如何为 X 的每个值获得 Y 的最小值？

Question

I have two lists X and Y.

X = [0.034, 0.026, 0.028, ...]
Y = [0.0099, 0.0065, 0.0061, ...]

I want to get min value of Y for each value of X. I tried with groupby approach. I need to get points on the border. which are marked in black in the figure below. I have X and Y coordinate for all the points.

Answer 1

You can use groupby with min() :

import pandas as pd

# two y values for 0.034 and 0.026

X = [0.034, 0.026, 0.028, 0.034, 0.026]
Y = [0.0099, 0.0065, 0.0061, 0.1, 0.000001]

df = pd.DataFrame({'x': X, 'y': Y})

       x         y
0  0.034  0.009900
1  0.026  0.006500
2  0.028  0.006100
3  0.034  0.100000
4  0.026  0.000001

df.groupby('x')['y'].min()

x
0.026    0.000001
0.028    0.006100
0.034    0.009900
Name: y, dtype: float64

As you deal with floating point numbers, you might want to do a groupby with rounded numbers (eg 5 digits):

df.groupby(df['x'].round(5))['y'].min()

That will give 8018 xy pairs using the dataset you provided.

Answer 2

This is one way in Python to get min values .. See the as an example

list1, list2 = [123, 223, 154, 235], [456, 700, 200]
print "min value element : ", min(list1)
print "min value element : ", min(list2)

When we run above program, it produces following result −

min value element :  123
min value element :  200

Pandas solution as stated in above answer:

df.groupby('x')['y'].min()