<jupyter_start><jupyter_text>AutoEDA: PandasGUI> Anaconda env: *eda3*<jupyter_code>!pip install -U scikit-learn
%matplotlib inline
import warnings
warnings.filterwarnings('ignore')
from sklearn.datasets import load_iris
import pandas as pd<jupyter_output><empty_output><jupyter_text>load data<jupyter_code># load dataset
dataset = load_iris()
dataset.keys()
# dataset to df
data = pd.DataFrame(dataset.data, columns = dataset.feature_names)
data['class'] = dataset.target
dclass = dict()
for i, ic in enumerate(dataset.target_names):
    dclass[i] = ic
data['class'] = data['class'].map(dclass)<jupyter_output><empty_output><jupyter_text>AutoEDA<jupyter_code>from pandasgui import show
#Deploy the GUI of the mpg dataset
gui = show(data)<jupyter_output>PandasGUI INFO — pandasgui.gui — Opening PandasGUI
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