pd.cut in pandas
>>> pd.qcut(range(5), 4, labels=False)
array([0, 0, 1, 2, 3])pd.cut in pandas
>>> pd.qcut(range(5), 4, labels=False)
array([0, 0, 1, 2, 3])pandas bins dummy
>>> dout
age ageD_[5, 30] ageD_(30, 70] (-inf, 5] (-inf, 30] (-inf, 70] (5, +inf) (30, +inf) (70, +inf)
0 5 1 0 1 1 1 0 0 0
1 23 1 0 0 1 1 1 0 0
2 43 0 1 0 0 1 1 1 0
3 70 0 1 0 0 1 1 1 0
4 30 1 0 0 1 1 1 0 0pandas bins dummy
df['ageD'], bins = pd.qcut(df.iloc[:, 0], 2, retbins=True)
left = (df["age"].values <= bins[:,None]).T.astype(int)
dl = pd.DataFrame(left, columns=["(-inf, {}]".format(b) for b in bins])
dr = pd.DataFrame(1-left, columns=["({}, +inf)".format(b) for b in bins])
dout = pd.concat([pd.get_dummies(df), dl, dr], axis=1)Copyright © 2021 Codeinu
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