Doubleml

- We added [Contribution Guidelines](https://github.com/DoubleML/doubleml-for-py/blob/master/CONTRIBUTING.md), issue templates, a pull request template and a [discussion forum](https://github.com/DoubleML/doubleml-for-py/discussions) to the repository #132
- Code refactorings, docu updates, unit test extensions and continuous integration 126 127 128 130 131

- **Release highlight:** Clustered standard errors for double machine learning models 116
- Improve exception handling for missings and infinite values in the confounders, predictions, etc. (fixes 120 by allowing null confounder values) 122
- Clean up dev requirements and use dev requirements on github actions 121
- Other updates 123

* Initialize all numeric matrices, vectors and arrays with the correct data type by using `NA_real_` instead of `NA` 115
* Replace a `print()` call with `cat()` 115

- Always use the same bootstrap algorithm independent of `dml1` vs `dml2` and consistent with docu and paper 101 & 102
- Added an exception handling to assure that an IV variable is specified when using a PLIV or IIVM model 107
- Improve exception handling for externally provided sample splitting 110
- Minor update of the str representation of `DoubleMLData` objects 112
- Code refactorings and unit test extensions 103, 105, 106, 111 & 113

- IIVM model: Added a subgroups option to adapt to cases with and without the subgroups of always-takers and never-takers (96).
- Add checks for the intersections of `y_col`, `d_cols`, `x_cols`, `z_cols` (84, 97). This also fixes 83 (with intersection between `x_cols` and `d_cols` a column could have been added multiple times to the covariate matrix).
- Added checks and exception handling for duplicate entries in `d_cols`, `x_cols` or `z_cols` (100).
- Check the datatype of `data` when initializing `DoubleMLData` objects. Also check for duplicate column names (100).
- Fix bug 95 in 97: It occurred when `x_cols` where inferred via setdiff and `y_col` was a string with multiple characters.
- We updated the citation info to refer to the arXiv paper (98): Bach, P., Chernozhukov, V., Kurz, M. S., and Spindler, M. (2021), DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python, [arXiv:2104.03220](https://arxiv.org/abs/2104.03220).

- Provide an option to store & export the first-stage predictions [91](https://github.com/DoubleML/doubleml-for-py/pull/91)
- Added the package logo to the doc