Add links to issues and documentation, and fix punctuation

Author: SangamSwadiK

_posts/2022-11-08-pandas-dataframe-output-for-sklearn-transformer.md

@@ -4,7 +4,7 @@ date: November 8, 2022
 categories:
   - Technical
 tags:
-  - Sklearn-Transformers
+  - performance
 featured-image: pandas_output_sklearn_transformers.PNG
 
 postauthors:
@@ -22,9 +22,21 @@ postauthors:
 <iframe width="560" height="315" src="https://www.youtube.com/embed/5bCg8VfX2x8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
 
 ## Upcoming feature in release 1.2
-Starting next release(v1.2) Scikit-learn provides the ability for the outputs of Scikit-learn transformers to be either in Numpy or Pandas format by configuring it explicitly.Previously, mapping a transformed output back into columns would be cumbersome as it might not be a one-to-one mapping because of complex preprocessing (e.g: Polynomial features ).
-The next release(v1.2) Pandas output for transformers maps the transformed features into corresponding names/how they were created automatically.This would be useful for more complex preprocessing pipelines.
+Starting with the next release of [scikit-learn](https://github.com/scikit-learn/scikit-learn) (v1.2), pandas dataframe output will be available for all sklearn transformers! This will make running pipelines on dataframes much easier and provide better ways to track feature names. Previously, mapping a transformed output back into columns would be cumbersome as it might not be a one-to-one mapping in cases of complex preprocessing (e.g., polynomial features ).
 
-## Links to Sample notebook and usage:
-- [Pandas output for transformers](https://scikit-learn.org/dev/auto_examples/miscellaneous/plot_set_output.html#sphx-glr-auto-examples-miscellaneous-plot-set-output-py) 
-- [Sample notebook](https://github.com/scikit-learn/blog/blob/main/assets/notebooks/sklearn-pandas-df-output.ipynb)
+The pandas dataframe output feature for transformers solves this by tracking features generated from pipelines automatically. The transformer output format can be configured explictly for either **numpy** or **pandas** output formats as shown in [sklearn.set_config](https://scikit-learn.org/dev/modules/generated/sklearn.set_config.html#sklearn.set_config) and the sample code below.
+```python
+from sklearn import set_config
+set_config(transform_output = "pandas")
+```
+
+Please see the sample notebook and documentation for a more detailed example and usage.
+
+## Links to documentation and example notebook:
+- [Pandas output for transformers documentation](https://scikit-learn.org/dev/auto_examples/miscellaneous/plot_set_output.html#sphx-glr-auto-examples-miscellaneous-plot-set-output-py) 
+- [Sample notebook](https://github.com/scikit-learn/blog/blob/main/assets/notebooks/sklearn-pandas-df-output.ipynb)
+
+
+## Reporting bugs:
+We'd love your feedback on this. In case of any suggestions or bugs, please report them at
+[scikit-learn issues](https://github.com/scikit-learn/scikit-learn/issues)