from numpy import *
list = array([["A", 25, 2], ["B", 25, 3], ["C", 10, 1], ["D", 50, 25]])
How do I sort this array by descending size of 2nd element divided by 3rd element. So in this case the correct arrangement would be:
["A", 25, 2], ["C", 10, 1], ["B", 25, 3], ["D", 50, 25]
import numpy as np
# Let's use a as the variable name so we don't override the list keyword
a = np.array([["A", 25, 2], ["B", 25, 3], ["C", 10, 1], ["D", 50, 25]])
# Need to convert values to int, because they are being casted as string
# in the original array (arrays only support one data type)
key_values = a[:,1].astype(int) / a[:,2].astype(int)
# Use argsort to get a sort index, then reverse the order to make it descending
index_array = np.argsort(key_values)[::-1] # -1 reverses the order
print(a[index_array])
Output:
[['A' '25' '2']
['C' '10' '1']
['B' '25' '3']
['D' '50' '25']]
Can you use pandas? If so,
import numpy as np
import pandas as pd
df = pd.DataFrame(np.array([["A", 25, 2], ["B", 25, 3], ["C", 10, 1], ["D", 50, 25]]))
df[1] = pd.to_numeric(df[1])
df[2] = pd.to_numeric(df[2])
df[3] = df[1] / df[2]
sorted_list = df.sort_values(by=3, ascending=False).values[:,:3]
print(sorted_list)
array([['A', 25, 2],
['C', 10, 1],
['B', 25, 3],
['D', 50, 25]], dtype=object)
Note that here I'm assuming (based on how I understood the question) that you want to sort based on the value of the 2nd column divided by the 3rd column. If that's the case, the output example has the first two elements flipped (since 25/2 > 10/1).
list(or "reserved words" in general) as variable namenumpy.array, all elements are of the same type, string in this case. Are you surenumpy.arrayis what you want/need in this case?