quantile()

quantile()

Location determined quartile two methods, method = POS. 1 (n-+. 1) P = 1+ POS Method 2 (. 1-n-) P

pandas method used is determined. Linear interpolation is used by default

In [213]:

df

 

 

Out[213]:

	key1	key2	data1	data2
0	a	one	-0.594168	0.530619
1	a	two	-1.337130	0.619927
2	b	one	-1.700586	0.464591
3	b	two	-0.399619	-0.211291
4	a	one	-0.277584	0.668908

In [217]:

  df. quantile(0.1)

 

Out[217]:

data1   -1.555204
data2    0.059062
Name: 0.1, dtype: float64

In [ ]:

 

# Default using linear interpolation

# Data1 column

# Pos = 1 + (5-1) * 0.1 = 1.4 I = 0.4, -1.700586 + (- 1.337130 - (- 1.700586)) * 0.4 = -1.555204

In [229]:

DF. Quantile ([ 0.05, 0.95]) # Note brackets

 

 

Out[229]:

	data1	data2
0.05	-1.627895	-0.076115
0.95	-0.301991	0.659112

In [260]:

 

def cap_outliers(ser,lower,higher):

    low,high=ser.quantile([lower,higher])

    ser[ser<low]=low

    ser[ser>high]=high

    return (ser)

cap_outliers(df['data1'],0.05,0.95)

 

Out[260]:

0   -0.594168
1   -1.337130
2   -1.523220
3   -0.399619
4   -0.337137
Name: data1, dtype: float64