added mode specific filter for maps

[achasmita]

Adding mode specific filter to maps

I started grouping data by confirmed modes and used that data to filter all three maps:

  

[achasmita]

Here I have grouped data by mode, so that data is plotted based on selected modes:

Bubble map:

Before:

After mode filter is added:

Density Heatmap:

Before:

After mode filter is added:

Trip Lines map:

[achasmita]

With the new changes

We can now filter bubble and density heat map by different modes (there were no filters in this two maps before). And for trip map as there was already a filter option with UUID's and emails:

now it can be either filtered by mode or by UUID's and emails

[achasmita]

All three maps can now be filtered using modes:

> ### Map Type 2. **Bubble Map** and **Density Heatmap** > - There were no filter for Bubble Map and Density Heatmap before. >> >> > - Now a filter 'Modes' is added: For now, it functions similarly to the Trip lines map, where coordinates will be plotted once the user selects the modes. Alternatively, We can continue to plot them as before: once the map is selected, all co-ordinates will be plotted with different colors corresponding to the modes. >>  >>  To filter data by modes: - Started with grouping data by modes using a function ```get_trips_group_by_user_mode``` ``` def get_trips_group_by_user_mode(trips_data): trips_group_by_user_mode = None trips_df = pd.DataFrame(trips_data['data']) if not trips_df.empty: trips_df['data.user_input.mode_confirm'] = trips_df['data.user_input.mode_confirm'].fillna('Unknown') trips_group_by_user_mode = trips_df.groupby('data.user_input.mode_confirm') return trips_group_by_user_mode ``` - Edited function ```store_trips_map_data```: > - created new function ``` process_trips_groups``` so it can be used for both ```trips_group_by_user_id``` and ```trips_group_by_user_mode```. ``` users_data = dict() if trips_group: keys = list(trips_group) n = len(keys) % 360 k = 359 // (n - 1) if n > 1 else 0 for ind, key in enumerate(trips_group.groups.keys()): color = f'hsl({ind * k}, 100%, 50%)' trips = trips_group.get_group(key).sort_values('trip_start_time_str').to_dict("records") users_data[key] = {'color': color, 'trips': trips} return users_data ``` >> This code block was previously inside ```store_trips_map_data``` (it processes a group of trips, assigns color to each group, sorts the trips within each group and stores the processed data in a dictionary).

[shankari]

@achasmita

Please see my comment above:

I checked to see if the commits had more information, but each commit only has a single line "added mode specific filter for maps "

I still only see one line for this comment "cleaned and made changes in previous code" I expect to see an actual description of the changes, similar to https://github.com/e-mission/em-public-dashboard/pull/112/commits/68911815a6b3168f9c48fcd0169f2e64fb0d17be

Please confirm that you have seen this message and will implement it going forward

[achasmita]

@achasmita

Please see my comment above:

I checked to see if the commits had more information, but each commit only has a single line "added mode specific filter for maps "

I still only see one line for this comment "cleaned and made changes in previous code" I expect to see an actual description of the changes, similar to e-mission/em-public-dashboard@6891181

Please confirm that you have seen this message and will implement it going forward

I will make sure to follow it going forward

[shankari]

Pending feedback from @JGreenlee and potential removal of the scatterplot in the heatmap.

[shankari]

@achasmita please add testing done after the last set of changes

[achasmita]

Scatter plot is removed from heatmap and testing is done.