Please can someone tell me how i could get the most frequent/modal array out of an nested array?
So for example for:
a = np.array([[A, 8, 3, 0],[B, 8, 4, 0],[A, 8, 3, 0]])
The result should be [A, 8, 3, 0] with count 2.
I did my research on that problem, but only found solutions which compare one value of one dimension and not the whole arrays.
And is it possible to get the 2nd and 3rd most frequent array too?
Thank you in advance,
Greetings :)
Using pandas
import pandas as pd
a = np.array([['A', 8, 3, 0],['B', 8, 4, 0],['A', 8, 3, 0]])
df=pd.DataFrame(a)
df=df.reset_index().groupby([0,1,2,3]).count().sort_values('index',ascending=False).reset_index()
np.array(df.iloc[0,0:4])
If you print you can find all the frequencies. HTH
If you don't care about the order of the lists, then you can use set comparisons to find the most common element just as you would do if you had a list of integers.
L = [['A', 8, 3, 0],['B', 8, 4, 0],['A', 8, 3, 0]]
counter = 0
set = L[0]
for i in L:
amount_times = L.count(i)
if amount_times > counter:
counter = amount_times
set = i
print (set)
print (counter)`
collections.Counterand convert your nested array to a nested tuple beforehand.