update 3rd notebook for exercise 7

exercises/release/exercise-07/3__plot_csv.ipynb

@@ -17,15 +17,32 @@
     "\n",
     "- Remember that you can get the command-line arguments to a python program by importing the `sys` module and accessing the `sys.argv` variable, which is a list of strings. So the filename with the data is provided as a command-line argument to your python program.\n",
     "- Read the CSV data from the provided filename using Pandas `read_csv()` function.\n",
-    "- Plot the results with seaborn's `lineplot()` function.\n",
+    "- Plot the results with [seaborn's `lineplot()`](https://seaborn.pydata.org/generated/seaborn.lineplot.html#seaborn.lineplot) function. The X value of the plot will by PCR cycle number and the Y value of the plot will be fluorescence intensity. To use one line per well, use the `hue` keyword argument.\n",
     "- Save this figure (with matplotlib.pylot's `savefig()`) to a file with the name equal to the original file name with `.png` appended to it (e.g. for the above example with `pcr_sample_1.csv` as input, save the figure to `pcr_sample_1.csv.png`).\n",
     "\n",
+    "Use the following imports block (and do not import anything else):\n",
+    "\n",
+    "```\n",
+    "import sys\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import pandas as pd\n",
+    "```\n",
+    "\n",
     "When you are done with your program `plot_pcr_data.py`, upload it to the directory for this exercise. I will run it with a new CSV data file from a different PCR experiments to check that it works.\n",
     "\n",
     "With `pcr_sample_1.csv`, your plot should look like this:\n",
     "\n",
     "![pcr_results.png](pcr_results.png)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "79875b52-ccd1-4a13-bf1b-547a15466ebc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {