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This project forked from attila5287/du_bigdata_hw5_matplotlib-pyber

* You must use the Pandas Library and the Jupyter Notebook. * You must use the Matplotlib library. * You must include a written description of three observable trends based on the data. * You must use proper labeling of your plots, including aspects like: Plot Titles, Axes Labels, Legend Labels, X and Y Axis Limits, etc. * Your scatter plots must include [error bars](https://en.wikipedia.org/wiki/Error_bar). This will allow the company to account for variability between mice. You may want to look into [`pandas.DataFrame.sem`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.sem.html) for ideas on how to calculate this. * Remember when making your plots to consider aesthetics! * Your legends should not be overlaid on top of any data. * Your bar graph should indicate tumor growth as red and tumor reduction as green. It should also include a label with the percentage change for each bar. You may want to consult this [tutorial](http://composition.al/blog/2015/11/29/a-better-way-to-add-labels-to-bar-charts-with-matplotlib/) for relevant code snippets. * See [Starter Workbook](Pymaceuticals/pymaceuticals_starter.ipynb) for a reference on expected format. (Note: For this example, you are not required to match the tables or data frames included. Your only goal is to build the scatter plots and bar graphs. Consider the tables to be potential clues, but feel free to approach this problem, however, you like.) ## Hints and Considerations * Be warned: These are very challenging tasks. Be patient with yourself as you trudge through these problems. They will take time and there is no shame in fumbling along the way. Data visualization is equal parts exploration, equal parts resolution.