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    "# Create a standalone Python program\n",
    "\n",
    "The instructions for this exercise are in this Jupyter notebook, but to successfully complete the exercise, you need to write a plain Python `.py` file called `plot_pcr_data.py` that runs from the command line. Write your program so that when you run it like this:\n",
    "\n",
    "    python plot_pcr_data.py pcr_sample_1.csv\n",
    "\n",
    "It will read load the CSV file named `pcr_sample_1.csv` and save a plot called `pcr_sample_1.csv.png`. This data file is the result of a [real-time PCR](https://en.wikipedia.org/wiki/Real-time_polymerase_chain_reaction) experiment in a 6 well plate. The plot should plot number of cycles on the X axis and fluorescence intensity on the Y axis. There should be a line for the data from each well in the experiment.\n",
    "\n",
    "Hints:\n",
    "\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",
    "- 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",
    "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)"
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