blob: b979480863e3d3891c5d4bd756d9fb900a31a2e5 [file] [log] [blame]
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from pprint import pprint\n",
"from collections import Counter\n",
"import common\n",
"import math"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"commit_list_df = pd.read_csv(\"results/classifier/commitlist.csv\")\n",
"mean_authors=commit_list_df.query(\"category == 'Uncategorized' & topic != 'not user facing'\").author.to_list()\n",
"counts = Counter(mean_authors)\n",
"commit_list_df.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"commit_list_df.category.describe()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# The number un categorized and no topic commits\n",
"no_category = commit_list_df.query(\"category == 'Uncategorized' & topic != 'not user facing'\")\n",
"print(len(no_category))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# check for cherry-picked commits\n",
"example_sha = '55c76baf579cb6593f87d1a23e9a49afeb55f15a'\n",
"commit_hashes = set(commit_list_df.commit_hash.to_list())\n",
"\n",
"example_sha[:11] in commit_hashes"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Get the difference between known categories and categories from commits\n",
"\n",
"diff_categories = set(commit_list_df.category.to_list()) - set(common.categories)\n",
"print(len(diff_categories))\n",
"pprint(diff_categories)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Counts of categories\n"
]
}
],
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