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    "#Plot sounding data from 9/8/2020 balloon launches\n",
    "# One of the most severe wind events to happen along the Wasatch Front occurred\n",
    "# on September 8, 2020\n",
    "# Undregrads launched a weather balloon carrying sensors to meaure weather conditions\n",
    "# including wind\n",
    "\n",
    "# The objective of this assignment is to read the data and then plot the vertical\n",
    "# profile of wind speed and direction observed at  7 AM MDT September 8 2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b1c8bc28-b4a6-4c48-9de9-7509f2623ea6",
   "metadata": {},
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0c2256c3-311b-4431-b66a-10b9e0c01ee9",
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   "source": [
    "# 1) look at the data file sonde_09_08_13utc.csv\n",
    "\n",
    "# The columns: are height (meters), pressure (hPa), temperature (C), relative humidity (%), wind speed (m/s), direction (degrees)\n",
    "# here are the \n",
    "\n",
    "# 2) Create a panda data frame, sounding, using only the columns: height, wind speed, and direction\n",
    "# hints: there are no headers in the file, so you need to say so using an option \"None\"\n",
    "# hints: you can define what columns to use by referring to them as a list of the columns you want to use\n",
    "         "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a0303099-648b-403d-afc6-5eb680641786",
   "metadata": {},
   "outputs": [],
   "source": [
    "#3) define a list, headers, that contains the headers for these three columns: \"HGHT\", \"SPED\", \"DRCT\"\n",
    "\n",
    "\n",
    "#4 add the columns headers using something of the form \"sounding.columns =\"\n",
    "\n",
    "#5 Have 'HGHT' be the index\n",
    "\n",
    "#6 Drop the HGHT column from the sounding dataframe\n",
    "\n",
    "#at this point HGHT should be the index and SPED and DRCT are the columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "52f8a8b2-43b7-4e05-ba5e-2224a3c12bdc",
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   "source": [
    "#7)  create a figure of size 5 wide by 10 tall with the axis \"ax\"\n",
    "\n",
    "# create a duplicate axis, ax1, to plot a second variable using the same y axis\n",
    "# look at pg. 153 but think about which axis is being \"twinned\"\n",
    "\n",
    "\n",
    "#8 plot on axis ax the speed on the x axis vs height (the index) on the y axis\n",
    "# with a red line of width 1\n",
    "\n",
    "\n",
    "#9 using the ax1, overlay direction on the x axis vs height on the y axis\n",
    "# no line, a balck square marker of size 2 \n",
    "\n",
    "#10 add labels on the x and y axes using 14 pt font\n",
    "# the labels should be\n",
    "#'Wind Speed m/s' (on the bottom)\n",
    "# 'Direction ($^\\circ$)' (on the top)\n",
    "# \"Height AGL (m)\" (on the side)\n",
    "# add a title with your name and unid using fontsize 20\n",
    "\n",
    "\n",
    "#11 save the plot as \"red_butte_09_08_22_1300utc.png\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8faa5515-2551-4b14-b76f-0d2693898ef9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#12 use the \"describe\" function to obtain info on the speed and direction values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f93458f7-2436-4010-a1aa-9acacdaf23b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 13) use the concepts shown in the Chapter2 stats code to find the height where the\n",
    "# wind speed is a max in the pandas data frame (look for idxmax). \n",
    "# there are many ways to do this but it can be done in two lines of code\n"
   ]
  }
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