Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Integrate common base mode colors into public dashboard #148

Merged
merged 43 commits into from
Sep 21, 2024
Merged

Integrate common base mode colors into public dashboard #148

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
43 commits
Select commit Hold shift + click to select a range
58d7697
Added in support for emission common to public dashboard, and integra…
louisg1337 Aug 8, 2024
ee7cc2e
Added in edge case to deal with bike to BICYCLE
louisg1337 Aug 8, 2024
25259d2
Removed emcommon dependency install and adjusted code to work for dyn…
louisg1337 Aug 20, 2024
7b456a9
Added in support for lighter colors if multiple of the same color appear
louisg1337 Aug 23, 2024
7137a01
Use exponential decay coefficient to account for infinite duplicate c…
louisg1337 Aug 23, 2024
6630214
Import and use emcommon's dedupe_colors function
louisg1337 Aug 26, 2024
998a725
Added support for emcommon default labels, but commented out for time…
louisg1337 Aug 29, 2024
ff703a9
Refactored plots and colors so they work off of internal values inste…
louisg1337 Aug 30, 2024
1808c69
Initial commit. Changes copied from Integrate common base mode colors…
iantei Sep 4, 2024
3094859
Check for baseMode as key in dynamic_labels
iantei Sep 4, 2024
86f3798
Update purpose-value mapping from label_options's Purpose's value ins…
iantei Sep 4, 2024
e2cd09c
Remove find_closest_key() since we are not using it anymore.
iantei Sep 4, 2024
b07ffd1
Remove dic_re, dic_pur as function parameter from mapping_color_label…
iantei Sep 4, 2024
2e2bedc
Update mapping_color_labels() to only take dynamic_labels as the func…
iantei Sep 4, 2024
d4cbcc1
Merge remote-tracking branch 'Louis_Changes/common_colors' into Integ…
iantei Sep 10, 2024
26c39a8
1. Update load_viz_notebook_data() as async function so we can call a…
iantei Sep 11, 2024
8c8b7ff
Update Other to other since we pass the internal mode instead of Disp…
iantei Sep 11, 2024
1ef4c3b
Update mapping_color_labels() to use await,and update its return valu…
iantei Sep 11, 2024
ac65528
Update mapping_colors_labels() to use await, and update return variab…
iantei Sep 11, 2024
fccc53d
Change the mapping_color_labels() to use await, and update return var…
iantei Sep 11, 2024
a0fae22
Update use of merge_mode_confirm over mode_confirm.
iantei Sep 11, 2024
12d4795
Update await to scaffolding.load_viz_notebook_data()
iantei Sep 11, 2024
51eb1da
Remove find_closest_key() since it's not being used anywhere.
iantei Sep 11, 2024
a5180c4
Add await in front of scaffolding.mapping_color_labels() since it is …
iantei Sep 11, 2024
78d105a
Add values_to_translations mapping for text and html table for mappin…
iantei Sep 12, 2024
e634d8e
Use merge_mode_confirm column which has internal label, merged to oth…
iantei Sep 12, 2024
ed0c4c6
Handle cases when MODE, PURPOSE, or REPLACED_MODE is unavailable.
iantei Sep 12, 2024
75b4ce2
Split mapping_color_labels() to two functions - mapping_color_labels(…
iantei Sep 15, 2024
a1620e4
Merge branch 'main' into Integrate_base_mode_colors
iantei Sep 16, 2024
75d594c
Handle INVALID sensed mode color mapping. Use dedupe to differentiate…
iantei Sep 16, 2024
f1176f6
Extract color mapping for BLE modes. Set the default values for dyanm…
iantei Sep 16, 2024
399cd5a
Update mapping_color_labels() to return colors_ble as another return …
iantei Sep 16, 2024
60f5af3
Update mapping_color_labels() for ble modes to pass only the unique_k…
iantei Sep 16, 2024
0e5d869
Add try-except block for ble processing for survey_metrics.ipynb like…
iantei Sep 16, 2024
b3a0391
Remove e-mission-common here since it is pulled from the server
shankari Sep 19, 2024
0034d6f
Aggregate a single place to chose labels from either dynamic_labels o…
iantei Sep 19, 2024
669d521
Merge branch 'Integrate_base_mode_colors' of https://github.com/iante…
iantei Sep 19, 2024
afaed09
Enforce coding standard for python as import X as x and then x.function.
iantei Sep 19, 2024
9cefa33
Rename the column in expaneded_ct in scaffolding from merge_** to **_…
iantei Sep 19, 2024
ec355ca
Rename merge_** to **_w_other in generic_metrics and mode_specific_me…
iantei Sep 19, 2024
821fe7d
Remove unnecessary conversion of defaultdict to dict.
iantei Sep 19, 2024
ac07f67
Rename edb for emcommon.diary.base.modes to emcdb. Rename eu for emco…
iantei Sep 19, 2024
3cbd76b
Merge branch 'main' into Integrate_base_mode_colors
iantei Sep 20, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion viz_scripts/energy_calculations.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -106,7 +106,7 @@
},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

don't we need the values_to_translations here? we should use the display modes in the energy and emission impact plots.

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

We do not need the values_to_translations() here. It's being used only with the Stacked Bar Charts. We are using display modes in the energy and emission impact plots.

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Wait, so we have mode_confirm, mode_confirm_w_other and Mode_confirm all at the same time? When we remove the csvs I think we should probably get rid of Mode_confirm and just use values_to_translations to prevent confusion.

" month,\n",
" program,\n",
" study_type,\n",
Expand Down
35 changes: 18 additions & 17 deletions viz_scripts/generic_metrics.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -90,7 +90,8 @@
"metadata": {},
"outputs": [],
"source": [
"colors_mode, colors_purpose, colors_sensed = scaffolding.mapping_color_labels(dynamic_labels, dic_re, dic_pur)"
"colors_mode, colors_replaced, colors_purpose, colors_sensed, colors_ble = await scaffolding.mapping_color_labels(dynamic_labels)\n",
"values_to_translations, value_to_translations_purpose, values_to_translations_replaced = await scaffolding.translate_values_to_labels(dynamic_labels)"
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

nit: why isn't this values_to_translations_mode?

]
},
{
Expand All @@ -108,7 +109,7 @@
"metadata": {},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
Expand Down Expand Up @@ -207,8 +208,8 @@
" # We will have text results corresponding to the axes for simplicity and consistency\n",
" text_results = [[\"Unmodified Alt Text\", \"Unmodified HTML\"], [\"Unmodified Alt Text\", \"Unmodified HTML\"]]\n",
" \n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: (df.groupby(\"Mode_confirm\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False)), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax[0], text_results[0], colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: (df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False)), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax[0], text_results[0], colors_mode, debug_df, values_to_translations)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_sensed, lambda df: (df.groupby(\"primary_mode\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False)), \n",
" \"Sensed by OpenPATH\\n\"+stacked_bar_quality_text_sensed, ax[1], text_results[1], colors_sensed, debug_df_sensed)\n",
" \n",
Expand Down Expand Up @@ -258,8 +259,8 @@
" # Plot entries\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True) \n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(expanded_ct_commute, lambda df: df.groupby(\"Mode_confirm\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n (Confirmed trips)\", ax, text_results, colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_commute, lambda df: df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n (Confirmed trips)\", ax, text_results, colors_mode, debug_df, values_to_translations)\n",
" set_title_and_save(fig, text_results, plot_title, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
" plt.clf()\n",
Expand Down Expand Up @@ -291,8 +292,8 @@
"try:\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True)\n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: df.groupby(\"Trip_purpose\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax, text_results, colors_purpose, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: df.groupby(\"purpose_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax, text_results, colors_purpose, debug_df, value_to_translations_purpose)\n",
" set_title_and_save(fig, text_results, plot_title_no_quality, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
" plt.clf()\n",
Expand Down Expand Up @@ -335,16 +336,16 @@
"\n",
" ## We do an existence check for the labeled df because we want to display the sensed value even if we don't have the labeled value\n",
" ## but we don't need to have an existence check for sensed because in that case we will have no data to display\n",
" expanded_ct_u80 = expanded_ct.loc[(expanded_ct['distance'] <= cutoff)] if \"Mode_confirm\" in expanded_ct.columns else None\n",
" expanded_ct_u80 = expanded_ct.loc[(expanded_ct['distance'] <= cutoff)] if \"mode_confirm_w_other\" in expanded_ct.columns else None\n",
" expanded_ct_sensed_u80 = expanded_ct_sensed.loc[(expanded_ct_sensed['distance'] <= cutoff)]\n",
" sensed_u80_quality_text = f\"{len(expanded_ct_sensed_u80)} trips ({round(len(expanded_ct_sensed_u80)/len(expanded_ct_sensed)*100)}% of all trips)\\nfrom {scaffolding.unique_users(expanded_ct_sensed_u80)} {sensed_match.group(3)}\"\n",
" labeled_u80_quality_text = f\"{len(expanded_ct_u80)} trips ({round(len(expanded_ct_u80)/len(expanded_ct)*100)}% of all labeled,\\n{round(len(expanded_ct_u80)/len(expanded_ct_sensed)*100)}% of all trips)\\nfrom {scaffolding.unique_users(expanded_ct_u80)} {sensed_match.group(3)}\" if \"Mode_confirm\" in expanded_ct.columns else \"0 labeled trips\"\n",
" \n",
" # Plot entries\n",
" fig, ax = plt.subplots(nrows=2, ncols=1, figsize=(15,2*2), sharex=True)\n",
" text_results = [[\"Unmodified Alt Text\", \"Unmodified HTML\"], [\"Unmodified Alt Text\", \"Unmodified HTML\"]]\n",
" plot_and_text_stacked_bar_chart(expanded_ct_u80, lambda df: df.groupby(\"Mode_confirm\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+labeled_u80_quality_text, ax[0], text_results[0], colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_u80, lambda df: df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+labeled_u80_quality_text, ax[0], text_results[0], colors_mode, debug_df, values_to_translations)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_sensed_u80, lambda df: df.groupby(\"primary_mode\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Sensed by OpenPATH\\n\"+sensed_u80_quality_text, ax[1], text_results[1], colors_sensed, debug_df_sensed)\n",
" set_title_and_save(fig, text_results, plot_title_no_quality, file_name)\n",
Expand Down Expand Up @@ -383,8 +384,8 @@
" fig, ax = plt.subplots(nrows=2, ncols=1, figsize=(15,2*2), sharex=True)\n",
" \n",
" text_results = [[\"Unmodified Alt Text\", \"Unmodified HTML\"], [\"Unmodified Alt Text\", \"Unmodified HTML\"]]\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: df.groupby(\"Mode_confirm\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax[0], text_results[0], colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax[0], text_results[0], colors_mode, debug_df, values_to_translations)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_sensed, lambda df: df.groupby(\"primary_mode\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Sensed by OpenPATH\\n\"+stacked_bar_quality_text_sensed, ax[1], text_results[1], colors_sensed, debug_df_sensed)\n",
" set_title_and_save(fig, text_results, plot_title_no_quality, file_name) \n",
Expand Down Expand Up @@ -419,15 +420,15 @@
"try:\n",
" ## We do an existence check for the labeled df because we want to display the sensed value even if we don't have the labeled value\n",
" ## but we don't need to have an existence check for sensed because in that case we will have no data to display\n",
" labeled_land_trips_df = expanded_ct[expanded_ct['mode_confirm'] != \"air\"] if \"mode_confirm\" in expanded_ct.columns else None\n",
" labeled_land_trips_df = expanded_ct[expanded_ct['mode_confirm_w_other'] != \"air\"] if \"mode_confirm_w_other\" in expanded_ct.columns else None\n",
" sensed_land_trips_df = expanded_ct_sensed[expanded_ct_sensed['primary_mode'] != \"AIR_OR_HSR\"]\n",
" \n",
" sensed_land_quality_text = f\"{len(sensed_land_trips_df)} trips ({round(len(sensed_land_trips_df)/len(expanded_ct_sensed)*100)}% of all trips)\\nfrom {scaffolding.unique_users(sensed_land_trips_df)} {sensed_match.group(3)}\"\n",
" labeled_land_quality_text = f\"{len(labeled_land_trips_df)} trips ({round(len(labeled_land_trips_df)/len(expanded_ct)*100)}% of all labeled,\\n{round(len(labeled_land_trips_df)/len(expanded_ct_sensed)*100)}%) of all trips)\\nfrom {scaffolding.unique_users(labeled_land_trips_df)} {sensed_match.group(3)}\" if \"Mode_confirm\" in expanded_ct.columns else \"0 labeled trips\"\n",
" labeled_land_quality_text = f\"{len(labeled_land_trips_df)} trips ({round(len(labeled_land_trips_df)/len(expanded_ct)*100)}% of all labeled,\\n{round(len(labeled_land_trips_df)/len(expanded_ct_sensed)*100)}%) of all trips)\\nfrom {scaffolding.unique_users(labeled_land_trips_df)} {sensed_match.group(3)}\" if \"mode_confirm_w_other\" in expanded_ct.columns else \"0 labeled trips\"\n",
"\n",
" fig, ax = plt.subplots(nrows=2, ncols=1, figsize=(15,2*2), sharex=True)\n",
" plot_and_text_stacked_bar_chart(labeled_land_trips_df, lambda df: df.groupby(\"Mode_confirm\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+labeled_land_quality_text, ax[0], text_results[0], colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(labeled_land_trips_df, lambda df: df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+labeled_land_quality_text, ax[0], text_results[0], colors_mode, debug_df, values_to_translations)\n",
" plot_and_text_stacked_bar_chart(sensed_land_trips_df, lambda df: df.groupby(\"primary_mode\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Sensed by OpenPATH\\n\"+sensed_land_quality_text, ax[1], text_results[1], colors_sensed, debug_df_sensed)\n",
" set_title_and_save(fig, text_results, plot_title_no_quality, file_name) \n",
Expand Down
4 changes: 2 additions & 2 deletions viz_scripts/generic_metrics_sensed.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -96,8 +96,8 @@
" expanded_ct[\"primary_mode\"] = expanded_ct.ble_sensed_summary.apply(lambda md: max(md[\"distance\"], key=md[\"distance\"].get))\n",
" unique_keys = expanded_ct.groupby(\"primary_mode\").agg({distance_col: \"count\"}).index\n",
" print(unique_keys)\n",
" colors_mode, colors_purpose, colors_sensed = scaffolding.mapping_color_labels({}, dict(zip(unique_keys, unique_keys)), {})\n",
" colors_sensed = colors_mode\n",
" colors_mode, colors_replaced, colors_purpose, colors_sensed, colors_ble = await scaffolding.mapping_color_labels(unique_keys) #Extract ble color mapping\n",
" colors_sensed = colors_ble\n",
"except ValueError as e:\n",
" print(\"Got ValueError \", e)"
]
Expand Down
2 changes: 1 addition & 1 deletion viz_scripts/generic_timeseries.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -87,7 +87,7 @@
},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
Expand Down
17 changes: 9 additions & 8 deletions viz_scripts/mode_specific_metrics.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -103,7 +103,8 @@
"metadata": {},
"outputs": [],
"source": [
"colors_mode, colors_purpose, colors_sensed = scaffolding.mapping_color_labels(dynamic_labels, dic_re, dic_pur)"
"colors_mode, colors_replaced, colors_purpose, colors_sensed, colors_ble = await scaffolding.mapping_color_labels(dynamic_labels)\n",
"values_to_translations, value_to_translations_purpose, value_to_translations_replaced = await scaffolding.translate_values_to_labels(dynamic_labels)"
]
},
{
Expand All @@ -121,7 +122,7 @@
"metadata": {},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
Expand Down Expand Up @@ -193,8 +194,8 @@
"try:\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True)\n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"Trip_purpose\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False),\n",
" f\"Labeled `{mode_of_interest}` by user\", ax, text_results, colors_purpose, debug_df)\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"purpose_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False),\n",
" f\"Labeled `{mode_of_interest}` by user\", ax, text_results, colors_purpose, debug_df, value_to_translations_purpose)\n",
" plot_title = plot_title_no_quality + \"\\n\" + f\"For {mode_of_interest}: \" + quality_text\n",
" set_title_and_save(fig, text_results, plot_title, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
Expand Down Expand Up @@ -228,8 +229,8 @@
"try:\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True)\n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"Replaced_mode\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n (Trip distance)\", ax, text_results, colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"replaced_mode_w_other\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n (Trip distance)\", ax, text_results, colors_replaced, debug_df, value_to_translations_replaced)\n",
" plot_title = plot_title_no_quality + \"\\n\" + f\"For {mode_of_interest}: \" + quality_text\n",
" set_title_and_save(fig, text_results, plot_title, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
Expand Down Expand Up @@ -263,8 +264,8 @@
"try:\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True)\n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"Replaced_mode\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" f\"Labeled `{mode_of_interest}` by user\", ax, text_results, colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"replaced_mode_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" f\"Labeled `{mode_of_interest}` by user\", ax, text_results, colors_replaced, debug_df, value_to_translations_replaced)\n",
" plot_title = plot_title_no_quality + \"\\n\" + f\"For {mode_of_interest}: \" + quality_text\n",
" set_title_and_save(fig, text_results, plot_title, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
Expand Down
2 changes: 1 addition & 1 deletion viz_scripts/mode_specific_timeseries.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -96,7 +96,7 @@
"metadata": {},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
Expand Down
Loading