DataScienceEcosystem.ipynb

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   "source": [
    "# Data Science Tools and Ecosystem"
   ]
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  {
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   "metadata": {},
   "source": [
    "## In this notebook, Data Science Tools and Ecosystem are summarized."
   ]
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   "source": [
    "# **Objectives:**"
   ]
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   "source": [
    "## List popular languages for Data Science\n",
    "- R\n",
    "- Python\n",
    "- Scala\n"
   ]
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    "## Some of the popular languages that Data Scientists use are:\n",
    "## 1. Python\n",
    "## 2. R\n",
    "## 3. Julia\n",
    "## 4. R"
   ]
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   "source": [
    "## Some of the commonly used libraries used by Data Scientists include:\n",
    "## 1. ggplot\n",
    "## 2. Pandas \n",
    "## 3. NumPy\n",
    "## 4. dplyr"
   ]
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   "source": [
    "\n",
    "| Data Science Tools |\n",
    "|--------------------|\n",
    "| VS Code            |\n",
    "| JupytherLab        |  \n",
    "| Google Collab      |\n"
   ]
  },
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   "source": [
    "### Below are a few examples of evaluating arithmetic expressions in Python"
   ]
  },
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   "source": [
    "#This a simple arithmetic expression to mutiply then add integers\n",
    "(3*4)+5"
   ]
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       "3.3333333333333335"
      ]
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     "execution_count": 3,
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   ],
   "source": [
    "#This will convert 200 minutes to hours by diving by 60\n",
    "200/60"
   ]
  },
  {
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   "id": "7d827092",
   "metadata": {},
   "source": [
    "## Author \n",
    "Adama NAON\n"
   ]
  },
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