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index.ipynb

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@@ -20,7 +20,7 @@
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"source": [
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"In the past few lessons, we have learned about working with different types of data in Python: strings, numbers (ints and floats), and booleans. Now let's put that knowledge into action.\n",
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"\n",
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"In this lesson we'll imagine that just met Art Vandelay, a CEO of his own travel agency, Vandelay Industries. He gave us his business card, and we would like to use our knowledge of strings to format his information properly before we file it away."
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"In this lesson we'll imagine that at a nice social gathering you exchanged business cards with a few people. One of the business cards belongs to Art Vandelay, a new travel agent. You want to use your programming skills to format this information correctly. "
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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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"Yea, he may not be our first choice, but we said he'd give us a discount so we move ahead. Plus his poor formatting on his card will give us practice with strings. \n",
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"Yea, he may not be the best person to get to know. But we know that when people fill out forms, they misenter information all of the time.\n",
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"\n",
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"And we know that a lot of information online is mistyped. Just think of when all the times people misenter information on forms. So let's get to work."
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"So as data scientists, we often need to clean and organize data to then make sense of it. Let's get to work. "
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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": null,
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"metadata": {},
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"outputs": [],
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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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"data": {
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"text/plain": [
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"'art.vandelay@vandelay.co'"
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]
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},
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"execution_count": 1,
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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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"\"art.vandelay@vandelay.co\" # False"
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]

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