4_more_pandas.ipynb

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   "source": [
    "# CSV in Pandas\n",
    "* What's a CSV?\n",
    "* let's take a look at something"
   ]
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   "source": [
    "!cat datasets/Admission_Predict.csv"
   ]
  },
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   "execution_count": null,
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   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('datasets/Admission_Predict.csv')\n",
    "# And let's look at the first few rows\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "# lots of great docs for read_csv\n",
    "pd.read_csv??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
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   "outputs": [],
   "source": [
    "df = pd.read_csv('datasets/Admission_Predict.csv', index_col=0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
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   },
   "source": [
    "* Let's update some of those column names, this can be done with `df.rename`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "new_df=df.rename(columns={'GRE Score':'GRE Score', 'TOEFL Score':'TOEFL Score',\n",
    "                   'University Rating':'University Rating', \n",
    "                   'SOP': 'Statement of Purpose','LOR': 'Letter of Recommendation',\n",
    "                   'CGPA':'CGPA', 'Research':'Research',\n",
    "                   'Chance of Admit':'Chance of Admit'})\n",
    "new_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "* wait, why didn't LOR change too?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
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   },
   "outputs": [],
   "source": [
    "new_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "slideshow": {
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   },
   "outputs": [],
   "source": [
    "new_df=new_df.rename(columns={'LOR ': 'Letter of Recommendation'})\n",
    "new_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "* could we do something cooler? Let's check the `DataFrame.rename()` docs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "hideCode": true,
    "slideshow": {
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   "outputs": [],
   "source": [
    "df.rename?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "new_df=new_df.rename(mapper=str.strip, axis='columns')\n",
    "# Let's take a look at results\n",
    "new_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
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   },
   "source": [
    "* we can also assign values to the columns attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "cols = list(df.columns)\n",
    "# Then a little list comprehenshion\n",
    "cols = [x.lower().strip() for x in cols]\n",
    "# Then we just overwrite what is already in the .columns attribute\n",
    "df.columns=cols\n",
    "# And take a look at our results\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "* While `read_csv()` is cool, `read_html()` is *really* cool\n",
    "* https://en.wikipedia.org/wiki/List_of_earthquakes_in_the_United_States"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
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   },
   "outputs": [],
   "source": [
    "pd.read_html?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
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   },
   "outputs": [],
   "source": [
    "df=pd.read_html('https://en.wikipedia.org/wiki/List_of_earthquakes_in_the_United_States')"
   ]
  }
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