feat: crypto tutorial (#273)

* A cool tutorial

This tutorial contains an example with multiple indexes and subsequent tampering to the data in order to show resiliency and a real life use case of TC applied on cryptocurrency prices up to 2021.

* Change merging method 

Fix to the issue raised on empty dataframe, resulting from an inner merge where the existing dataframe that accumulated results and the newer one had diferent indices. A subsequent issue must be raised to either: 
1 report a single model failure (on index matching) 
2 fix the moirai discrepancy (only model that showed this issue)

* run pre-comit hooks

* Changing filename to requested formats and folder. This also contains the title suggested

* Clearance of verbose cells

* Staging changes to mkdocs and the naming of the tutorial file

---------

Co-authored-by: azul <fede.garza.ramirez@gmail.com>
Co-authored-by: elmartinj <elmartinj>

Author: elmartinj

docs/examples/cryptocurrency-quickstart.ipynb

@@ -27,6 +27,7 @@ nav:
           - examples/ts-foundation-models-comparison-quickstart.ipynb
           - examples/gift-eval.ipynb
           - examples/chronos-family.ipynb
+          - examples/crytpocurrency-quickstart.ipynb
   - Experiments:
       - experiments/gift-eval.md
       - experiments/fev.md

mkdocs.yml

@@ -113,10 +113,7 @@ def _call_models(
                     # to cross validation
                     # (the initial model)
                     res_df_model = res_df_model.drop(columns=["y"])
-                res_df = res_df.merge(
-                    res_df_model,
-                    on=merge_on,
-                )
+                res_df = res_df.merge(res_df_model, on=merge_on, how="left")
         return res_df
 
     def forecast(