slight modification sample data

data/sample_data_1.csv

@@ -184,7 +184,7 @@ date,media,sales
 2018-07-04,0.0,8.359797280736121
 2018-07-05,0.0,7.844611915480035
 2018-07-06,0.0,7.624275189117045
-2018-07-07,0.0,8.05752136474238
+2018-07-07,0.0,6.05752136474238
 2018-07-08,0.0,7.719221623176026
 2018-07-09,0.0,7.790240634090118
 2018-07-10,0.0,7.806956427602587
@@ -549,7 +549,7 @@ date,media,sales
 2019-07-04,0.0,8.53517033396665
 2019-07-05,0.0,8.443243974286553
 2019-07-06,0.0,8.67832949250563
-2019-07-07,0.0,8.591581728350102
+2019-07-07,0.0,6.591581728350102
 2019-07-08,0.0,9.072561536169918
 2019-07-09,0.0,9.011869004286433
 2019-07-10,0.0,8.436469259404992
@@ -915,7 +915,7 @@ date,media,sales
 2020-07-04,0.0,11.60061888194707
 2020-07-05,0.0,11.830792393168794
 2020-07-06,0.9484533069621567,12.798122644457994
-2020-07-07,0.0,12.245427896665591
+2020-07-07,0.0,10.245427896665591
 2020-07-08,0.0,11.806658259511664
 2020-07-09,0.0,11.811578639104212
 2020-07-10,0.0,11.456162791209191

meetup.md

@@ -23,6 +23,6 @@ On the file `data/sample_data_1.csv` you can find (dummy) `sales` data (`2018-01
 3. Is the feature `media` useful for prediction? 
 4. How do you evaluate model performance?
 
-Try to generate predictions for the whole month of July 2021. We will provide the "true" values during the meetup so that we can all test our models. Again, this is not a competition, but rather a concrete use case to apply what we learn about Prophet. 
+Try to generate predictions for the whole month of *July 2021*. We will provide the "true" values during the meetup so that we can all test our models. Again, this is not a competition, but rather a concrete use case to apply what we learn about Prophet. 
 
 Please bring questions and suggestions to make the best out of this session!