tutorial_pandas.ipynb

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   "source": [
    "# Tutorial: Pandas"
   ]
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   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/insop/ML_crash_course/blob/main/tutorial_pandas.ipynb)"
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    "[Pandas](https://pandas.pydata.org/) is python library for handling structured data, such as `csv` file input. We will review some of the basics of Pandas usage in this notebook."
   ]
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   "source": [
    "We will use covid case from Italy for this tutorial."
   ]
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   "source": [
    "# load csv file and save locally\n",
    "from urllib.request import urlretrieve\n",
    "\n",
    "italy_covid_url = 'https://gist.githubusercontent.com/aakashns/f6a004fa20c84fec53262f9a8bfee775/raw/f309558b1cf5103424cef58e2ecb8704dcd4d74c/italy-covid-daywise.csv'\n",
    "\n",
    "urlretrieve(italy_covid_url, 'italy-covid-daywise.csv')"
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  {
   "cell_type": "code",
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   "id": "1b8ba632",
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   "source": [
    "# import pandas\n",
    "import pandas as pd\n",
    "\n",
    "# load as pandas 'dataframe'\n",
    "covid_df = pd.read_csv('italy-covid-daywise.csv')"
   ]
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    "# check the loaded data\n",
    "\n",
    "covid_df"
   ]
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   "source": [
    "# check the statistical summary, max, min, average...\n",
    "covid_df.describe()"
   ]
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   "source": [
    "# handling column\n",
    "covid_df[\"new_cases\"] # or covid_df.new_cases"
   ]
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   "source": [
    "# handling row\n",
    "covid_df.loc[247]"
   ]
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   "source": [
    "# create a new data frame\n",
    "\n",
    "cases_df = covid_df[['date', 'new_cases']]\n",
    "cases_df"
   ]
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   "cell_type": "code",
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   "id": "4b0c42a4",
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   "source": [
    "# querying\n",
    "\n",
    "high_new_cases = covid_df.new_cases > 1000\n",
    "covid_df[high_new_cases] # or covid_df[covid_df.new_cases > 1000] "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7cde082",
   "metadata": {},
   "source": [
    "## Credits\n",
    "\n",
    "This notebook is a condensed version of the excellent Pandas tutorial from Jovian.ai, [Pandas tutorial from Jovian](https://jovian.ai/learn/data-analysis-with-python-zero-to-pandas/lesson/lesson-4-analyzing-tabular-data-with-pandas)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3879cc37",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "- [Pandas tutorial from Jovian](https://jovian.ai/learn/data-analysis-with-python-zero-to-pandas/lesson/lesson-4-analyzing-tabular-data-with-pandas)"
   ]
  }
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