How to replace values in an array based on table values?

Question

I have the following script and sample data:

import numpy as np
from tabulate import tabulate
 

a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])


table = [['cat','value'],[1,0.5],[2,0.5],[3,0.5],[4,0.5],[6,0.05],[7,0.025],[8,0.005],[9,0.123]]
print(tabulate(table))

Output:

cat  value
1    0.5
2    0.5
3    0.5
4    0.5
6    0.05
7    0.025
8    0.005
9    0.123

The array (a) contains the categories.

How can I replace the categories in the array with the data from the "value" column in the table?

For example, all 1 in the array will be replaced with 0.5, etc.

In this example, I created a table. But I also have a separate csv file containing the data from the table I created.

I will be applying this on a 1200 x 1200 array.

Answer 1

You can create a mapping dictionary and then apply this mapping to your list. For example:

mapping = dict(table[1:])

out = [[mapping.get(v, v) for v in l] for l in a]
print(out)

Prints:

[[0.5, 0.5, 0.5], [0.5, 5, 0.05], [0.025, 0.005, 0.123]]