python-scikit-learnConvert bunch object to dataframe

from sklearn import datasets
import pandas as pd

data = datasets.load_iris()

df = pd.DataFrame(data['data'], columns=data['feature_names'])
df['target'] = data['target']ctrl + cgithub

`from sklearn import` import module from scikit-learn	`import pandas as pd` load Pandas module
`load_iris()` loads Iris dataset	`.DataFrame(` create new dataframe from given data
`columns` list of columns to use for dataframe	`data['feature_names']` list of loaded data features (we're using them as columns in dataframe)
`data['target']` target variable values

Usage example

from sklearn import datasets
import pandas as pd

data = datasets.load_iris()

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

print(df.head())

output

   sepal length (cm)  sepal width (cm)  ...  petal width (cm)  target
0                5.1               3.5  ...               0.2       0
1                4.9               3.0  ...               0.2       0
2                4.7               3.2  ...               0.2       0
3                4.6               3.1  ...               0.2       0
4                5.0               3.6  ...               0.2       0

[5 rows x 5 columns]

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