DataScienceEcosystem.ipynb

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   "source": [
    "# Data Science Tools and Ecosystem"
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    "In this notebook, Data Science Tools and Ecosystems are summarized."
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    "**Objectives**:\n",
    "* List of popular languages for Data Science\n",
    "* List of commonly used libraries from Data Scientists\n",
    "* List of Data Science Tools as Development Environment\n",
    "* Examples of arithmetic expression in Python"
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    "Some of the popular languages that Data Scientists use are:\n",
    "1. Python\n",
    "2. R\n",
    "3. SQL\n",
    "4. Julia\n",
    "5. Java\n",
    "6. Java Script\n",
    "7. Scala\n",
    "8. C++"
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    "Some of the commonly used libraries used by Data Scientists include:\n",
    "1. Matplotlib\n",
    "2. Numpy\n",
    "3. Pandas\n",
    "4. ggplot"
   ]
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   "source": [
    "|Data Science Tools|\n",
    "|-------------------|\n",
    "|Jupyter (Notebook, Labs)|\n",
    "|R Studio|\n",
    "|Apache Zeppellin|"
   ]
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    "### Below are a few examples of evaluating arithmetic expressions in Python"
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   "source": [
    "# This is a simple arithmetic expression to multiply then add integers\n",
    "(3*4)+5"
   ]
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       "3.3333333333333335"
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   "source": [
    "# This will convert 200 minutes to hours by diving by 60\n",
    "200/60"
   ]
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   "metadata": {},
   "source": [
    "## Author\n",
    "Ronny Hoffmann"
   ]
  }
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