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+{
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+ "cells": [
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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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+ "# Project: Jupyter Notebook\n",
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+ "\n",
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+ "## 2. Running Code"
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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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+ "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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+ "Hello, Jupyter!\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "welcome_message = 'Hello, Jupyter!'\n",
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+ "first_cell = True\n",
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+ "\n",
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+ "if first_cell:\n",
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+ " print(welcome_message)"
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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": 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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+ "240.0\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "result = 1200 / 5\n",
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+ "second_cell = True\n",
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+ "\n",
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+ "if second_cell:\n",
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+ " print(result)"
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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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+ "## 3. Running Code Using the Keyboard"
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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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+ "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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+ "Hello, Jupyter!\n",
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+ "First cell\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "### Shift + Enter; then Alt + Enter ###\n",
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+ "\n",
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+ "welcome_message = 'Hello, Jupyter!'\n",
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+ "first_cell = True\n",
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+ "\n",
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+ "if first_cell:\n",
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+ " print(welcome_message)\n",
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+ " \n",
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+ "print('First cell')"
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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": 4,
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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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+ "Second cell\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "### Ctrl + Enter ###\n",
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+ "\n",
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+ "print('Second cell')"
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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": 5,
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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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+ "240.0\n",
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+ "Third cell\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "### Ctrl + Enter ###\n",
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+ "\n",
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+ "result = 1200 / 5\n",
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+ "second_cell = True\n",
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+ "\n",
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+ "if second_cell:\n",
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+ " print(result)\n",
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+ " \n",
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+ "print('Third cell')"
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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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+ "## 4. Keyboard Shortcuts"
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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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+ "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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+ "Hello, Jupyter!\n",
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+ "First cell\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "welcome_message = 'Hello, Jupyter!'\n",
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+ "first_cell = True\n",
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+ "\n",
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+ "if first_cell:\n",
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+ " print(welcome_message)\n",
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+ " \n",
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+ "print('First cell')"
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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": 7,
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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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+ "240.0\n",
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+ "Second cell\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "result = 1200 / 5\n",
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+ "second_cell = True\n",
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+ "\n",
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+ "if second_cell:\n",
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+ " print(result)\n",
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+ " \n",
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+ "print('Second cell')"
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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": 8,
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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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+ "A true third cell\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "print('A true third cell')"
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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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+ "## 5. State"
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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": 9,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "def welcome(a_string):\n",
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+ " print('Welcome to ' + a_string + '!')\n",
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+ " \n",
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+ "dq = 'Dataquest'\n",
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+ "jn = 'Jupyter Notebook'\n",
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+ "py = 'Python'"
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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": 10,
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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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+ "Welcome to Dataquest!\n",
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+ "Welcome to Jupyter Notebook!\n",
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+ "Welcome to Python!\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "welcome(dq)\n",
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+ "welcome(jn)\n",
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+ "welcome(py)"
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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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+ "## 6. Hidden State"
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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": 11,
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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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+ ">>> welcome_message = 'Hello, Jupyter!'\n",
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+ "... first_cell = True\n",
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+ "... \n",
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+ "... if first_cell:\n",
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+ "... print(welcome_message)\n",
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+ "...\n",
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+ ">>> result = 1200 / 5\n",
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+ "... second_cell = True\n",
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+ "... \n",
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+ "... if second_cell:\n",
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+ "... print(result)\n",
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+ "...\n",
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+ ">>> ### Shift + Enter; then Alt + Enter ###\n",
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+ "... \n",
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+ "... welcome_message = 'Hello, Jupyter!'\n",
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+ "... first_cell = True\n",
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+ "... \n",
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+ "... if first_cell:\n",
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+ "... print(welcome_message)\n",
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+ "... \n",
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+ "... print('First cell')\n",
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+ "...\n",
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+ ">>> ### Ctrl + Enter ###\n",
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+ "... \n",
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+ "... print('Second cell')\n",
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+ "...\n",
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+ ">>> ### Ctrl + Enter ###\n",
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+ "... \n",
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+ "... result = 1200 / 5\n",
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+ "... second_cell = True\n",
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+ "... \n",
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+ "... if second_cell:\n",
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+ "... print(result)\n",
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+ "... \n",
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+ "... print('Third cell')\n",
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+ "...\n",
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+ ">>> welcome_message = 'Hello, Jupyter!'\n",
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+ "... first_cell = True\n",
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+ "... \n",
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+ "... if first_cell:\n",
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+ "... print(welcome_message)\n",
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+ "... \n",
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+ "... print('First cell')\n",
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+ "...\n",
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+ ">>> result = 1200 / 5\n",
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+ "... second_cell = True\n",
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+ "... \n",
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+ "... if second_cell:\n",
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+ "... print(result)\n",
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+ "... \n",
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+ "... print('Second cell')\n",
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+ "...\n",
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+ ">>> print('A true third cell')\n",
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+ ">>> def welcome(a_string):\n",
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+ "... print('Welcome to ' + a_string + '!')\n",
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+ "... \n",
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+ "... dq = 'Dataquest'\n",
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+ "... jn = 'Jupyter Notebook'\n",
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+ "... py = 'Python'\n",
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+ "...\n",
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+ ">>> welcome(dq)\n",
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+ "... welcome(jn)\n",
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+ "... welcome(py)\n",
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+ "...\n",
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+ ">>> %history -p\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "%history -p"
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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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+ "# Restart & Clear Output"
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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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+ "'''\n",
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+ "Note: To reproduce exactly the output in this notebook\n",
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+ "as whole:\n",
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+ "\n",
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+ "1. Run all the cells above.\n",
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+ "2. Restart the program's state but keep the output\n",
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+ "(click Restart Kernel).\n",
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+ "3. Then, run only the cells below.\n",
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+ "\n",
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+ "\n",
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+ "(You were not asked in this exercise to write a note like this.\n",
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+ "The note above was written to give more details on how to reproduce\n",
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+ "the behavior seen in this notebook.)\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": 1,
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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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+ ">>> %history -p\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "%history -p"
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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": 4,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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|
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+ "def welcome(a_string):\n",
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+ " welcome_msg = 'Welcome to ' + a_string + '!'\n",
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+ " return welcome_msg\n",
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+ "\n",
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+ "dq = 'Dataquest'\n",
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+ "jn = 'Jupyter Notebook'"
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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": 3,
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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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|
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+ "text": [
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|
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+ "Welcome to Dataquest!\n",
|
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|
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+ "Welcome to Jupyter Notebook!\n",
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+ "Welcome to Python!\n"
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|
+ ]
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|
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+ }
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|
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+ ],
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+ "source": [
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+ "welcome(dq)\n",
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+ "welcome(jn)\n",
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+ "welcome(py)"
|
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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": 5,
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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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|
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+ ">>> %history -p\n",
|
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|
|
+ ">>> def welcome(a_string):\n",
|
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|
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+ "... print('Welcome to ' + a_string + '!')\n",
|
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|
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+ "... \n",
|
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|
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+ "... dq = 'Dataquest'\n",
|
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|
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+ "... jn = 'Jupyter Notebook'\n",
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+ "... py = 'Python'\n",
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|
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+ "...\n",
|
|
|
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+ ">>> welcome(dq)\n",
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+ "... welcome(jn)\n",
|
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|
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+ "... welcome(py)\n",
|
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|
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+ "...\n",
|
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|
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+ ">>> def welcome(a_string):\n",
|
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|
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+ "... welcome_msg = 'Welcome to ' + a_string + '!'\n",
|
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|
|
+ "... return welcome_msg\n",
|
|
|
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+ "... \n",
|
|
|
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+ "... dq = 'Dataquest'\n",
|
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|
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+ "... jn = 'Jupyter Notebook'\n",
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|
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+ "...\n",
|
|
|
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+ ">>> %history -p\n"
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|
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+ ]
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+ }
|
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+ ],
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|
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+ "source": [
|
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|
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+ "%history -p"
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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": 6,
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+ "metadata": {},
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+ "outputs": [
|
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|
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+ {
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+ "data": {
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+ "text/plain": [
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+ "'Welcome to Python!'"
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|
|
+ ]
|
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|
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+ },
|
|
|
|
+ "execution_count": 6,
|
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|
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+ "metadata": {},
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|
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+ "output_type": "execute_result"
|
|
|
|
+ }
|
|
|
|
+ ],
|
|
|
|
+ "source": [
|
|
|
|
+ "welcome(dq)\n",
|
|
|
|
+ "welcome(jn)\n",
|
|
|
|
+ "welcome(py)"
|
|
|
|
+ ]
|
|
|
|
+ },
|
|
|
|
+ {
|
|
|
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+ "cell_type": "markdown",
|
|
|
|
+ "metadata": {},
|
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|
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+ "source": [
|
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|
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+ "## 7. Text and Markdown"
|
|
|
|
+ ]
|
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+ },
|
|
|
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+ {
|
|
|
|
+ "cell_type": "markdown",
|
|
|
|
+ "metadata": {},
|
|
|
|
+ "source": [
|
|
|
|
+ "In the code cell below, we:\n",
|
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|
+ "\n",
|
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|
|
+ "- Open the `AppleStore.csv` file using the `open()` function, and assign the output to a variable named `opened_file`\n",
|
|
|
|
+ "- Import the `reader()` function from the `csv` module\n",
|
|
|
|
+ "- Read in the opened file using the `reader()` function, and assign the output to a variable named `read_file`\n",
|
|
|
|
+ "- Transform the read-in file to a list of lists using `list()` and save it to a variable named `apps_data`\n",
|
|
|
|
+ "- Display the header row and the first three rows of the data set."
|
|
|
|
+ ]
|
|
|
|
+ },
|
|
|
|
+ {
|
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|
|
+ "cell_type": "code",
|
|
|
|
+ "execution_count": 7,
|
|
|
|
+ "metadata": {},
|
|
|
|
+ "outputs": [
|
|
|
|
+ {
|
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+ "data": {
|
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|
|
+ "text/plain": [
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|
|
+ "[['id',\n",
|
|
|
|
+ " 'track_name',\n",
|
|
|
|
+ " 'size_bytes',\n",
|
|
|
|
+ " 'currency',\n",
|
|
|
|
+ " 'price',\n",
|
|
|
|
+ " 'rating_count_tot',\n",
|
|
|
|
+ " 'rating_count_ver',\n",
|
|
|
|
+ " 'user_rating',\n",
|
|
|
|
+ " 'user_rating_ver',\n",
|
|
|
|
+ " 'ver',\n",
|
|
|
|
+ " 'cont_rating',\n",
|
|
|
|
+ " 'prime_genre',\n",
|
|
|
|
+ " 'sup_devices.num',\n",
|
|
|
|
+ " 'ipadSc_urls.num',\n",
|
|
|
|
+ " 'lang.num',\n",
|
|
|
|
+ " 'vpp_lic'],\n",
|
|
|
|
+ " ['284882215',\n",
|
|
|
|
+ " 'Facebook',\n",
|
|
|
|
+ " '389879808',\n",
|
|
|
|
+ " 'USD',\n",
|
|
|
|
+ " '0.0',\n",
|
|
|
|
+ " '2974676',\n",
|
|
|
|
+ " '212',\n",
|
|
|
|
+ " '3.5',\n",
|
|
|
|
+ " '3.5',\n",
|
|
|
|
+ " '95.0',\n",
|
|
|
|
+ " '4+',\n",
|
|
|
|
+ " 'Social Networking',\n",
|
|
|
|
+ " '37',\n",
|
|
|
|
+ " '1',\n",
|
|
|
|
+ " '29',\n",
|
|
|
|
+ " '1'],\n",
|
|
|
|
+ " ['389801252',\n",
|
|
|
|
+ " 'Instagram',\n",
|
|
|
|
+ " '113954816',\n",
|
|
|
|
+ " 'USD',\n",
|
|
|
|
+ " '0.0',\n",
|
|
|
|
+ " '2161558',\n",
|
|
|
|
+ " '1289',\n",
|
|
|
|
+ " '4.5',\n",
|
|
|
|
+ " '4.0',\n",
|
|
|
|
+ " '10.23',\n",
|
|
|
|
+ " '12+',\n",
|
|
|
|
+ " 'Photo & Video',\n",
|
|
|
|
+ " '37',\n",
|
|
|
|
+ " '0',\n",
|
|
|
|
+ " '29',\n",
|
|
|
|
+ " '1'],\n",
|
|
|
|
+ " ['529479190',\n",
|
|
|
|
+ " 'Clash of Clans',\n",
|
|
|
|
+ " '116476928',\n",
|
|
|
|
+ " 'USD',\n",
|
|
|
|
+ " '0.0',\n",
|
|
|
|
+ " '2130805',\n",
|
|
|
|
+ " '579',\n",
|
|
|
|
+ " '4.5',\n",
|
|
|
|
+ " '4.5',\n",
|
|
|
|
+ " '9.24.12',\n",
|
|
|
|
+ " '9+',\n",
|
|
|
|
+ " 'Games',\n",
|
|
|
|
+ " '38',\n",
|
|
|
|
+ " '5',\n",
|
|
|
|
+ " '18',\n",
|
|
|
|
+ " '1']]"
|
|
|
|
+ ]
|
|
|
|
+ },
|
|
|
|
+ "execution_count": 7,
|
|
|
|
+ "metadata": {},
|
|
|
|
+ "output_type": "execute_result"
|
|
|
|
+ }
|
|
|
|
+ ],
|
|
|
|
+ "source": [
|
|
|
|
+ "opened_file = open('AppleStore.csv')\n",
|
|
|
|
+ "from csv import reader\n",
|
|
|
|
+ "read_file = reader(opened_file)\n",
|
|
|
|
+ "apps_data = list(read_file)\n",
|
|
|
|
+ "\n",
|
|
|
|
+ "apps_data[:4]"
|
|
|
|
+ ]
|
|
|
|
+ },
|
|
|
|
+ {
|
|
|
|
+ "cell_type": "markdown",
|
|
|
|
+ "metadata": {},
|
|
|
|
+ "source": [
|
|
|
|
+ "The data set above contains information about more than 7000 Apple iOS mobile apps. The data was collected from the iTunes Search API by data engineer [Ramanathan Perumal](https://www.kaggle.com/ramamet4). Documentation for the data set can be found [at this page](https://www.kaggle.com/ramamet4/app-store-apple-data-set-10k-apps/home), where you'll also be able to download the data set.\n",
|
|
|
|
+ "\n",
|
|
|
|
+ "This is a table explaining what each column in the data set describes:\n",
|
|
|
|
+ "\n",
|
|
|
|
+ "Column name | Description\n",
|
|
|
|
+ "-- | --\n",
|
|
|
|
+ "\"id\" | App ID\n",
|
|
|
|
+ "\"track_name\"| App Name\n",
|
|
|
|
+ "\"size_bytes\"| Size (in Bytes)\n",
|
|
|
|
+ "\"currency\"| Currency Type\n",
|
|
|
|
+ "\"price\"| Price amount\n",
|
|
|
|
+ "\"rating_count_tot\"| User Rating counts (for all version)\n",
|
|
|
|
+ "\"rating_count_ver\"| User Rating counts (for current version)\n",
|
|
|
|
+ "\"user_rating\" | Average User Rating value (for all version)\n",
|
|
|
|
+ "\"user_rating_ver\"| Average User Rating value (for current version)\n",
|
|
|
|
+ "\"ver\" | Latest version code\n",
|
|
|
|
+ "\"cont_rating\"| Content Rating\n",
|
|
|
|
+ "\"prime_genre\"| Primary Genre\n",
|
|
|
|
+ "\"sup_devices.num\"| Number of supporting devices\n",
|
|
|
|
+ "\"ipadSc_urls.num\"| Number of screenshots showed for display\n",
|
|
|
|
+ "\"lang.num\"| Number of supported languages\n",
|
|
|
|
+ "\"vpp_lic\"| Vpp Device Based Licensing Enabled"
|
|
|
|
+ ]
|
|
|
|
+ }
|
|
|
|
+ ],
|
|
|
|
+ "metadata": {
|
|
|
|
+ "kernelspec": {
|
|
|
|
+ "display_name": "Python 3",
|
|
|
|
+ "language": "python",
|
|
|
|
+ "name": "python3"
|
|
|
|
+ },
|
|
|
|
+ "language_info": {
|
|
|
|
+ "codemirror_mode": {
|
|
|
|
+ "name": "ipython",
|
|
|
|
+ "version": 3
|
|
|
|
+ },
|
|
|
|
+ "file_extension": ".py",
|
|
|
|
+ "mimetype": "text/x-python",
|
|
|
|
+ "name": "python",
|
|
|
|
+ "nbconvert_exporter": "python",
|
|
|
|
+ "pygments_lexer": "ipython3",
|
|
|
|
+ "version": "3.6.4"
|
|
|
|
+ }
|
|
|
|
+ },
|
|
|
|
+ "nbformat": 4,
|
|
|
|
+ "nbformat_minor": 2
|
|
|
|
+}
|