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update terms
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‎1_Basics/02.1_Python_Terms.ipynb

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@@ -35,12 +35,12 @@
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"\n",
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"In data analytics, an object is like a record in your spreadsheet. Each record can have multiple fields, such as job title, location, and salary.\n",
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"\n",
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"**Object**: A data record with fields.\n"
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"**Object**: A data record with fields; an instance of a class.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 69,
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"execution_count": 55,
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"id": "968ee59f",
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"metadata": {},
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"outputs": [
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"'Data Analyst'"
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]
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},
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"execution_count": 69,
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"execution_count": 55,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 70,
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"execution_count": 56,
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"id": "34181ac4",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"str"
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]
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},
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"execution_count": 56,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"type(\"Data Analyst\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 57,
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"id": "53b471a2",
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"metadata": {},
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"outputs": [
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"90000"
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]
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},
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"execution_count": 70,
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"execution_count": 57,
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"metadata": {},
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"output_type": "execute_result"
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}
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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": 58,
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"id": "4d55db87",
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"metadata": {},
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"outputs": [
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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": 59,
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"id": "aaa5da4b",
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"metadata": {},
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"outputs": [
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"str"
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]
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},
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"execution_count": 9,
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"execution_count": 59,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# this is a class string object\n",
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"# this is an instance of the `type` class\n",
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"str"
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]
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},
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"\n",
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"Think of a variable as a cell in an Excel spreadsheet. You can store data in it, like a number, text, or a formula.\n",
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"\n",
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"**Variable**: A named cell that references an object."
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"**Variable**: A defined name that references an object."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 60,
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"id": "0fb0d189",
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"metadata": {},
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"outputs": [],
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"source": [
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"job_title = \"Data Analyst\"\n",
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"job_location = \"United States\"\n",
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"job_salary = 90000"
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"job_salary = 90000\n",
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"my_print_function = print"
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]
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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": 61,
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"id": "5199770e",
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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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"Data Analyst 90000\n"
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]
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}
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],
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"source": [
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"my_print_function(job_title, job_salary)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 62,
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"id": "a03cbbf0",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(4594639152, 4594645744, 4593144944)"
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"(4528218160, 4528508112, 4457027104)"
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]
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},
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"execution_count": 3,
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"execution_count": 62,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# each variable has a unique identifier\n",
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"id(job_title), id(job_location), id(job_salary)"
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"id(job_title), id(job_salary), id(my_print_function),"
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]
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},
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{
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},
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{
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"cell_type": "code",
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"execution_count": 63,
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"id": "4b917379",
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"metadata": {},
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"outputs": [
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"'Data Analyst'"
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]
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},
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"execution_count": 63,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(4594639152, 4594639152)"
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"(4528218160, 4528218160)"
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]
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},
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"execution_count": 5,
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"execution_count": 64,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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"cell_type": "code",
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"execution_count": 65,
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"id": "a5aa7f31",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(4594562480, 4594554352)"
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"(4528619824, 4528440816)"
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]
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},
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"execution_count": 8,
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"execution_count": 65,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 66,
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"id": "2c21a898",
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"outputs": [
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},
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"cell_type": "code",
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"execution_count": 70,
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"outputs": [
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"__main__.JobPost"
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]
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"str"
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},
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"outputs": [
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"'Data Engineer'"
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"425000"
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"execution_count": 78,
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"id": "00414ac1",
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"outputs": [

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