Returning a series with length and index

[Max Russell]

I am working with the scikit learn Wisconsin breast cancer dataset.

I've created a DataFrame with last columns like so:

      worst concave points  worst symmetry  worst fractal dimension  target  
 0                 0.26540          0.4601                  0.11890     0.0  
 1                 0.18600          0.2750                  0.08902     0.0  
 2                 0.24300          0.3613                  0.08758     0.0  

I'm trying to create a pd.Series based on target where it can be 0 or 1 and assign that to an index of 'malignant', 'benign'

I've tried the following:

output = df.Series([0,1], index= ['Malginant', 'Benign'])

with output being:

Enter code here...no    0

yes       1
dtype: int64

and also tried a mapping:

    status = {0:'Malignant', 1:'Benign'}

    cancerdf['target'] = pd.to_numeric(cancerdf['target'], errors='coerce').fillna(2).astype(int).map(status)

where cancerdf is my whole dataframe with the target column

however, this throws a type error:

TypeError: tuple indices must be integers or slices, not str

I'm trying to understand how to get this kind of mapping from the column, in order to move to further processing.

thanks very much.

[Joris Van den Bossche]

It's not fully clear what the end result is what you want to obtain. Can you provide a reproducible example with the desired output?

Joris

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[Peter Leimbigler]

If you intend to replace 0 with 'Malignant' and 1 with 'Benign':

df['target'].replace({0: 'Malignant', 1: 'Benign'}, inplace=True)

Complete example:

import pandas as pd
import numpy as np
from sklearn.datasets import load_breast_cancer
data = load_breast_cancer()
df = pd.DataFrame(data=np.c_[data['data'], data['target']],
                  columns=list(data['feature_names']) + ['target'])
df['target'].replace({0: 'Malignant', 1: 'Benign'}, inplace=True)
df.head()

Best,

Peter