fixed code not outputting mixed df

This commit is contained in:
Cameron Seamons 2025-12-23 20:53:25 -07:00
parent e0cef40f23
commit e4ccb2297e

View file

@ -2,7 +2,7 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 2,
"id": "58867898", "id": "58867898",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -11,39 +11,33 @@
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
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" Using cached pandas-2.3.3-cp310-cp310-win_amd64.whl.metadata (19 kB)\n", " Downloading pandas-2.3.3-cp310-cp310-win_amd64.whl.metadata (19 kB)\n",
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"Installing collected packages: pytz, tzdata, six, numpy, python-dateutil, pandas\n", "Installing collected packages: pytz, tzdata, six, numpy, python-dateutil, pandas\n",
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"Successfully installed numpy-2.2.6 pandas-2.3.3 python-dateutil-2.9.0.post0 pytz-2025.2 six-1.17.0 tzdata-2025.3\n", "Successfully installed numpy-2.2.6 pandas-2.3.3 python-dateutil-2.9.0.post0 pytz-2025.2 six-1.17.0 tzdata-2025.3\n",
"Note: you may need to restart the kernel to use updated packages.\n", "Note: you may need to restart the kernel to use updated packages.\n",
"Collecting faker\n", "Collecting faker\n",
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@ -241,7 +300,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 14, "execution_count": 3,
"id": "d786ab3d", "id": "d786ab3d",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -249,7 +308,7 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"c:\\Users\\leaf3\\OneDrive\\Desktop\\DataLab\\Data_lab\\fake_data\n" "c:\\Users\\leaf3\\Desktop\\Data Engineer\\datalab\\Data_Lab\\fake_data\n"
] ]
} }
], ],
@ -269,7 +328,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 6,
"id": "46f10552", "id": "46f10552",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -277,7 +336,9 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"Data Exported\n" "Saved files to:\n",
"c:\\Users\\leaf3\\Desktop\\Data Engineer\\datalab\\Data_Lab\\fake_data\\healthy_medical_records.csv\n",
"c:\\Users\\leaf3\\Desktop\\Data Engineer\\datalab\\Data_Lab\\fake_data\\mixed_medical_records.csv\n"
] ]
} }
], ],
@ -475,12 +536,292 @@
"for column in mixed_df.columns:\n", "for column in mixed_df.columns:\n",
" mixed_df.loc[healthy_mask, column] = healthy_df.loc[healthy_mask, column]\n", " mixed_df.loc[healthy_mask, column] = healthy_df.loc[healthy_mask, column]\n",
"\n", "\n",
"mixed_df = generate_dataset(is_healthy=False)\n", "mixed_df.to_csv(mixed_path, index=False)\n",
"\n", "\n",
"print(\"Saved files to:\")\n", "print(\"Saved files to:\")\n",
"print(healthy_path)\n", "print(healthy_path)\n",
"print(mixed_path)" "print(mixed_path)"
] ]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "0b9c67b5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Medical datasets combined and exported successfully.\n"
]
}
],
"source": [
"# Load the datasets\n",
"healthy_df = pd.read_csv('healthy_medical_records.csv')\n",
"mixed_df = pd.read_csv('mixed_medical_records.csv')\n",
"\n",
"# Concatenate the two DataFrames\n",
"output_df = pd.concat([healthy_df, mixed_df], ignore_index=True)\n",
"\n",
"output_df.fillna('None', inplace=True)\n",
"\n",
"# Export the final dataset to a CSV file\n",
"output_df.to_csv('sample_medical_records.csv', index=False)\n",
"\n",
"print(\"Medical datasets combined and exported successfully.\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "928bf039",
"metadata": {},
"outputs": [
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"text/plain": [
" Patient ID Last Checkup Date of Birth Gender Ethnicity \\\n",
"0 KP-6511-3073-2278 2024-05-28 1955-08-02 Female Pacific Islander \n",
"1 RK-1845-1516-4239 2023-05-29 1950-09-27 Male Asian \n",
"2 XA-8453-5992-5165 2025-09-28 1958-06-22 Male Other \n",
"3 LX-9887-6375-7280 2025-05-24 2005-02-21 Male Other \n",
"4 WM-9463-4744-1527 2023-06-19 1994-02-23 Male Native American \n",
"\n",
" Blood Type Occupation Insurance Provider \\\n",
"0 B+ Electrician Pugh, Tate and Green \n",
"1 O+ Nurse Gonzalez-Martinez \n",
"2 O- Engineer Kim, Medina and Hawkins \n",
"3 B+ Customer Service Representative Rogers-Baker \n",
"4 O+ Student NaN \n",
"\n",
" Insurance Plan Monthly Premium ... Stroke \\\n",
"0 Comprehensive Care Plan 722.18 ... No \n",
"1 Family Health Coverage 610.27 ... No \n",
"2 High Deductible Health Plan 652.52 ... No \n",
"3 Premium Health Insurance 290.39 ... No \n",
"4 Individual Health Insurance 257.43 ... No \n",
"\n",
" Coronary Heart Disease (CHD) Blood Glucose Level (mmol/L) \\\n",
"0 No 5.0 \n",
"1 No 5.0 \n",
"2 No 4.2 \n",
"3 No 5.1 \n",
"4 No 4.7 \n",
"\n",
" HDL Cholesterol (mmol/L) LDL Cholesterol (mmol/L) Triglycerides (mmol/L) \\\n",
"0 1.4 2.7 1.4 \n",
"1 1.3 2.2 0.7 \n",
"2 1.3 2.9 1.3 \n",
"3 1.6 2.1 0.7 \n",
"4 1.4 2.7 1.2 \n",
"\n",
" Hemoglobin A1C (%) White Blood Cell Count (10^9/L) \\\n",
"0 5.4 9.1 \n",
"1 5.0 5.1 \n",
"2 4.2 5.8 \n",
"3 4.4 10.7 \n",
"4 4.3 5.3 \n",
"\n",
" Red Blood Cell Count (10^12/L) Platelet Count (10^9/L) \n",
"0 4.8 310.5 \n",
"1 4.6 226.1 \n",
"2 4.7 274.4 \n",
"3 4.6 154.0 \n",
"4 4.9 273.1 \n",
"\n",
"[5 rows x 29 columns]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_csv('sample_medical_records.csv')\n",
"\n",
"\n",
"\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "899a271c",
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {