[CPU] Add script for benchmark average counters aggregation

src/plugins/intel_cpu/tools/aggregate-average-counters/README.md

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+# Aggregate average counters
+
+Aggregate csv data produced by
+``` shell
+benchmark_app --report_type average_counters
+```
+
+Simple example:
+``` shell
+aggregate-average-counters.py benchmark_average_counters_report.csv
+```
+
+See `help` for more options
+``` shell
+aggregate-average-counters.py --help
+```
+

src/plugins/intel_cpu/tools/aggregate-average-counters/aggregate-average-counters.py

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+#!/usr/bin/env python3
+import pandas as pd
+import argparse
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument('--format', '-f', choices=['no', 'csv', 'md'], default='no', required=False, help="print data using format")
+    parser.add_argument('--group_by', '-g', choices=['layerName', 'layerType', 'execType'], default=['layerType'], required=False, help="group data by column", nargs='+')
+    parser.add_argument('benchmark_average_counters_file', type=str, action='store')
+    return parser.parse_args();
+
+def get_dataframe(path):
+    with open(path, 'r', newline='') as csvfile:
+        return pd.read_csv(path, delimiter=';', header=0, index_col=0)
+
+def aggregate(df, group_by):
+    # remove existing total
+    df = df.drop(index='Total')
+
+    aggregated = df.groupby(group_by, as_index=False)['cpuTime (ms)'].agg(['count','sum'])
+    # sort by sum
+    result = aggregated.sort_values(by=['sum'], ascending=False)
+    # add percentage
+    result['%'] = (result['sum'] / result['sum'].sum()) * 100
+    # round percentage
+    result = result.round({'%': 2})
+    # add total
+    result.loc['Total'] = result.sum(numeric_only=True)
+    for group in group_by:
+        result.at['Total', group] = 'Total'
+
+    # ensure count as int (no trailing .0)
+    result['count'] = result['count'].astype('int')
+    # rename columns
+    result = result.rename(columns={"count": "Count", "sum":"Sum (ms)"})
+    return result
+
+def print_df(df, format):
+    if format == 'csv':
+        print(df.to_csv(index=False))
+    elif format == 'md':
+        print(df.to_markdown(index=False))
+    else:
+        print(df.to_string(index=False))
+
+if __name__ == "__main__":
+    args = parse_args();
+
+    df = get_dataframe(args.benchmark_average_counters_file);
+    df = aggregate(df, args.group_by)
+    print_df(df, args.format)

src/plugins/intel_cpu/tools/aggregate-average-counters/requirements.txt

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+pandas>=2.0
+argparse