Good good progress
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-22
@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 21,
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"id": "63f43af5",
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"metadata": {},
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"outputs": [],
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@@ -16,7 +16,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 22,
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"id": "97da3d1c",
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"metadata": {},
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"outputs": [],
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@@ -26,7 +26,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 23,
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"id": "b0ee2af1",
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"metadata": {},
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"outputs": [
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@@ -42,7 +42,7 @@
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/tmp/ipykernel_103354/3076306744.py:3: FutureWarning: errors='ignore' is deprecated and will raise in a future version. Use to_numeric without passing `errors` and catch exceptions explicitly instead\n",
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"/tmp/ipykernel_150441/3076306744.py:3: FutureWarning: errors='ignore' is deprecated and will raise in a future version. Use to_numeric without passing `errors` and catch exceptions explicitly instead\n",
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" df = df.apply(pd.to_numeric, errors='ignore')\n"
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]
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}
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@@ -72,7 +72,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 24,
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"id": "99116a35",
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"metadata": {},
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"outputs": [],
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@@ -84,7 +84,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 25,
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"id": "fbd292c3",
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"metadata": {},
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"outputs": [
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@@ -102,7 +102,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 26,
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"id": "4c439b2c",
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"metadata": {},
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"outputs": [
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@@ -167,7 +167,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 27,
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"id": "a565f1b3",
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"metadata": {},
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"outputs": [
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@@ -237,7 +237,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 28,
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"id": "470e871e",
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"metadata": {},
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"outputs": [
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@@ -431,7 +431,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 29,
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"id": "0ab6f0b0",
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"metadata": {},
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"outputs": [
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@@ -577,7 +577,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 30,
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"id": "ef8bc7ac",
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"metadata": {},
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"outputs": [
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@@ -638,7 +638,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 31,
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"id": "06244aa2",
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"metadata": {},
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"outputs": [
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@@ -753,7 +753,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 32,
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"id": "8a1878a0",
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"metadata": {},
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"outputs": [
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@@ -832,7 +832,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 33,
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"id": "7361fb05",
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"metadata": {},
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"outputs": [
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@@ -893,7 +893,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 34,
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"id": "c89478ff",
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"metadata": {},
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"outputs": [
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@@ -953,7 +953,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 35,
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"id": "1db16040",
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"metadata": {},
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"outputs": [
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@@ -1028,7 +1028,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 36,
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"id": "c8ad6076",
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"metadata": {},
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"outputs": [
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@@ -1109,7 +1109,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": 37,
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"id": "25327cc1",
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"metadata": {},
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"outputs": [
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@@ -1415,7 +1415,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"execution_count": 38,
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"id": "c46b53f0",
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"metadata": {},
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"outputs": [
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@@ -1731,7 +1731,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 39,
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"id": "84addc63",
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"metadata": {},
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"outputs": [
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@@ -1869,7 +1869,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"execution_count": 40,
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"id": "f324fe94",
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"metadata": {},
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"outputs": [
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@@ -2066,7 +2066,7 @@
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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"display_name": "report-generation",
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"language": "python",
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"name": "python3"
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},
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