mirror of
https://github.com/beak-insights/felicity-lims.git
synced 2025-02-23 00:12:54 +08:00
299 lines
5.4 KiB
Text
299 lines
5.4 KiB
Text
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 40,
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"metadata": {},
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"outputs": [],
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"source": [
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"class Dog:\n",
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" name = \"penny\"\n",
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"\n",
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"dog = Dog()\n",
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"\n",
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"\n",
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"class Person(object):\n",
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" name = \"donald\"\n",
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" username = \"miguire\"\n",
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" age = 23\n",
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" pet = dog\n",
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" \n",
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" def access(self, attr):\n",
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" return getattr(self, attr)\n",
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" \n",
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" def really(self, attr):\n",
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" if getattr(self, attr) < 10:\n",
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" print(\"Hello youngster\")\n",
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" else:\n",
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" print(\"Khulu\")\n",
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" \n",
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" def pet_name(self):\n",
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" return getattr(getattr(self, 'pet'), 'name')"
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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": 41,
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"metadata": {},
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"outputs": [],
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"source": [
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"p = Person()"
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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": 42,
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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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"23"
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]
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},
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"execution_count": 42,
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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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"p.access(\"age\")"
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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": 43,
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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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"'donald'"
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]
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},
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"execution_count": 43,
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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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"p.access(\"name\")"
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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": 44,
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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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"'miguire'"
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]
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},
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"execution_count": 44,
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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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"p.access(\"username\")"
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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": 45,
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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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"Khulu\n"
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]
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}
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],
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"source": [
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"p.really(\"age\")"
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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": 46,
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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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"'penny'"
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]
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},
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"execution_count": 46,
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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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"p.pet.name"
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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": 47,
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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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"'penny'"
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]
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},
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"execution_count": 47,
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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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"p.pet_name()"
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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": 48,
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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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"{'user_type': 55}"
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]
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},
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"execution_count": 48,
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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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"{**{ 'user_type':444 }, **{ 'user_type': 55 }}"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 55,
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"metadata": {},
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"outputs": [],
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"source": [
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"h = {\n",
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" 'hu': \"hh\",\n",
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" 'hg': \"ht\",\n",
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" 'hz': \"hy\",\n",
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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": 61,
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"metadata": {},
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"outputs": [
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{
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"ename": "KeyError",
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"evalue": "'09'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-61-941db0b68224>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mh\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'09'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
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"\u001b[0;31mKeyError\u001b[0m: '09'"
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]
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}
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],
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"source": [
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"h['09']"
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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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"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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"True"
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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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"source": [
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"isinstance(0, int)"
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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": 64,
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"metadata": {},
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"outputs": [],
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"source": [
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"genders = [\"Male\", \"Female\", \"Missing\", \"Trans Gender\"]"
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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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"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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"'Trans Gender'"
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]
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},
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"execution_count": 69,
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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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"genders[3]"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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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": "3.8.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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