Lifelines

New features
- Now `cumulative_density_` & `survival_function_` are _always_ present on a fitted `KaplanMeierFitter`.
- New attributes/methods on `KaplanMeierFitter`: `plot_cumulative_density()`, `confidence_interval_cumulative_density_`, `plot_survival_function` and `confidence_interval_survival_function_`.

New features
- Left censoring is now supported in univariate parametric models: `.fit(..., left_censorship=True)`. Examples are in the docs.
- new dataset: `lifelines.datasets.load_nh4()`
- Univariate parametric models now include, by default, support for the cumulative density function: `.cumulative_density_`, `.confidence_interval_cumulative_density_`, `plot_cumulative_density()`, `cumulative_density_at_times(t)`.
- add a `lifelines.plotting.qq_plot` for univariate parametric models that handles censored data.

API changes
- `plot_lifetimes` no longer reverses the order when plotting. Thanks vpolimenov!
- The `C` column in `load_lcd` dataset is renamed to `E`.

Bug fixes
- fixed a naming error in `KaplanMeierFitter` when `left_censorship` was set to True, `plot_cumulative_density_()` is now `plot_cumulative_density()`.
- added some error handling when passing in timedeltas. Ideally, users don't pass in timedeltas, as the scale is ambiguous. However, the error message before was not obvious, so we do some conversion, warn the user, and pass it through.
- `qth_survival_times` for a truncated CDF would return `np.inf` if the q parameter was below the truncation limit. This should have been `-np.inf`

- Some performance improvements to `CoxPHFitter` (about 30%). I know it may seem silly, but we are now about the same or slighty faster than the Cox model in R's `survival` package (for some testing datasets and some configurations). This is a big deal, because 1) lifelines does more error checking prior, 2) R's cox model is written in C, and we are still pure Python/NumPy, 3) R's cox model has decades of development.
- suppressed unimportant warnings

API changes
- Previously, lifelines _always_ added a 0 row to `cph.baseline_hazard_`, even if there were no event at this time. This is no longer the case. A 0 will still be added if there is a duration (observed or not) at 0 occurs however.

- Starting with 0.20.0, only Python3 will be supported. Over 75% of recent installs where Py3.
- Updated minimum dependencies, specifically Matplotlib and Pandas.

New features
- smarter initialization for AFT models which should improve convergence.

API changes
- `inital_beta` in Cox model's `.fit` is now `initial_point`.
- `initial_point` is now available in AFT models and `CoxTimeVaryingFitter`
- the DataFrame `confidence_intervals_` for univariate models is transposed now (previous parameters where columns, now parameters are rows).

Bug fixes
- Fixed a bug with plotting and `check_assumptions`.

New features
- `plot_covariate_group` can accept multiple covariates to plot. This is useful for columns that have implicit correlation like polynomial features or categorical variables.
- Convergence improvements for AFT models.

Bug fixes
- remove some bad print statements in `CoxPHFitter`.