How do I convert data from a Scikit-learn Bunch object to a Pandas DataFrame?

Question

I have used the following code to convert the sk learn breast cancer data set to data frame : I am not getting the output ? I am very new in python and not able to figure out what is wrong.

def answer_one(): 

    import numpy as np
    import pandas as pd
    from sklearn.datasets import load_breast_cancer 
    cancer = load_breast_cancer()     
    data = numpy.c_[cancer.data, cancer.target]
    columns = numpy.append(cancer.feature_names, ["target"])
    return pandas.DataFrame(data, columns=columns)

answer_one()

score 8 · Answer 1 · answered Dec 09 '19 at 18:13

Use pandas

There was a great answer here: How to convert a Scikit-learn dataset to a Pandas dataset?

The keys in bunch object give you an idea about which data you want to make columns for.

df = pd.DataFrame(cancer.data, columns=cancer.feature_names)
df['target'] = pd.Series(cancer.target)

score 7 · Answer 2 · answered May 25 '20 at 13:55

7

As of scikit-learn 0.23 you can do the following to get a DataFrame and save some keystrokes:

df = load_breast_cancer(as_frame=True)
df.frame

answered May 25 '20 at 13:55

jeffhale

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Not working for me for some reason in Google Colab. Colab has 0.22, but I upgraded to 0.24 using pip (and the __version__ shows the updated version), still using as_frame=True) still returns a bunch :-/ – Levon Feb 17 '21 at 00:06
Question: How did you know to use the attribute `.frame`? I'm new to Python and sklearn and trying to figure out how you knew to use `.frame`, as I don't see it mentioned in the help docs. – Desmond Sep 25 '22 at 12:28
@Desmond, see example here: https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html "dataBunch Dictionary-like object, with the following attributes. data{ndarray, dataframe} of shape (150, 4) The data matrix. If as_frame=True, data will be a pandas DataFrame. ... frame: DataFrame of shape (150, 5) Only present when as_frame=True. DataFrame with data and target. – jeffhale Sep 26 '22 at 11:58

score 6 · Answer 3 · answered Feb 13 '18 at 15:15

6

The following code works

def answer_one(): 
    import numpy as np
    import pandas as pd
    from sklearn.datasets import load_breast_cancer 
    cancer = load_breast_cancer()     
    data = np.c_[cancer.data, cancer.target]
    columns = np.append(cancer.feature_names, ["target"])
    return pd.DataFrame(data, columns=columns)

answer_one()

The reason why your code doesn't work before was you try to call numpy and pandas package again after defining it as np and pd respectively.

However, i suggest that the package loading and redefinition is done at the beginning of the script, outside a function definition.

answered Feb 13 '18 at 15:15

Michael L. Tanny

139
4

def answer_one(): data = numpy.c_[cancer.data, cancer.target] columns = numpy.append(cancer.feature_names, ["target"]) return pandas.DataFrame(data, columns=columns) answer_one() – solly bennet Feb 13 '18 at 17:22
I tried without defining them. but does not get an output. Anything wrong with the return statement ? – solly bennet Feb 13 '18 at 17:23

score 3 · Answer 4 · edited Apr 18 '20 at 20:07

3

dataframe = pd.DataFrame(data=cancer.data, columns=cancer.feature_names)
dataframe['target'] = cancer.target
return dataframe

edited Apr 18 '20 at 20:07

4b0

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answered Apr 18 '20 at 20:06

Marckhz

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Welcome to Stack Overflow! Code-only answers are not particularly helpful. Please include a brief description of how this code solves the problem. – 4b0 Apr 18 '20 at 20:07

How do I convert data from a Scikit-learn Bunch object to a Pandas DataFrame?

4 Answers4