Livesplit-parser

* Fixed a bug where completed run heatmaps and lineplots were not being generated due to split names containing the substring `Sec` in them (ex 1-Secret or Princess' Secret Slide)
* Added an optional `plot` boolean parameter to all plotting functions that lets you decide whether you want to generate a new plot on the function call or leave it as is.
* Set the default value of `drop_na` to True for heatmap, lineplot, and violinplots to remove runs that have skipped splits that significantly throw off the average
* Fixed a bug that poorly computed averages if runs with skipped splits were removed for plotting purposes
* Added an optional `time_limit` parameter to all plotting functions that lets you set an upper bound on finished times to include in your plots. This effectively lets you remove outliers of crazy slow times from your plots should you want that. Default value is `None`.
* Added two new functions `chance_run_continues()` and `percent_run_past()` that when given a split name will return the percentage of runs that get past that split

Added the following updates:

* Added a `plot_completed_runs_lineplot()` that visualizes your completed runs and how far off they are from the average time it takes to complete that split
* Added a `plot_completed_runs_heatmap()` function that visualizes how good/bad a split was compared to the average based on a color
* Added a `plot_splits_violin_plot()` function that plots your splits information using a violinplot technique
* Added a `export_data()` function that exports your data to a csv file
* Added a `plot_num_resets()` function that plots the number of times you reset between completed attempts
* Added a `plot_completed_over_time()` function that plots the final times of all your completed runs

Initial release of the package! Includes the `LiveSplitData` class with information stored about your LiveSplit data. `LivesplitData` is structured as follows:

* `LivesplitData.num_attempts`: the number of attempts for your run
* `LivesplitData.num_completed_attempts`: the number of attempts that were also completed runs
* `LivesplitData.percent_runs_completed`: the percentage of all your attempts that were completed (this is just `LivesplitData.num_completed_attempts / LivesplitData.num_attempts * 100`)
* `LivesplitData.attempt_info_df`: A `pandas.DataFrame` object containing information about every attempt. Each row is an attempt indexed by an ID. The columns of the dataframe are as follows:
* `started`: timestamp of when the attempt started
* `isStartedSynced`: ?????
* `ended`: timestamp of when the attempt ended
* `isEndedSynced`: ?????
* `RunCompleted`: If `True`, the attempt was a completed run. If `False`, the attempt was not a completed run
* `RealTime`: If not a completed run, shows the time the attempt lasted for. If a completed run, shows the final time of the run.
* Every column afterwards is the name of a split and the length of that segment for that attempt
* `LiveSplitData.split_info_df`: A `pandas.DataFrame` object containing general information about every segment in your run. Each row is an individual split in your run. The columns of the dataframe are as follows:
* `PersonalBest`: the **segment time** for your Personal Best
* `PersonalBestSplitTime`: the **split time** for your Personal Best
* `BestSegment`: the fastest time you have completed that split
* `BestSegmentSplitTime`: the **split times** for your best segments if your best segments were a completed run
* `Average`: the average length of a given split
* `AverageSegmentSplitTime`: the **split times** for your average segments if your average segments were a completed run
* `Median`: the median length of a given split
* `MedianSegmentSplitTime`: the **split times** for your median segments if your median segments were a completed run
* `NumRunsPassed`: The number of attempts that completed that split
* `PercentRunsPassed`: The percentage of attempts that completed that split