2024-05-08 17:45:29 +02:00
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Reading SB\n",
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"Length of SB: 16559\n",
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"Reading AFIB\n",
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"Length of AFIB: 9839\n",
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"Reading GSVT\n",
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"Length of GSVT: 948\n",
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"Reading SR\n",
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"Length of SR: 9720\n"
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]
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}
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],
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"source": [
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"import pickle\n",
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"from matplotlib import pyplot as plt\n",
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"import wfdb\n",
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"# read pickle files and check len and print first record and first record keys\n",
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"\n",
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"path = \"C:/Studium/dsa/data\"\n",
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"#path = \"C:/Users/Nils/Documents/HS-Mannheim/0000_MASTER/DSA/EKG_Prog/data\"\n",
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"\n",
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"categories_dict = {\n",
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"'SB': [426177001],\n",
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"'AFIB': [164889003, 164890007],\n",
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"'GSVT': [426761007, 713422000, 233896004, 233897008, 713422000],\n",
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"'SR': [426783006, 427393009]\n",
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"}\n",
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"\n",
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"\n",
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"data = {}\n",
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"for cat_name in categories_dict.keys():\n",
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" print(f\"Reading {cat_name}\")\n",
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" with open(f'{path}/{cat_name}.pkl', 'rb') as f:\n",
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" records = pickle.load(f)\n",
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" data[cat_name] = records\n",
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" print(f\"Length of {cat_name}: {len(records)}\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Check for missing data in timeseries"
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]
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},
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{
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"cell_type": "code",
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2024-05-12 13:31:54 +02:00
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"execution_count": 12,
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2024-05-08 17:45:29 +02:00
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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2024-05-12 13:31:54 +02:00
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"First record in SB: ['Age: 59', 'Sex: Female', 'Dx: 426177001,164934002', 'Rx: Unknown', 'Hx: Unknown', 'Sx: Unknown']\n",
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"Missing sex in JS34080 and comments: Sex: Unknown\n",
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"Missing age in JS12543 and comments: Age: NaN\n",
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"Missing age in JS12571 and comments: Age: NaN\n",
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"Missing age in JS12576 and comments: Age: NaN\n",
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"Missing sex in JS12576 and comments: Sex: Unknown\n",
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"Missing age in JS12609 and comments: Age: NaN\n",
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"Missing sex in JS12609 and comments: Sex: Unknown\n",
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"Missing age in JS13024 and comments: Age: NaN\n",
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"Missing sex in JS13024 and comments: Sex: Unknown\n",
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"Missing age in JS13504 and comments: Age: NaN\n",
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"Missing age in JS13505 and comments: Age: NaN\n",
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"Missing age in JS13575 and comments: Age: NaN\n",
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"Missing age in JS13583 and comments: Age: NaN\n",
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"Missing age in JS13645 and comments: Age: NaN\n",
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"Missing age in JS13646 and comments: Age: NaN\n",
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"Missing age in JS13647 and comments: Age: NaN\n",
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"Missing age in JS14027 and comments: Age: NaN\n",
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"Missing age in JS14050 and comments: Age: NaN\n",
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"Missing age in JS14498 and comments: Age: NaN\n",
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"Missing age in JS14555 and comments: Age: NaN\n",
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"Missing age in JS14995 and comments: Age: NaN\n",
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"Missing sex in JS14995 and comments: Sex: Unknown\n",
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"Missing age in JS18505 and comments: Age: NaN\n",
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"Missing age in JS18506 and comments: Age: NaN\n",
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"Missing age in JS18507 and comments: Age: NaN\n",
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"Missing age in JS18508 and comments: Age: NaN\n",
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"Missing age in JS18509 and comments: Age: NaN\n",
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"Missing age in JS18510 and comments: Age: NaN\n",
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"Missing age in JS18511 and comments: Age: NaN\n",
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"Missing age in JS18512 and comments: Age: NaN\n",
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"Missing age in JS18513 and comments: Age: NaN\n",
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"Missing age in JS18514 and comments: Age: NaN\n",
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"Missing age in JS18515 and comments: Age: NaN\n",
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"Missing sex in JS18515 and comments: Sex: Unknown\n",
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"Missing age in JS18574 and comments: Age: NaN\n",
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"Missing age in JS19386 and comments: Age: NaN\n",
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"Missing age in JS19447 and comments: Age: NaN\n",
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"Missing age in JS10867 and comments: Age: NaN\n",
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"Missing sex in JS10867 and comments: Sex: Unknown\n",
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"Missing age in JS11507 and comments: Age: NaN\n",
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"Missing sex in JS11507 and comments: Sex: Unknown\n",
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"Missing age in JS22918 and comments: Age: NaN\n",
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"Missing sex in JS22918 and comments: Sex: Unknown\n",
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"Missing age in JS23063 and comments: Age: NaN\n",
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"Missing sex in JS23063 and comments: Sex: Unknown\n",
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"Missing age in JS23064 and comments: Age: NaN\n",
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"Missing age in JS23787 and comments: Age: NaN\n",
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"Missing sex in JS23787 and comments: Sex: Unknown\n",
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"Missing age in JS24143 and comments: Age: NaN\n",
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"Missing sex in JS24143 and comments: Sex: Unknown\n",
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"Missing age in JS24144 and comments: Age: NaN\n",
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"Missing sex in JS24144 and comments: Sex: Unknown\n",
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"Missing age in JS24145 and comments: Age: NaN\n",
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"Missing age in JS45355 and comments: Age: NaN\n",
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"Missing age in JS45356 and comments: Age: NaN\n",
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"Missing age in JS45357 and comments: Age: NaN\n",
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"Missing age in JS45358 and comments: Age: NaN\n",
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"Missing age in JS45359 and comments: Age: NaN\n",
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"Missing age in JS45360 and comments: Age: NaN\n",
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"Missing sex in JS45360 and comments: Sex: Unknown\n",
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"Missing age in JS45361 and comments: Age: NaN\n",
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"Missing sex in JS45361 and comments: Sex: Unknown\n",
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"Missing age in JS45364 and comments: Age: NaN\n",
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"Missing age in JS45367 and comments: Age: NaN\n",
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"Missing sex in JS45367 and comments: Sex: Unknown\n",
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"Missing age in JS45369 and comments: Age: NaN\n",
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"Missing age in JS45370 and comments: Age: NaN\n",
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"Missing sex in JS45370 and comments: Sex: Unknown\n",
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"Missing age in JS45382 and comments: Age: NaN\n",
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"Missing sex in JS45382 and comments: Sex: Unknown\n",
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"Missing age in JS45383 and comments: Age: NaN\n",
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"Missing sex in JS45383 and comments: Sex: Unknown\n",
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"Missing age in JS45384 and comments: Age: NaN\n",
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"Missing sex in JS45384 and comments: Sex: Unknown\n",
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"Missing age in JS45385 and comments: Age: NaN\n",
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"Missing sex in JS45385 and comments: Sex: Unknown\n",
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"Missing timeseries in 0 records\n",
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"Missing age in 55 records\n",
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"Missing sex in 21 records\n"
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2024-05-08 17:45:29 +02:00
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]
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}
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],
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"source": [
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2024-05-12 13:31:54 +02:00
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"# print first record and first record keys\n",
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"print(f\"First record in SB: {data['SB'][0].comments}\")\n",
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"\n",
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2024-05-08 17:45:29 +02:00
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"missing_timeseries = []\n",
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2024-05-12 13:31:54 +02:00
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"missing_age = []\n",
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"missing_sex = []\n",
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2024-05-08 17:45:29 +02:00
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"for cat_name, records in data.items():\n",
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" for record in records:\n",
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" if len(record.p_signal) != 5000:\n",
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" missing_timeseries.append(record)\n",
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" print(f\"Missing timeseries in {record.record_name}\")\n",
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" #if record.comments[2]== '':\n",
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2024-05-12 13:31:54 +02:00
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" if 'Age: ' not in record.comments[0] or record.comments[0] == 'Age: NaN':\n",
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" missing_age.append(record)\n",
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" print(f\"Missing age in {record.record_name} and comments: {record.comments[0]}\")\n",
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" if record.comments[1] == 'Sex: Unknown' or record.comments[1] == '':\n",
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" missing_sex.append(record)\n",
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" print(f\"Missing sex in {record.record_name} and comments: {record.comments[1]}\")\n",
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" \n",
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"print(f\"Missing timeseries in {len(missing_timeseries)} records\")\n",
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"print(f\"Missing age in {len(missing_age)} records\")\n",
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"print(f\"Missing sex in {len(missing_sex)} records\")"
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2024-05-08 17:45:29 +02:00
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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