delete outliers in pandas
cols = ['col_1', 'col_2'] # one or more
Q1 = df[cols].quantile(0.25)
Q3 = df[cols].quantile(0.75)
IQR = Q3 - Q1
df = df[~((df[cols] < (Q1 - 1.5 * IQR)) |(df[cols] > (Q3 + 1.5 * IQR))).any(axis=1)]delete outliers in pandas
cols = ['col_1', 'col_2'] # one or more
Q1 = df[cols].quantile(0.25)
Q3 = df[cols].quantile(0.75)
IQR = Q3 - Q1
df = df[~((df[cols] < (Q1 - 1.5 * IQR)) |(df[cols] > (Q3 + 1.5 * IQR))).any(axis=1)]outliers removal
#Removing outliers first then skewness
from scipy.stats import zscore
z=abs(zscore(df))
print(z.shape)
df=df[(z<3).all(axis=1)]
df.shapeCopyright © 2021 Codeinu
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