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Data Types.ipynb

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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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"# Data Types"
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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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"* Int - numerical and non decimal values\n",
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"* Float - Decimal values\n",
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"* Bool - Boolean (true or false)\n",
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"* Str - Strings"
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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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"source": [
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"x= 1\n",
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"y = 'Hello'\n",
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"z= 1.5\n",
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"A= True"
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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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"<class 'int'>\n",
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"<class 'str'>\n",
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"<class 'float'>\n",
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"<class 'bool'>\n"
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]
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}
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],
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"source": [
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"print(type(x))\n",
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"print(type(y))\n",
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"print(type(z))\n",
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"print(type(A))"
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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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"we us function **type()** for getting the data types of the objects"
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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": "3.6.4"
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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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