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### Assignment # Page View Time Series Visualizer
For this project you will visualize time series data using a line chart, bar chart, and box plots. You will use Pandas, Matplotlib, and Seaborn to visualize a dataset containing the number of page views each day on the freeCodeCamp.org forum from 2016-05-09 to 2019-12-03. The data visualizations will help you understand the patterns in visits and identify yearly and monthly growth. This is the boilerplate for the Page View Time Series Visualizer project. Instructions for building your project can be found at https://www.freecodecamp.org/learn/data-analysis-with-python/data-analysis-with-python-projects/page-view-time-series-visualizer
Use the data to complete the following tasks:
* Use Pandas to import the data from "fcc-forum-pageviews.csv". Set the index to the "date" column.
* Clean the data by filtering out days when the page views were in the top 2.5% of the dataset or bottom 2.5% of the dataset.
* Create a `draw_line_plot` function that uses Matplotlib to draw a line chart similar to "examples/Figure_1.png". The title should be "Daily freeCodeCamp Forum Page Views 5/2016-12/2019". The label on the x axis should be "Date" and the label on the y axis should be "Page Views".
* Create a `draw_bar_plot` function that draws a bar chart similar to "examples/Figure_2.png". It should show average daily page views for each month grouped by year. The legend should show month labels and have a title of "Months". On the chart, the label on the x axis should be "Years" and the label on the y axis should be "Average Page Views".
* Create a `draw_box_plot` function that uses Searborn to draw two adjacent box plots similar to "examples/Figure_3.png". These box plots should show how the values are distributed within a given year or month and how it compares over time. The title of the first chart should be "Year-wise Box Plot (Trend)" and the title of the second chart should be "Month-wise Box Plot (Seasonality)". Make sure the month labels on bottom start at "Jan" and the x and x axis are labeled correctly.
For each chart, make sure to use a copy of the data frame. Unit tests are written for you under `test_module.py`.
### Development
For development, you can use `main.py` to test your functions. Click the "run" button and `main.py` will run.
### Testing
We imported the tests from `test_module.py` to `main.py` for your convenience. The tests will run automatically whenever you hit the "run" button.
### Submitting
Copy your project's URL and submit it to freeCodeCamp.