(sheet.values) for sheet in wb.worksheets]
        df = pd.concat(frames)
    wb.close()
else:
    return pd.Dataframe()

return df

def combine_dataframe(dataframe):
'''Converts pandas dataframe into one list'''
return [cell for cell in [dataframe[i] for i in dataframe] ]

def get_springer_books_excel():
parent_dir = '/root/Desktop/springnature.xlsx'
return parent_dir

def main():
file_path = get_lookup_excel_path()
if file_path == '': return
df = upload_spreadsheet(file_path, active_sheet_only=True)
search_values = ['Engineering', 'Computer']
df[df.name.str.contains('|'.join(search_values))]

if name == 'main':
main()

[chkoar]

Hey I am facing similar issue when I am using regex a string on entire dataframe .

@ertanuj96 sorry, I do not get it. Is this related to imbalanced-learn?

[ramiazmi]

I had experienced this before. I resolved it by passing a dataframe into X and a Series into y.

[chkoar]

@ramiazmi #681 has solved this issue. So 0.6.2 (which is currently not released) will solve such problems.

[glemaitre]

0.6.2 is out on PyPI and will be shortly available on conda-forge. Locking this issue