· This notebook shows appropriate usage of Geodataframe and VAL functions.
· For visualizations, they are converting to pandas dataframe and they are using plotly.express and matplotlib which can be converted into GeoDataFrame.plot.
Reviewer 2 comments:
· section1 usesrun_procedure.py. teradataml has copy_to_sql/load_example_data/fast_load to load the data.
· section5 combines multiple plots to a single image. teradataml supports subplots to do the same.
Reviewer 1 Suggestions
Section : Store Locations/Competitor Store Location / Customer Location
Conversion to pandas dataframe and usage of matplotlib/plotly.express can be avoided if we can use GeoDataFrame.plot() functionality to achieve similar plots.
Reviewer 2 Suggestions
· use teradataml utilities to load the data.
· Explore the possibility of using teradataml inhouse plot.
Pankaj Vinod Purandare review:
· Dont import the sqlalchemy module in section 6. They are not being used also.
Reviewer 1:Aanchal Kavedia Reviewer 2:Pradeep Garre Reviewer 1 comments:
· This notebook shows appropriate usage of Geodataframe and VAL functions.
· For visualizations, they are converting to pandas dataframe and they are using plotly.express and matplotlib which can be converted into GeoDataFrame.plot.
Reviewer 2 comments:
· section1 usesrun_procedure.py. teradataml has copy_to_sql/load_example_data/fast_load to load the data.
· section5 combines multiple plots to a single image. teradataml supports subplots to do the same.
Reviewer 1 Suggestions
Section : Store Locations/Competitor Store Location / Customer Location
Conversion to pandas dataframe and usage of matplotlib/plotly.express can be avoided if we can use GeoDataFrame.plot() functionality to achieve similar plots.
Reviewer 2 Suggestions
· use teradataml utilities to load the data.
· Explore the possibility of using teradataml inhouse plot.
Pankaj Vinod Purandare review:
· Dont import the sqlalchemy module in section 6. They are not being used also.