amaury
2146 lines
776 KiB
Plaintext
Vendored
2146 lines
776 KiB
Plaintext
Vendored
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "b6cc3c6b-85c7-4a04-9aef-8ffc055aa93c",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Names Analysis & Modeling"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"id": "initial_id",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T19:54:31.700090Z",
|
||
"start_time": "2025-09-25T19:54:31.689969Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import pandas as pd \n",
|
||
"import unicodedata \n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"import seaborn as sns\n",
|
||
"import numpy as np \n",
|
||
"import re \n",
|
||
"import sys \n",
|
||
"import os\n",
|
||
"from collections import Counter\n",
|
||
"\n",
|
||
"from rich.jupyter import display\n",
|
||
"\n",
|
||
"sys.path.append(os.path.abspath(\"..\")) \n",
|
||
"from collections import Counter \n",
|
||
"from core.utils.data_loader import DataLoader\n",
|
||
"from core.utils.region_mapper import RegionMapper\n",
|
||
"from core.config.pipeline_config import PipelineConfig"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"id": "16647cc71aea7594",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T18:26:50.162866Z",
|
||
"start_time": "2025-09-25T18:26:50.159601Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"LETTERS = 'abcdefghijklmnopqrstuvwxyz'"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"id": "f1a69290-a9c0-40d0-9fe8-a06d8a466671",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T17:39:49.310278Z",
|
||
"start_time": "2025-09-25T17:39:49.304876Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"config = PipelineConfig(\n",
|
||
" paths={\n",
|
||
" \"root_dir\": \"../data\",\n",
|
||
" \"data_dir\": \"../data/dataset\",\n",
|
||
" \"models_dir\": \"../models\",\n",
|
||
" \"outputs_dir\": \"../data/processed\",\n",
|
||
" \"logs_dir\": \"../logs\",\n",
|
||
" \"configs_dir\": \"../configs\",\n",
|
||
" \"checkpoints_dir\": \"../checkpoints\"\n",
|
||
" }\n",
|
||
")\n",
|
||
"\n",
|
||
"loader = DataLoader(config)\n",
|
||
"\n",
|
||
"def normalize_letters(s):\n",
|
||
" \"\"\"Normalize accents -> ascii, lowercase, keep only a-z.\"\"\"\n",
|
||
" s = str(s)\n",
|
||
" s = unicodedata.normalize(\"NFKD\", s)\n",
|
||
" s = s.encode(\"ascii\", errors=\"ignore\").decode(\"utf-8\")\n",
|
||
" s = s.lower()\n",
|
||
" s = re.sub(r\"[^a-z]\", \"\", s)\n",
|
||
" return s"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"id": "e48c6fd9a213bcd2",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T17:59:34.598256Z",
|
||
"start_time": "2025-09-25T17:58:54.210735Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"df = loader.load_csv_complete(config.paths.data_dir / \"names_featured.csv\")\n",
|
||
"df['province'] = RegionMapper.clean_province(df['province'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "2715f291947f5158",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T17:59:38.255948Z",
|
||
"start_time": "2025-09-25T17:59:38.249016Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Index(['name', 'sex', 'region', 'words', 'length', 'probable_native',\n",
|
||
" 'probable_surname', 'identified_name', 'identified_surname',\n",
|
||
" 'ner_entities', 'ner_tagged', 'annotated', 'identified_category',\n",
|
||
" 'province'],\n",
|
||
" dtype='object')"
|
||
]
|
||
},
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.columns"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "93f8859e3e9c4350",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T18:01:22.242283Z",
|
||
"start_time": "2025-09-25T18:01:21.580597Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>count</th>\n",
|
||
" <th>mean</th>\n",
|
||
" <th>std</th>\n",
|
||
" <th>min</th>\n",
|
||
" <th>25%</th>\n",
|
||
" <th>50%</th>\n",
|
||
" <th>75%</th>\n",
|
||
" <th>max</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>words</th>\n",
|
||
" <td>6467942.0</td>\n",
|
||
" <td>2.869578</td>\n",
|
||
" <td>0.46841</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" <td>3.0</td>\n",
|
||
" <td>3.0</td>\n",
|
||
" <td>3.0</td>\n",
|
||
" <td>11.0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>length</th>\n",
|
||
" <td>6467942.0</td>\n",
|
||
" <td>20.141236</td>\n",
|
||
" <td>3.796574</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>18.0</td>\n",
|
||
" <td>21.0</td>\n",
|
||
" <td>23.0</td>\n",
|
||
" <td>60.0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>ner_tagged</th>\n",
|
||
" <td>5018124.0</td>\n",
|
||
" <td>0.997939</td>\n",
|
||
" <td>0.045348</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>annotated</th>\n",
|
||
" <td>5018124.0</td>\n",
|
||
" <td>0.997939</td>\n",
|
||
" <td>0.045348</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" <td>1.0</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" count mean std min 25% 50% 75% max\n",
|
||
"words 6467942.0 2.869578 0.46841 1.0 3.0 3.0 3.0 11.0\n",
|
||
"length 6467942.0 20.141236 3.796574 0.0 18.0 21.0 23.0 60.0\n",
|
||
"ner_tagged 5018124.0 0.997939 0.045348 0.0 1.0 1.0 1.0 1.0\n",
|
||
"annotated 5018124.0 0.997939 0.045348 0.0 1.0 1.0 1.0 1.0"
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.describe().T"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "378147d2abc9ab24",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T18:02:53.214472Z",
|
||
"start_time": "2025-09-25T18:02:52.427559Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th>identified_category</th>\n",
|
||
" <th>compose</th>\n",
|
||
" <th>simple</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>province</th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>AUTRES</th>\n",
|
||
" <td>0.206217</td>\n",
|
||
" <td>0.793783</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>BANDUNDU</th>\n",
|
||
" <td>0.626906</td>\n",
|
||
" <td>0.373094</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>BAS-CONGO</th>\n",
|
||
" <td>0.090813</td>\n",
|
||
" <td>0.909187</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>EQUATEUR</th>\n",
|
||
" <td>0.124238</td>\n",
|
||
" <td>0.875762</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>KASAI-OCCIDENTAL</th>\n",
|
||
" <td>0.261266</td>\n",
|
||
" <td>0.738734</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>KASAI-ORIENTAL</th>\n",
|
||
" <td>0.076224</td>\n",
|
||
" <td>0.923776</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>KATANGA</th>\n",
|
||
" <td>0.180624</td>\n",
|
||
" <td>0.819376</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>KINSHASA</th>\n",
|
||
" <td>0.076792</td>\n",
|
||
" <td>0.923208</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>MANIEMA</th>\n",
|
||
" <td>0.461150</td>\n",
|
||
" <td>0.538850</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>NORD-KIVU</th>\n",
|
||
" <td>0.119626</td>\n",
|
||
" <td>0.880374</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>ORIENTALE</th>\n",
|
||
" <td>0.160905</td>\n",
|
||
" <td>0.839095</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>SUD-KIVU</th>\n",
|
||
" <td>0.409647</td>\n",
|
||
" <td>0.590353</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
"identified_category compose simple\n",
|
||
"province \n",
|
||
"AUTRES 0.206217 0.793783\n",
|
||
"BANDUNDU 0.626906 0.373094\n",
|
||
"BAS-CONGO 0.090813 0.909187\n",
|
||
"EQUATEUR 0.124238 0.875762\n",
|
||
"KASAI-OCCIDENTAL 0.261266 0.738734\n",
|
||
"KASAI-ORIENTAL 0.076224 0.923776\n",
|
||
"KATANGA 0.180624 0.819376\n",
|
||
"KINSHASA 0.076792 0.923208\n",
|
||
"MANIEMA 0.461150 0.538850\n",
|
||
"NORD-KIVU 0.119626 0.880374\n",
|
||
"ORIENTALE 0.160905 0.839095\n",
|
||
"SUD-KIVU 0.409647 0.590353"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Group by province and compute counts\n",
|
||
"from IPython.display import display\n",
|
||
"word_stats = (\n",
|
||
" df.groupby(\"province\")[\"identified_category\"]\n",
|
||
" .value_counts(normalize=True) # get proportions\n",
|
||
" .unstack(fill_value=0) # reshape into columns per word count\n",
|
||
")\n",
|
||
"\n",
|
||
"display(word_stats.head(12))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"id": "6d5c1abb55b7076a",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T18:05:12.951347Z",
|
||
"start_time": "2025-09-25T18:05:12.736698Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1200x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"ax = word_stats.plot(\n",
|
||
" kind=\"bar\",\n",
|
||
" stacked=True,\n",
|
||
" figsize=(12, 6),\n",
|
||
" colormap=\"tab20c\"\n",
|
||
")\n",
|
||
"\n",
|
||
"plt.xlabel(\"Province\")\n",
|
||
"plt.ylabel(\"Proportion (%)\")\n",
|
||
"plt.legend(title=\"Name Category\", bbox_to_anchor=(1.05, 1), loc=\"upper left\")\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"id": "24a4ad40319f441b",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T18:07:02.981141Z",
|
||
"start_time": "2025-09-25T18:06:14.115049Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Explode identified_name into words\n",
|
||
"df_names = (\n",
|
||
" df.assign(\n",
|
||
" name=(\n",
|
||
" df['identified_name']\n",
|
||
" .fillna('')\n",
|
||
" .str.replace(r\"[^\\w'\\-]+\", \" \", regex=True) # keep letters, digits, _, -, '\n",
|
||
" .str.strip()\n",
|
||
" .str.split()\n",
|
||
" )\n",
|
||
" )\n",
|
||
" .explode('name', ignore_index=True)\n",
|
||
" .dropna(subset=['name'])\n",
|
||
")\n",
|
||
"\n",
|
||
"# Clean up tokens\n",
|
||
"df_names['name'] = df_names['name'].str.strip()\n",
|
||
"df_names = df_names[df_names['name'].ne('')]\n",
|
||
"\n",
|
||
"df_names = df_names[['name', 'province', 'sex']].reset_index(drop=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"id": "5ce61cb4109c1cee",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T18:01:37.658949Z",
|
||
"start_time": "2025-09-25T18:01:33.224026Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>count</th>\n",
|
||
" <th>unique</th>\n",
|
||
" <th>top</th>\n",
|
||
" <th>freq</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>name</th>\n",
|
||
" <td>10015595</td>\n",
|
||
" <td>644336</td>\n",
|
||
" <td>ilunga</td>\n",
|
||
" <td>82342</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>province</th>\n",
|
||
" <td>10015595</td>\n",
|
||
" <td>12</td>\n",
|
||
" <td>KINSHASA</td>\n",
|
||
" <td>2106077</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>sex</th>\n",
|
||
" <td>10015595</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>m</td>\n",
|
||
" <td>6033856</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" count unique top freq\n",
|
||
"name 10015595 644336 ilunga 82342\n",
|
||
"province 10015595 12 KINSHASA 2106077\n",
|
||
"sex 10015595 2 m 6033856"
|
||
]
|
||
},
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df_names.describe().T"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"id": "77abf83a2f6360f5",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T17:48:50.735911Z",
|
||
"start_time": "2025-09-25T17:48:49.779413Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>province</th>\n",
|
||
" <th>count_original</th>\n",
|
||
" <th>count_names</th>\n",
|
||
" <th>augmentation</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>KINSHASA</td>\n",
|
||
" <td>1140620</td>\n",
|
||
" <td>2106077</td>\n",
|
||
" <td>84.64</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>AUTRES</td>\n",
|
||
" <td>1035751</td>\n",
|
||
" <td>1644326</td>\n",
|
||
" <td>58.76</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>KATANGA</td>\n",
|
||
" <td>836220</td>\n",
|
||
" <td>1370359</td>\n",
|
||
" <td>63.88</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>BANDUNDU</td>\n",
|
||
" <td>809949</td>\n",
|
||
" <td>604374</td>\n",
|
||
" <td>-25.38</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>KASAI-ORIENTAL</td>\n",
|
||
" <td>434497</td>\n",
|
||
" <td>802757</td>\n",
|
||
" <td>84.76</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>NORD-KIVU</td>\n",
|
||
" <td>394999</td>\n",
|
||
" <td>695494</td>\n",
|
||
" <td>76.07</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>KASAI-OCCIDENTAL</td>\n",
|
||
" <td>367626</td>\n",
|
||
" <td>543156</td>\n",
|
||
" <td>47.75</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>EQUATEUR</td>\n",
|
||
" <td>356404</td>\n",
|
||
" <td>624252</td>\n",
|
||
" <td>75.15</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>SUD-KIVU</td>\n",
|
||
" <td>346152</td>\n",
|
||
" <td>408708</td>\n",
|
||
" <td>18.07</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>ORIENTALE</td>\n",
|
||
" <td>322756</td>\n",
|
||
" <td>541646</td>\n",
|
||
" <td>67.82</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>10</th>\n",
|
||
" <td>BAS-CONGO</td>\n",
|
||
" <td>295155</td>\n",
|
||
" <td>536702</td>\n",
|
||
" <td>81.84</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>11</th>\n",
|
||
" <td>MANIEMA</td>\n",
|
||
" <td>127813</td>\n",
|
||
" <td>137744</td>\n",
|
||
" <td>7.77</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" province count_original count_names augmentation\n",
|
||
"0 KINSHASA 1140620 2106077 84.64\n",
|
||
"1 AUTRES 1035751 1644326 58.76\n",
|
||
"2 KATANGA 836220 1370359 63.88\n",
|
||
"3 BANDUNDU 809949 604374 -25.38\n",
|
||
"4 KASAI-ORIENTAL 434497 802757 84.76\n",
|
||
"5 NORD-KIVU 394999 695494 76.07\n",
|
||
"6 KASAI-OCCIDENTAL 367626 543156 47.75\n",
|
||
"7 EQUATEUR 356404 624252 75.15\n",
|
||
"8 SUD-KIVU 346152 408708 18.07\n",
|
||
"9 ORIENTALE 322756 541646 67.82\n",
|
||
"10 BAS-CONGO 295155 536702 81.84\n",
|
||
"11 MANIEMA 127813 137744 7.77"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Province counts before exploding\n",
|
||
"prov_counts_orig = (\n",
|
||
" df['province'].value_counts()\n",
|
||
" .rename_axis(\"province\")\n",
|
||
" .reset_index(name=\"count_original\")\n",
|
||
")\n",
|
||
"\n",
|
||
"# Province counts after exploding into df_names\n",
|
||
"prov_counts_names = (\n",
|
||
" df_names['province'].value_counts()\n",
|
||
" .rename_axis(\"province\")\n",
|
||
" .reset_index(name=\"count_names\")\n",
|
||
")\n",
|
||
"\n",
|
||
"# Merge both into one table\n",
|
||
"comparison = (\n",
|
||
" prov_counts_orig\n",
|
||
" .merge(prov_counts_names, on=\"province\", how=\"outer\")\n",
|
||
" .fillna(0)\n",
|
||
")\n",
|
||
"\n",
|
||
"# Add augmentation percentage\n",
|
||
"comparison[\"augmentation\"] = (\n",
|
||
" (comparison[\"count_names\"] - comparison[\"count_original\"])\n",
|
||
" / comparison[\"count_original\"]\n",
|
||
" * 100\n",
|
||
").round(2)\n",
|
||
"\n",
|
||
"# Sort and display top 12 provinces\n",
|
||
"comparison = (\n",
|
||
" comparison\n",
|
||
" .sort_values(\"count_original\", ascending=False)\n",
|
||
" .reset_index(drop=True)\n",
|
||
")\n",
|
||
"\n",
|
||
"display(comparison.head(12))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "98ba6e48-a7c4-4aae-8b46-872489c95faf",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Transition probabilities"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"id": "e324e1c9e8da4bd8",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T19:59:00.238808Z",
|
||
"start_time": "2025-09-25T19:59:00.225716Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def build_transition_probs(\n",
|
||
" names: pd.Series,\n",
|
||
" *,\n",
|
||
" letters: str = \"abcdefghijklmnopqrstuvwxyz\",\n",
|
||
" start_token: str = \"^\",\n",
|
||
" end_token: str = \"$\",\n",
|
||
" alpha: float = 0.0, # Laplace smoothing; e.g., 1.0 to avoid zeros\n",
|
||
") -> dict:\n",
|
||
" # 1) Normalize\n",
|
||
" names = (\n",
|
||
" names.astype(str)\n",
|
||
" .str.lower()\n",
|
||
" .str.replace(fr\"[^{letters}]\", \"\", regex=True)\n",
|
||
" )\n",
|
||
" names = names[names.str.len() > 0]\n",
|
||
"\n",
|
||
" # 2) Prepare sequences\n",
|
||
" sequences = (start_token + names + end_token).tolist()\n",
|
||
"\n",
|
||
" # 3) Tokens and indices\n",
|
||
" tokens = [start_token] + list(letters) + [end_token]\n",
|
||
" index = {t: i for i, t in enumerate(tokens)}\n",
|
||
" V = len(tokens)\n",
|
||
"\n",
|
||
" # 4) ASCII lookup table (O(1) char -> idx); others -> -1\n",
|
||
" lut = np.full(128, -1, dtype=np.int32)\n",
|
||
" for ch, i in index.items():\n",
|
||
" lut[ord(ch)] = i\n",
|
||
"\n",
|
||
" # 5) Concatenate with a separator that’s not in vocab to kill cross-boundary pairs\n",
|
||
" concat = (\" \".join(sequences)).encode(\"ascii\", errors=\"ignore\")\n",
|
||
"\n",
|
||
" # 6) Map bytes to indices\n",
|
||
" arr = np.frombuffer(concat, dtype=np.uint8)\n",
|
||
" idx = lut[arr]\n",
|
||
"\n",
|
||
" # 7) Build bigram pairs; drop invalid ones (separator & OOV)\n",
|
||
" a = idx[:-1]\n",
|
||
" b = idx[1:]\n",
|
||
" mask = (a >= 0) & (b >= 0)\n",
|
||
" a, b = a[mask], b[mask]\n",
|
||
"\n",
|
||
" # 8) Count with a single bincount\n",
|
||
" lin = a * V + b\n",
|
||
" counts = np.bincount(lin, minlength=V * V).reshape(V, V)\n",
|
||
"\n",
|
||
" # 9) Optional Laplace smoothing\n",
|
||
" if alpha and alpha > 0:\n",
|
||
" counts = counts + alpha\n",
|
||
"\n",
|
||
" # 10) Row-normalize to probabilities\n",
|
||
" row_sums = counts.sum(axis=1, keepdims=True)\n",
|
||
" # avoid division by zero\n",
|
||
" probs = np.divide(counts, np.where(row_sums == 0, 1.0, row_sums), where=True)\n",
|
||
"\n",
|
||
" # 11) DataFrames\n",
|
||
" df_counts = pd.DataFrame(counts, index=tokens, columns=tokens)\n",
|
||
" df_probs = pd.DataFrame(probs, index=tokens, columns=tokens)\n",
|
||
"\n",
|
||
" return {\n",
|
||
" \"tokens\": tokens,\n",
|
||
" \"index\": index,\n",
|
||
" \"counts\": counts,\n",
|
||
" \"df_counts\": df_counts,\n",
|
||
" \"probs\": probs,\n",
|
||
" \"df_probs\": df_probs,\n",
|
||
" }\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"id": "12a7094d94ad519f",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T19:59:41.506588Z",
|
||
"start_time": "2025-09-25T19:59:03.640342Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"transitions_both = build_transition_probs(df_names['name'])\n",
|
||
"transitions_male = build_transition_probs(df_names.loc[df_names['sex'].str.lower() == 'm', 'name'])\n",
|
||
"transitions_female = build_transition_probs(df_names.loc[df_names['sex'].str.lower() == 'f', 'name'])\n",
|
||
"\n",
|
||
"# Access the probability matrices\n",
|
||
"P_both = transitions_both['probs']\n",
|
||
"P_male = transitions_male['probs']\n",
|
||
"P_female = transitions_female['probs']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"id": "67b3e0f724af646b",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T20:02:32.577754Z",
|
||
"start_time": "2025-09-25T20:02:32.569329Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def plot_transition_matrix(ax, df_probs, title=\"\", letters=\"abcdefghijklmnopqrstuvwxyz\"):\n",
|
||
" hm = sns.heatmap(\n",
|
||
" df_probs.loc[list(letters), list(letters)],\n",
|
||
" cmap=\"Reds\",\n",
|
||
" annot=False,\n",
|
||
" cbar=False,\n",
|
||
" ax=ax\n",
|
||
" )\n",
|
||
" ax.set_title(title, fontsize=12)\n",
|
||
" return hm"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"id": "f15ad6eb4df27527",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T20:02:36.087443Z",
|
||
"start_time": "2025-09-25T20:02:34.953458Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 2000x600 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Create 1x3 grid\n",
|
||
"fig, axes = plt.subplots(1, 3, figsize=(20, 6), sharex=True, sharey=True)\n",
|
||
"\n",
|
||
"hm1 = plot_transition_matrix(axes[0], transitions_male['df_probs'], \"Male\")\n",
|
||
"hm2 = plot_transition_matrix(axes[1], transitions_female['df_probs'], \"Female\")\n",
|
||
"hm3 = plot_transition_matrix(axes[2], transitions_both['df_probs'], \"All\")\n",
|
||
"\n",
|
||
"# Add one shared colorbar\n",
|
||
"cbar = fig.colorbar(hm3.collections[0], ax=axes, orientation=\"vertical\", fraction=0.03, pad=0.02)\n",
|
||
"cbar.set_label(\"Transition probability\")\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"id": "51ec0792317364fc",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T20:03:42.518370Z",
|
||
"start_time": "2025-09-25T20:03:42.145944Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 600x500 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"diff = transitions_male['df_probs'] - transitions_female['df_probs']\n",
|
||
"\n",
|
||
"plt.figure(figsize=(6, 5))\n",
|
||
"sns.heatmap(diff.loc[list(LETTERS), list(LETTERS)], cmap=\"RdBu_r\", center=0, annot=False)\n",
|
||
"plt.title(\"Male – Female Transition Probability Differences\")\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"id": "dae836cd8a6c26e6",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T19:54:41.378255Z",
|
||
"start_time": "2025-09-25T19:54:41.361591Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"L2 distance: 0.3189\n",
|
||
"KL(male||female): 0.0432\n",
|
||
"KL(female||male): 0.0215\n",
|
||
"JSD: 0.0324\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"from scipy.spatial.distance import euclidean\n",
|
||
"from scipy.stats import entropy\n",
|
||
"\n",
|
||
"P_m = transitions_male['probs'].flatten()\n",
|
||
"P_f = transitions_female['probs'].flatten()\n",
|
||
"\n",
|
||
"# L2 distance\n",
|
||
"l2 = euclidean(P_m, P_f)\n",
|
||
"\n",
|
||
"# KL divergence (use smoothing to avoid log(0))\n",
|
||
"kl_mf = entropy(P_m + 1e-12, P_f + 1e-12) # D_KL(male || female)\n",
|
||
"kl_fm = entropy(P_f + 1e-12, P_m + 1e-12)\n",
|
||
"\n",
|
||
"# Symmetric Jensen-Shannon divergence\n",
|
||
"jsd = 0.5 * (kl_mf + kl_fm)\n",
|
||
"\n",
|
||
"print(f\"L2 distance: {l2:.4f}\")\n",
|
||
"print(f\"KL(male||female): {kl_mf:.4f}\")\n",
|
||
"print(f\"KL(female||male): {kl_fm:.4f}\")\n",
|
||
"print(f\"JSD: {jsd:.4f}\")\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "f0bbe49cf3e65f10",
|
||
"metadata": {},
|
||
"source": [
|
||
"The transition probabilities of characters in male and female names from your dataset are very similar. There are measurable but small differences: male names diverge slightly more from the female pattern than the reverse. However, the overall structure of how characters follow each other is largely shared between the two groups."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"id": "d029bbd85794df95",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T20:20:11.270081Z",
|
||
"start_time": "2025-09-25T20:20:11.244279Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Row 'a' → χ²=66636.402, dof=26, p=0.000e+00\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"import pandas as pd\n",
|
||
"from scipy.stats import chi2_contingency\n",
|
||
"\n",
|
||
"def chi2_row_test(trans_male, trans_female, row_token, alpha=0.5, min_expected=1e-12):\n",
|
||
" \"\"\"\n",
|
||
" Chi-square test comparing next-letter distributions for a given starting letter.\n",
|
||
" Handles zeros by dropping all-zero columns and adding pseudocount alpha.\n",
|
||
"\n",
|
||
" Args:\n",
|
||
" trans_male, trans_female: dicts returned by build_transition_probs (need 'counts','index','tokens')\n",
|
||
" row_token: e.g., 'a'\n",
|
||
" alpha: pseudocount added to every cell (0.5 is common; set 0 to disable)\n",
|
||
" min_expected: tiny floor to avoid expected==0 after drop (defensive)\n",
|
||
" \"\"\"\n",
|
||
" i_m = trans_male['index'][row_token]\n",
|
||
" i_f = trans_female['index'][row_token]\n",
|
||
" cm = trans_male['counts'][i_m].astype(float)\n",
|
||
" cf = trans_female['counts'][i_f].astype(float)\n",
|
||
"\n",
|
||
" # Stack into 2xK\n",
|
||
" table = np.vstack([cm, cf])\n",
|
||
"\n",
|
||
" # Drop columns with zero total across both groups\n",
|
||
" keep = table.sum(axis=0) > 0\n",
|
||
" table = table[:, keep]\n",
|
||
"\n",
|
||
" # If everything got dropped or only 1 column left, test is undefined\n",
|
||
" if table.size == 0 or table.shape[1] < 2:\n",
|
||
" return np.nan, np.nan, 0, None\n",
|
||
"\n",
|
||
" # Add pseudocounts (helps with sparsity and zero expected)\n",
|
||
" if alpha and alpha > 0:\n",
|
||
" table = table + alpha\n",
|
||
"\n",
|
||
" chi2, p, dof, expected = chi2_contingency(table, correction=False)\n",
|
||
" # Defensive floor (optional)\n",
|
||
" if np.any(expected < min_expected):\n",
|
||
" # fall back: jitter + rerun (very rare)\n",
|
||
" table = table + 1e-9\n",
|
||
" chi2, p, dof, expected = chi2_contingency(table, correction=False)\n",
|
||
" return chi2, p, dof, expected\n",
|
||
"\n",
|
||
"# Example: a single row\n",
|
||
"chi2, p, dof, expected = chi2_row_test(transitions_male, transitions_female, row_token='a', alpha=0.5)\n",
|
||
"print(f\"Row 'a' → χ²={chi2:.3f}, dof={dof}, p={p:.3e}\")\n",
|
||
"\n",
|
||
"# Run for all letters and assemble a summary (with FDR correction)\n",
|
||
"from statsmodels.stats.multitest import multipletests\n",
|
||
"\n",
|
||
"tokens = [t for t in transitions_both['tokens'] if t not in ('^','$')]\n",
|
||
"results = []\n",
|
||
"for t in tokens:\n",
|
||
" chi2, p, dof, _ = chi2_row_test(transitions_male, transitions_female, row_token=t, alpha=0.5)\n",
|
||
" results.append((t, chi2, dof, p))\n",
|
||
"\n",
|
||
"df_tests = pd.DataFrame(results, columns=['row_token','chi2','dof','p'])\n",
|
||
"# FDR (Benjamini–Hochberg)\n",
|
||
"mask = df_tests['p'].notna()\n",
|
||
"rej, p_adj, _, _ = multipletests(df_tests.loc[mask, 'p'], method='fdr_bh')\n",
|
||
"df_tests.loc[mask, 'p_adj'] = p_adj\n",
|
||
"df_tests.loc[mask, 'significant'] = rej\n",
|
||
"\n",
|
||
"df_tests = df_tests.sort_values('chi2', ascending=False).reset_index(drop=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"id": "80e7f52285a073ea",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T20:20:17.405785Z",
|
||
"start_time": "2025-09-25T20:20:17.395818Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>row_token</th>\n",
|
||
" <th>chi2</th>\n",
|
||
" <th>dof</th>\n",
|
||
" <th>p</th>\n",
|
||
" <th>p_adj</th>\n",
|
||
" <th>significant</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>a</td>\n",
|
||
" <td>66636.401639</td>\n",
|
||
" <td>26</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>True</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>i</td>\n",
|
||
" <td>36497.202246</td>\n",
|
||
" <td>26</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>True</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>n</td>\n",
|
||
" <td>32505.512092</td>\n",
|
||
" <td>25</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>True</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>u</td>\n",
|
||
" <td>31904.897504</td>\n",
|
||
" <td>26</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>True</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>g</td>\n",
|
||
" <td>24595.637377</td>\n",
|
||
" <td>26</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>True</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>m</td>\n",
|
||
" <td>23254.272134</td>\n",
|
||
" <td>26</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>True</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>e</td>\n",
|
||
" <td>19945.183545</td>\n",
|
||
" <td>26</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>True</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" row_token chi2 dof p p_adj significant\n",
|
||
"0 a 66636.401639 26 0.0 0.0 True\n",
|
||
"1 i 36497.202246 26 0.0 0.0 True\n",
|
||
"2 n 32505.512092 25 0.0 0.0 True\n",
|
||
"3 u 31904.897504 26 0.0 0.0 True\n",
|
||
"4 g 24595.637377 26 0.0 0.0 True\n",
|
||
"5 m 23254.272134 26 0.0 0.0 True\n",
|
||
"6 e 19945.183545 26 0.0 0.0 True"
|
||
]
|
||
},
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df_tests.head(7)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "d5cd70c832e5ac2",
|
||
"metadata": {},
|
||
"source": [
|
||
"Male and female names in your dataset have very similar character transition patterns overall (global JSD ≈ 0.03),\n",
|
||
"But for certain letters — especially a, i, n, u, g, m, e — the differences are statistically huge.\n",
|
||
"These letters likely correspond to prefixes or suffixes that carry strong gender information in local naming traditions."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "c49254df7eee9ae2",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Letters frequency"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"id": "ffb0b937-fb9e-47d5-94c7-20afdf99560c",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T20:27:29.403600Z",
|
||
"start_time": "2025-09-25T20:27:29.397414Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def letter_freq(df: pd.DataFrame, col: str = \"name\") -> pd.DataFrame:\n",
|
||
" s = (\n",
|
||
" df[col].astype(str).str.lower()\n",
|
||
" .str.replace(r'[^a-z]', '', regex=True) # keep only a–z\n",
|
||
" .str.cat(sep='') # one big string\n",
|
||
" )\n",
|
||
" ser = pd.Series(list(s))\n",
|
||
" out = (\n",
|
||
" ser.value_counts(normalize=False)\n",
|
||
" .reindex(list(LETTERS), fill_value=0)\n",
|
||
" .rename_axis(\"letter\").reset_index(name=\"count\")\n",
|
||
" )\n",
|
||
" total = out[\"count\"].sum()\n",
|
||
" out[\"freq\"] = out[\"count\"] / (total if total > 0 else 1)\n",
|
||
" return out\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"id": "4a0d8e2a74a6406c",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:39:15.252765Z",
|
||
"start_time": "2025-09-25T21:39:15.191830Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def plot_letter_grid(df_all: pd.DataFrame, use=\"freq\", sort_values=False):\n",
|
||
" \"\"\"\n",
|
||
" Plot a 1×3 grid of letter distributions for Male, Female, and Both.\n",
|
||
" `use` ∈ {\"freq\",\"count\"} controls y-axis.\n",
|
||
" \"\"\"\n",
|
||
" # Slice datasets (adapt values if your labels are 'M'/'F', etc.)\n",
|
||
" df_male = df_all[df_all['sex'].str.lower() == str('m').lower()]\n",
|
||
" df_female = df_all[df_all['sex'].str.lower() == str('f').lower()]\n",
|
||
"\n",
|
||
" L_m = letter_freq(df_male, col='name')\n",
|
||
" L_f = letter_freq(df_female, col='name')\n",
|
||
"\n",
|
||
" y = \"freq\" if use == \"freq\" else \"count\"\n",
|
||
" if sort_values:\n",
|
||
" L_m = L_m.sort_values(y, ascending=False)\n",
|
||
" L_f = L_f.sort_values(y, ascending=False)\n",
|
||
"\n",
|
||
" ymax = max(L_m[y].max(), L_f[y].max()) * 1.10\n",
|
||
"\n",
|
||
" fig, axes = plt.subplots(1, 2, figsize=(18, 5), sharey=True, constrained_layout=True)\n",
|
||
" for ax, data, title in zip(axes, [L_m, L_f], [\"Male\", \"Female\"]):\n",
|
||
" ax.bar(data[\"letter\"], data[y], color=\"steelblue\", alpha=0.8)\n",
|
||
" ax.set_title(title)\n",
|
||
" ax.set_xlabel(\"Letter\")\n",
|
||
" ax.set_ylim(0, ymax)\n",
|
||
" ax.grid(axis=\"y\", alpha=0.3)\n",
|
||
" axes[0].set_ylabel(\"Frequency\" if y == \"freq\" else \"Count\")\n",
|
||
" plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"id": "9265e47639c4319d",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:39:45.123899Z",
|
||
"start_time": "2025-09-25T21:39:17.350875Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x500 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_letter_grid(df_names, use=\"freq\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"id": "395dace523f1bed4",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:40:08.366997Z",
|
||
"start_time": "2025-09-25T21:39:45.174312Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x500 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_letter_grid(df_names, use=\"freq\", sort_values=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"id": "98c7ed61-5c2d-4d9a-9d85-e4efe4bfc402",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:35:00.849876Z",
|
||
"start_time": "2025-09-25T21:35:00.831997Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def count_ngrams(df: pd.DataFrame, n: int, col: str = \"name\") -> pd.DataFrame:\n",
|
||
" # Normalize and clean\n",
|
||
" _names = (\n",
|
||
" df[col]\n",
|
||
" .astype(str)\n",
|
||
" .str.lower()\n",
|
||
" .str.replace(r\"[^a-z]\", \"\", regex=True)\n",
|
||
" )\n",
|
||
"\n",
|
||
" # Collect n-grams from all names\n",
|
||
" ngrams = []\n",
|
||
" for name in _names:\n",
|
||
" if len(name) >= n:\n",
|
||
" ngrams.extend(name[i:i+n] for i in range(len(name) - n + 1))\n",
|
||
"\n",
|
||
" # Count\n",
|
||
" counter = Counter(ngrams)\n",
|
||
"\n",
|
||
" # Build DataFrame\n",
|
||
" df_ngrams = (\n",
|
||
" pd.DataFrame(counter.items(), columns=[f\"{n}-gram\", \"count\"])\n",
|
||
" .sort_values(\"count\", ascending=False)\n",
|
||
" .reset_index(drop=True)\n",
|
||
" )\n",
|
||
" df_ngrams[\"freq\"] = df_ngrams[\"count\"] / df_ngrams[\"count\"].sum()\n",
|
||
" return df_ngrams\n",
|
||
"\n",
|
||
"def plot_ngrams_grid(df: pd.DataFrame, n: int, top_k: int = 20,\n",
|
||
" gender_col=\"sex\", male_value=\"m\", female_value=\"f\", name_col=\"name\"):\n",
|
||
" \"\"\"\n",
|
||
" Plot top n-grams for Male, Female, and All in a 1×3 grid.\n",
|
||
" \"\"\"\n",
|
||
" # Split datasets\n",
|
||
" df_male = df[df[gender_col].str.lower() == str(male_value).lower()]\n",
|
||
" df_female = df[df[gender_col].str.lower() == str(female_value).lower()]\n",
|
||
"\n",
|
||
" # Compute n-grams\n",
|
||
" ng_male = count_ngrams(df_male, n, col=name_col)\n",
|
||
" ng_female = count_ngrams(df_female, n, col=name_col)\n",
|
||
"\n",
|
||
" # Plot in a grid\n",
|
||
" fig, axes = plt.subplots(1, 2, figsize=(18, 6), sharey=True, constrained_layout=True)\n",
|
||
" for ax, data, title in zip(\n",
|
||
" axes, [ng_male, ng_female], [\"Male\", \"Female\"]\n",
|
||
" ):\n",
|
||
" sns.barplot(\n",
|
||
" data=data.head(top_k),\n",
|
||
" x=f\"{n}-gram\", y=\"count\",\n",
|
||
" ax=ax\n",
|
||
" )\n",
|
||
" ax.set_title(f\"{title} – Top {top_k} {n}-grams\")\n",
|
||
" ax.set_xlabel(f\"{n}-gram\")\n",
|
||
" ax.set_ylabel(\"Count\")\n",
|
||
" ax.tick_params(axis=\"x\", rotation=45)\n",
|
||
"\n",
|
||
" plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"id": "412883b2-c1fd-483f-b61a-ba2bfc8b04e7",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:35:45.360163Z",
|
||
"start_time": "2025-09-25T21:35:03.778209Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x600 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_ngrams_grid(df_names, n=3, top_k=20, gender_col=\"sex\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"id": "b4eda839e6cc5d8f",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:36:19.354244Z",
|
||
"start_time": "2025-09-25T21:35:45.428602Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x600 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_ngrams_grid(df_names, n=4, top_k=20, gender_col=\"sex\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"id": "55605ab05b9a10bb",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:36:46.475564Z",
|
||
"start_time": "2025-09-25T21:36:21.247703Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x600 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_ngrams_grid(df_names, n=5, top_k=20, gender_col=\"sex\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "28e65639-9082-464d-9330-71e2a028c878",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Name generation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"id": "28fe77f9-f9b0-4267-9dbb-3969e04b83fb",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:43:42.826584Z",
|
||
"start_time": "2025-09-25T21:43:42.798968Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# tokens must include '^' (start) and '$' (end)\n",
|
||
"tokens = [\"^\"] + list(LETTERS) + [\"$\"]\n",
|
||
"token_to_idx = {t: i for i, t in enumerate(tokens)}\n",
|
||
"idx_to_token = np.array(tokens)\n",
|
||
"V = len(tokens)\n",
|
||
"\n",
|
||
"# Prepare a well-formed probability matrix (rows sum to 1, no NaNs/negatives)\n",
|
||
"def prepare_prob_matrix(df_probs, tokens):\n",
|
||
" import pandas as pd, numpy as np\n",
|
||
" if isinstance(df_probs, pd.DataFrame):\n",
|
||
" P = df_probs.loc[tokens, tokens].to_numpy(dtype=float, copy=True)\n",
|
||
" else:\n",
|
||
" P = np.array(df_probs, dtype=float, copy=True)\n",
|
||
" if P.shape[0] != len(tokens) or P.shape[1] != len(tokens):\n",
|
||
" raise ValueError(\n",
|
||
" f\"Matrix shape {P.shape} does not match tokens length {len(tokens)}. \"\n",
|
||
" \"Use the same tokens used to build the matrix (e.g., transitions['tokens']).\"\n",
|
||
" )\n",
|
||
" # clean & renormalize\n",
|
||
" P[~np.isfinite(P) | (P < 0)] = 0.0\n",
|
||
" rs = P.sum(axis=1, keepdims=True)\n",
|
||
" P = np.divide(P, np.where(rs == 0, 1.0, rs), out=np.zeros_like(P), where=True)\n",
|
||
" return P\n",
|
||
"\n",
|
||
"\n",
|
||
"def generate_name(P, token_to_idx, idx_to_token, *,\n",
|
||
" target_len=None, # exact character length (letters only), if provided\n",
|
||
" min_len=1, # minimum character length\n",
|
||
" max_len=12, # hard cap on steps\n",
|
||
" temperature=1.0):\n",
|
||
" start = token_to_idx['^']\n",
|
||
" end = token_to_idx['$']\n",
|
||
" cur = start\n",
|
||
" out = []\n",
|
||
"\n",
|
||
" for _ in range(max_len):\n",
|
||
" row = P[cur]\n",
|
||
"\n",
|
||
" # Temperature scaling (τ<1 = sharper, τ>1 = flatter)\n",
|
||
" if temperature != 1.0:\n",
|
||
" row = np.power(row, 1.0 / temperature)\n",
|
||
" s = row.sum()\n",
|
||
" row = row / s if s > 0 else row\n",
|
||
"\n",
|
||
" row_mod = row.copy()\n",
|
||
"\n",
|
||
" # 1) Prevent early stop before min_len\n",
|
||
" if len(out) < min_len:\n",
|
||
" row_mod[end] = 0.0\n",
|
||
"\n",
|
||
" # 2) If target_len reached or exceeded, force end\n",
|
||
" if target_len is not None and len(out) >= target_len:\n",
|
||
" row_mod[:] = 0.0\n",
|
||
" row_mod[end] = 1.0\n",
|
||
"\n",
|
||
" s = row_mod.sum()\n",
|
||
" if s == 0.0:\n",
|
||
" # Fallback: uniform over valid next tokens\n",
|
||
" candidates = np.arange(V)\n",
|
||
" # exclude '^'\n",
|
||
" candidates = candidates[candidates != start]\n",
|
||
" # exclude '$' if below min_len\n",
|
||
" if len(out) < min_len:\n",
|
||
" candidates = candidates[candidates != end]\n",
|
||
" probs = np.ones(len(candidates)) / len(candidates)\n",
|
||
" nxt_idx = np.random.choice(candidates, p=probs)\n",
|
||
" else:\n",
|
||
" row_mod = row_mod / s\n",
|
||
" nxt_idx = np.random.choice(V, p=row_mod)\n",
|
||
"\n",
|
||
" if nxt_idx == end:\n",
|
||
" break\n",
|
||
" out.append(idx_to_token[nxt_idx])\n",
|
||
" cur = nxt_idx\n",
|
||
"\n",
|
||
" return \"\".join(out).capitalize()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"id": "a01eb547985d5a62",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:43:58.987200Z",
|
||
"start_time": "2025-09-25T21:43:57.635944Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Example preparation and usage\n",
|
||
"P = prepare_prob_matrix(transitions_male['df_probs'], tokens)\n",
|
||
"generated_var = [generate_name(P, token_to_idx, idx_to_token, min_len=5, max_len=12, temperature=0.5) for _ in range(10)]\n",
|
||
"\n",
|
||
"names = pd.DataFrame(generated_var, columns=[\"name\"])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"id": "c5bcbff0204ceaa4",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:44:03.354829Z",
|
||
"start_time": "2025-09-25T21:44:03.336042Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>name</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>Mambo</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>Mbanga</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>Bomanga</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>Kasala</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>Mbiangonga</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>Mambe</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>Mangi</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>Mbangando</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>Mulombe</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>Kitoto</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" name\n",
|
||
"0 Mambo\n",
|
||
"1 Mbanga\n",
|
||
"2 Bomanga\n",
|
||
"3 Kasala\n",
|
||
"4 Mbiangonga\n",
|
||
"5 Mambe\n",
|
||
"6 Mangi\n",
|
||
"7 Mbangando\n",
|
||
"8 Mulombe\n",
|
||
"9 Kitoto"
|
||
]
|
||
},
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"names"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"id": "5d5ec37da189b7a8",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:44:29.411892Z",
|
||
"start_time": "2025-09-25T21:44:29.403639Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"P = prepare_prob_matrix(transitions_female['df_probs'], tokens)\n",
|
||
"generated_var = [generate_name(P, token_to_idx, idx_to_token, min_len=5, max_len=12, temperature=0.5) for _ in range(10)]\n",
|
||
"\n",
|
||
"names = pd.DataFrame(generated_var, columns=[\"name\"])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"id": "f9da3dad4317ac10",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-09-25T21:44:33.290488Z",
|
||
"start_time": "2025-09-25T21:44:33.284314Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>name</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>Mungu</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>Mando</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>Malusha</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>Mumana</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>Mbanga</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>Nganga</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>Mbamba</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>Lango</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>Mumba</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>Mbango</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" name\n",
|
||
"0 Mungu\n",
|
||
"1 Mando\n",
|
||
"2 Malusha\n",
|
||
"3 Mumana\n",
|
||
"4 Mbanga\n",
|
||
"5 Nganga\n",
|
||
"6 Mbamba\n",
|
||
"7 Lango\n",
|
||
"8 Mumba\n",
|
||
"9 Mbango"
|
||
]
|
||
},
|
||
"execution_count": 34,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"names"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "a0ed137d-a75e-49eb-95b8-e3a2c65fa2a0",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Transition Probabilities (for surname)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"id": "18bd2610-170d-47cc-926a-6cf9a126cef5",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Explode identified_surname into words\n",
|
||
"df_surnames = (\n",
|
||
" df.assign(\n",
|
||
" surname=(\n",
|
||
" df['identified_surname']\n",
|
||
" .fillna('')\n",
|
||
" .str.replace(r\"[^\\w'\\-]+\", \" \", regex=True)\n",
|
||
" .str.strip()\n",
|
||
" .str.split()\n",
|
||
" )\n",
|
||
" )\n",
|
||
" .explode('surname', ignore_index=True)\n",
|
||
" .dropna(subset=['surname'])\n",
|
||
")\n",
|
||
"\n",
|
||
"# Clean tokens\n",
|
||
"df_surnames['surname'] = df_surnames['surname'].str.strip()\n",
|
||
"df_surnames = df_surnames[df_surnames['surname'].ne('')]\n",
|
||
"\n",
|
||
"df_surnames = df_surnames[['surname', 'province', 'sex']].reset_index(drop=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 42,
|
||
"id": "e2e53f6e-4ae9-4ea5-9135-02d9f2a46554",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Transition probabilities for identified_surname\n",
|
||
"transitions_surname_both = build_transition_probs(df['identified_surname'])\n",
|
||
"transitions_surname_male = build_transition_probs(\n",
|
||
" df.loc[df['sex'].str.lower() == 'm', 'identified_surname']\n",
|
||
")\n",
|
||
"transitions_surname_female = build_transition_probs(\n",
|
||
" df.loc[df['sex'].str.lower() == 'f', 'identified_surname']\n",
|
||
")\n",
|
||
"\n",
|
||
"# Access matrices\n",
|
||
"P_surname_both = transitions_surname_both['probs']\n",
|
||
"P_surname_male = transitions_surname_male['probs']\n",
|
||
"P_surname_female = transitions_surname_female['probs']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 43,
|
||
"id": "d339f85f-1a0f-4025-8185-63fe039b87e3",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 2000x600 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Plot heatmaps for surnames\n",
|
||
"fig, axes = plt.subplots(1, 3, figsize=(20, 6), sharex=True, sharey=True)\n",
|
||
"\n",
|
||
"hm1 = plot_transition_matrix(axes[0], transitions_surname_male['df_probs'], \"Male (surnames)\")\n",
|
||
"hm2 = plot_transition_matrix(axes[1], transitions_surname_female['df_probs'], \"Female (surnames)\")\n",
|
||
"hm3 = plot_transition_matrix(axes[2], transitions_surname_both['df_probs'], \"All (surnames)\")\n",
|
||
"\n",
|
||
"# Shared colorbar\n",
|
||
"cbar = fig.colorbar(hm3.collections[0], ax=axes, orientation=\"vertical\", fraction=0.03, pad=0.02)\n",
|
||
"cbar.set_label(\"Transition probability\")\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 44,
|
||
"id": "ab4176d9-e206-48d4-9a4e-d4e226f978fe",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 600x500 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Difference between male and female surname transition probabilities\n",
|
||
"diff_surnames = transitions_surname_male['df_probs'] - transitions_surname_female['df_probs']\n",
|
||
"\n",
|
||
"plt.figure(figsize=(6, 5))\n",
|
||
"sns.heatmap(\n",
|
||
" diff_surnames.loc[list(\"abcdefghijklmnopqrstuvwxyz\"), list(\"abcdefghijklmnopqrstuvwxyz\")],\n",
|
||
" cmap=\"RdBu_r\",\n",
|
||
" center=0,\n",
|
||
" annot=False\n",
|
||
")\n",
|
||
"plt.title(\"Male – Female Transition Probability Differences (surnames)\")\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 45,
|
||
"id": "f210fbf7-a6c0-4661-b576-db1b3c488c63",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"transitions_both = build_transition_probs(df_surnames['surname'])\n",
|
||
"transitions_male = build_transition_probs(df_surnames.loc[df_surnames['sex'].str.lower() == 'm', 'surname'])\n",
|
||
"transitions_female = build_transition_probs(df_surnames.loc[df_surnames['sex'].str.lower() == 'f', 'surname'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 46,
|
||
"id": "9527ec56-ebdf-465b-aa9c-52119987cba7",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x500 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_letter_grid(df_surnames.rename(columns={'surname': 'name'}), use=\"freq\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 53,
|
||
"id": "1028daaa-6b15-4c9b-b67a-583234a700b7",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x500 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_letter_grid(df_surnames.rename(columns={\"surname\": \"name\"}), use=\"freq\", sort_values=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 47,
|
||
"id": "f205e4a0-2565-47cb-829e-27c142062483",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x600 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_ngrams_grid(df_surnames.rename(columns={'surname': 'name'}), n=3, top_k=20, gender_col=\"sex\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 48,
|
||
"id": "1453f7ae-6bec-4cc7-9190-d0703412cafb",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x600 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_ngrams_grid(df_surnames.rename(columns={'surname': 'name'}), n=4, top_k=20, gender_col=\"sex\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 49,
|
||
"id": "801a36c0-cf28-47ad-8e79-63726bc2ac03",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1800x600 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_ngrams_grid(df_surnames.rename(columns={'surname': 'name'}), n=5, top_k=20, gender_col=\"sex\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "4a6dfe90-84d0-43c7-aea3-8646ae677ae7",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Surname generation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 50,
|
||
"id": "8b2185c5-474f-4181-a0ed-d01e4c986cfd",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"P = prepare_prob_matrix(transitions_male['df_probs'], tokens)\n",
|
||
"generated_firstnames = [generate_name(P, token_to_idx, idx_to_token, min_len=5, max_len=12, temperature=0.5) for _ in range(10)]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 51,
|
||
"id": "97d8f2c6-763f-498c-8b71-e762c7cbac6f",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"['Jonain',\n",
|
||
" 'Jachatier',\n",
|
||
" 'Anuel',\n",
|
||
" 'Serise',\n",
|
||
" 'Belphache',\n",
|
||
" 'Moninn',\n",
|
||
" 'Beloe',\n",
|
||
" 'Daman',\n",
|
||
" 'Jenis',\n",
|
||
" 'Delel']"
|
||
]
|
||
},
|
||
"execution_count": 51,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"generated_firstnames"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "597b151d-bdfe-4a6a-84ae-c9c9036f29e2",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.12.3"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|