To make averages from the data of a text file

awk '/^[0-9]+ +[0-9]+$/ { # pick only lines with two numbers
         arr[$1] += $2    # accumulate the numbers in indexed bins
         n[$1]++          # keep track of how may numbers are in each bin
     }
     END {                     # finally,
         for (e in arr)        # for each bin
             print arr[e]/n[e] # divide
     }' your_input_file

Here is a solution, assuming the data are contained in a string called 's'

from collections import defaultdict

s = '1 23' #....etc

def list_struct():
    return list((int(), int()))

data = defaultdict(list_struct) # format: {id: [occurrences, total]}

for line in s.split('\n'):
    if line[0:1].isdigit(): # i'm assuming that all the lines that start with a number are the 'right' lines
        n, value = line.split()
        data[int(n)][0] += 1
        data[int(n)][1] += int(value)

for elem in data:
    print(elem, data[elem][1] / data[elem][0])

Output with your data:

1 22.75
2 24.0
3 22.5
4 21.5
5 21.75
6 21.0
7 19.0
8 24.0
9 18.666666666666668
10 22.666666666666668
11 23.0
12 22.0
13 23.0
14 16.0

Edit:

To read from a file just change the for loop to:

with open('f.txt', 'r') as f:
    for line in f:
        if line[0:1].isdigit(): # i'm assuming that all the lines that start with a number are the 'right' lines
            n, value = line.split()
            data[int(n)][0] += 1
            data[int(n)][1] += int(value)

A gimmick with bash because the question originally had a bash tag.

#!/bin/bash

div ()  # Arguments: dividend and divisor
{
  if [ $2 -eq 0 ]; then echo division by 0; exit; fi
  local p=15                            # precision
  local c=${c:-0}                       # precision counter
  local d=.                             # decimal separator
  local r=$(($1/$2)); echo -n $r        # result of division
  local m=$(($r*$2))
  [ $c -eq 0 ] && [ $m -ne $1 ] && echo -n $d
  [ $1 -eq $m ] || [ $c -eq $p ] && echo && return
  local e=$(($1-$m))
  c=$(($c+1))
  div $(($e*10)) $2
}

while read -r num val; do
  if [[ $num =~ ^[0-9] ]]; then
    a[$num]=$((a[$num]+$val))
    ((v[$num]++))
  fi
done < file

for((i=1; i<=${#a[@]}; i++)); do
  div ${a[$i]} ${v[$i]}
done

I used div function from there.

Output:

22.75
24
22.5
21.5
21.75
21
19
24
18.666666666666666
22.666666666666666
23
22
23
16

GNU datamash is a very handy tool for doing stats on groups of columnar data in scripts and one-liners. The catches here are having to remove the non-data lines first, and sorting the input numerically to get output in the desired order.

$ sed '/^$/d; /Cluster/d' input.txt | sort -k1,1n | datamash -Wg1 mean 2
1       22.75
2       24
3       22.5
4       21.5
5       21.75
6       21
7       19
8       24
9       18.666666666667
10      22.666666666667
11      23
12      22
13      23
14      16

Here's a simple python implementation.

# I'll store the output in a list of dicts
def get_averages(filename):
  results = []
  temp_dict = {'count':0, 'total':0, 'avg':0} # unnecessary; illustrate format
  for line in open(filename):
    words = line.rstrip('\n').split(' ')
    try: # if first word is a number
      if (int(words[0]) == 1): # interpret as start of new data list
        temp_dict = {'count':0, 'total':0, 'avg':0} # reset dict
      temp_dict['count'] += 1
      temp_dict['total'] += float(words[1])
    except ValueError:
      if (words[0] == 'Cluster'): # interpret as end of list
        temp_dict['avg']=temp_dict['total']/temp_dict['count']
        results.append(temp_dict)
      temp_dict = None # just to be safe
  return results

And then to get the desired form of your output:

results=get_averages(filename)
for i in range(len(results)):
  print('{} {}'.format(i,results[i]['avg']))