def update_charts(selected_status, selected_clinicians, selected_patients, start_date, end_date, selected_task, selected_task_category): data = chart_utils.get_loaded_data('CENSUS_VISITS_BY_STATUS') patient_roster_data = chart_utils.get_loaded_data('PATIENT_ROSTER') if start_date: data = data.loc[data["SCHEDULED_DATE"] >= start_date] if end_date: data = data.loc[data["SCHEDULED_DATE"] < end_date] if selected_clinicians: data = data.loc[data["ASSIGNED_TO"].isin(selected_clinicians)] if selected_status: data = data.loc[data["STATUS"].isin(selected_status)] if selected_patients: data = data.loc[data["PATIENT"].isin(selected_patients)] if selected_task: data = data.loc[data["TASK"].isin(selected_task)] if selected_task_category: data = data.loc[data["TASK_CATEGORY"].isin(selected_task_category)] pie_charts = [ ddk.Card( [ ddk.CardHeader("Overview of {}".format(column.title())), chart_utils.generate_pie(data, column), ], ) for column in ["PAYOR", "STATUS"] ] time_series = [ ddk.DataCard( id='visits_by_status_count', value=data.shape[0] ), ddk.CardHeader("Status of tasks for selected clinicians, dates, and status"), chart_utils.generate_census_bar(data), ] data_table = data.sort_values(by="SCHEDULED_DATE").to_dict("records") patient_roster_chart = [ ddk.DataCard( id='census_count', value=patient_roster_data.shape[0] ), ddk.CardHeader("Patient Roster Chart"), chart_utils.generate_patient_roster_bar(patient_roster_data), ] return patient_roster_chart, data_table, time_series, 0
def generate_table_layout(table_df, title, tableid, sort_cols, remove_cols): children = html.Div([ ddk.Card(children=[ ddk.CardHeader(children=[ html.Div( title, style={"float": "left"}, ), ]), ddk.Block(ddk.DataTable( columns=[{ "name": i.replace("_", " ").title(), "id": i } for i in table_df.columns if (i not in remove_cols)], filter_action="native", page_action="native", page_size=10, row_selectable="multi", id=tableid, style_cell={ 'fontSize': 12, 'font-family': 'sans-serif' }, style_table={'overflowX': 'auto'}, ), style={"overflow": "scroll"}), ]), ]) return children
def trigger_by_modify(n): # print("############### UPDATE 1 #########################") # PARSER.new_refresh() # Structure.refresh_BD() # print("############### UPDATE 2 #########################") print("############### START UPDATE #########################") result = [ ddk.CardHeader(title='Матчи', style={ 'background-color': '#1c424c', 'margin': '0px', 'padding': '15px', 'display': 'block', 'font-size': '20px' }), Main_page.main_page() ] # live = [i for i in Live_matches.live()] results = [ ddk.CardHeader(title='Результаты', style={ 'background-color': '#1c424c', 'margin': '0px', 'padding': '15px', 'display': 'block', 'font-size': '20px' }), Result_page.result_page() ] # # tour = [ # ddk.CardHeader(title='Турниры', # style={'background-color': '#1c424c', # 'margin': '0px', # 'padding': '15px', # 'display':'block', # 'font-size': '20px'}), # Main_tours_page.tour_page()] print("############### UPDATED #########################") return result, results
def update_charts( selected_status, selected_clinicians, selected_patients, start_date, end_date ): data = chart_utils.get_loaded_data("SCHEDULEREPORTS_VISITSBYSTATUS","DATASET") #print(data.columns) if start_date: data = data.loc[data["SCHEDULED_DATE"] > start_date] if end_date: data = data.loc[data["SCHEDULED_DATE"] < end_date] if selected_clinicians: data = data.loc[data["ASSIGNED_TO"].isin(selected_clinicians)] if selected_status: data = data.loc[data["STATUS"].isin(selected_status)] if selected_patients: data = data.loc[data["PATIENT"].isin(selected_patients)] pie_charts = [ ddk.Card( [ ddk.CardHeader(title="Overview of {}".format(column.title())), chart_utils.generate_pie(data, column), ], ) for column in ["PAYOR", "STATUS"] ] time_series = [ ddk.DataCard( id='total_visits_count', value=data.shape[0] ), ddk.CardHeader( title="Status of tasks for selected clinicians, dates, and status" ), chart_utils.generate_bar(data), ] data_table = data.sort_values(by="SCHEDULED_DATE").to_dict("records") return pie_charts, data_table, time_series, 0
def news_items(): newsBD = pd.read_csv(main_path_data + '\\news.csv') cards = [] for ind in newsBD.index: ########################## NEWS CARD ################################### news_item = dbc.ListGroupItem( href='/news/{}'.format(newsBD['Mid'][ind]), id={ 'type': 'news-card', 'index': str(newsBD['Mid'][ind]) }, style={ 'padding': '0px', 'margin-bottom': "10px", 'margin-top': "10px", 'border': 'none' }, children=[ ddk.Card(style={ 'background-color': '#073642', 'max-height': '100px', 'min-height': '100px', 'overflowY': 'hidden', 'text-align': 'center', 'margin': '0', 'padding': '0px' }, card_hover=True, children=[ ddk.CardHeader(newsBD['name'][ind], style={ 'text-align': 'left', 'font-size': '12px', 'height': '40px', 'max-height': '40px', 'overflow-y': 'hidden', 'background-color': 'transparent', }), html.H6(newsBD['disc'][ind], style={ 'margin': '0', 'padding-bottom': '5px', 'color': 'lightslategrey' }) ]) ]) cards.append(news_item) return cards
def _perform_layout(self): ddk = import_ddk() # No callbacks here. Must be constant or idempotent card_children = [] if self.title: card_children.append(ddk.CardHeader(title=self.title)) card_children.append( html.Div( style={"padding": 20}, children=html.Div(self.get_containers("output")) ) ) card_children.append(html.Hr(style={"width": "100%", "margin": "auto"})) card_children.extend(self.get_containers("input")) layout = ddk.ControlCard( children=card_children, **filter_kwargs(width=self.width), ) return layout
def _perform_layout(self): ddk = import_ddk() # Input card input_card = ddk.ControlCard( children=self.get_containers("input"), width=self.input_width, ) output_card_children = [] if self.title is not None: output_card_children.append(ddk.CardHeader(title=self.title)) output_card_children.extend(self.get_containers("output")) output_card = ddk.ControlCard( children=output_card_children, width=100 - self.input_width, ) row_children = [input_card, output_card] layout = ddk.Row(row_children) return layout
def news_page(id): all_cardsBD = pd.read_csv(main_path_data + '\\news.csv') # print(" id from NEWS :", id) # id = id.replace("news/", "") df = all_cardsBD[(all_cardsBD['Mid'].isin([int(id)]))] ############## HEAD CARD of MATCH ################################### news_head = ddk.Card( style={ 'width': '-webkit-fill-available', 'min-height': '120px', 'margin': '10px', 'padding': '15px', 'background-color': '#f9f9f91c' }, children=[ ddk.Block(width=100, style={ 'height': 'fit-content', }, children=[ html.H2(df.iloc[0]['name'], style={ 'text-align': 'left', 'font-size': '30px', 'text-color': 'azure', 'margin': '0' }) ]), ddk.Block(width=100, style={ 'max-height': 'fit-content', 'margin-bottom': '20px', }, children=[ html.P('{}'.format(df.iloc[0]['date']), style={ 'text-align': 'left', 'margin': '0' }) ]), ddk.Block(width=100, style={'max-height': 'fit-content'}, children=[ html.P('{}'.format(df.iloc[0]['disc']), style={ 'text-align': 'left', 'margin': '0' }) ]), ]) match_card = ddk.Block( width=100, style={ 'height': '93vh', 'text-align': 'center' }, children=[ ddk.Block( width=70, style={ 'height': '89vh', 'margin': '0', 'padding': '0', 'color': 'azure', 'overflowY': 'scroll', 'overflowX': 'hidden', }, children=[ news_head # ddk.Card(style={'width':'-webkit-fill-available', # 'margin':'10px', 'padding':'0', # 'background-color': '#f9f9f91c',}, # children=news_head), ]), ddk.Block(width=30, style={'height': '90vh'}, children=[ ddk.Card(width=100, style={ 'background-color': 'transparent', 'max-height': '40vh', 'min-height': '40vh', 'padding-bottom': '5px', 'padding': '0', 'overflowY': 'hidden', 'margin': '10px' }, children=[ ddk.CardHeader(title='Live', style={ 'background-color': 'transparent' }), Live_matches.live_list() ]), ddk.Card(width=100, id='match_sample_right', style={ 'background-color': 'transparent', 'max-height': '45vh', 'min-height': '45vh', 'padding-bottom': '5px', 'padding': '0', 'overflowY': 'hidden', 'margin': '10px' }, children=[ ddk.CardHeader(title='Matches', style={ 'background-color': 'transparent' }), Main_page.main_page() ]) ]) ]) return match_card
searchable=True, ), html.Div(id="Period-dropdown"), html.Label('Dino Type', style={'fontSize':30, 'textAlign':'center'}), dcc.Dropdown(id='display-type', options=[], multi=True, value=[]), ] ) ), width=8, ), ddk.Card( width=24, children=[ ddk.CardHeader(title='Total Fossils Found Across All Periods'), ddk.DataCard(value=totalFossilsFounds, style={'width':'fit-content'}), ] ), # ddk.Card( # width=24, # children=[ # ddk.CardHeader(title='Total Fossils Found'), # ddk.DataCard( # id='total-fossils', # value='', # style={'width':'fit-content'}), # ] # ),
def layout(): patient_roster_data = patient_roster_df() patient_roster_data["DOB"] = patient_roster_data["DOB"].astype(str) redis_instance.hset("app-data", "PATIENT_ROSTER", json.dumps(patient_roster_data.to_dict("records"))) data = full_df() data["SCHEDULED_DATE"] = data["SCHEDULED_DATE"].astype(str) redis_instance.hset("app-data", "CENSUS_VISITS_BY_STATUS", json.dumps(data.to_dict("records"))) max_date = datetime.now() children = html.Div( [ ddk.Row( [ ddk.Card(id="patient-roster-chart"), ] ), ddk.Row( [ ddk.ControlCard( [ html.Details( [ html.Summary("About this app"), html.P( """Select attributes to fine tune graphs and tables.""" ), ] ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": status, "value": status} for status in sorted( [ status for status in data["STATUS"].unique() if status ] ) ], multi=True, placeholder="Select Status", id="census-status-selector" #value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": task, "value": task} for task in sorted( [ task for task in data["TASK"].unique() if task ] ) ], multi=True, placeholder="Select Task", id="census-task-selector" ) ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": task_category, "value": task_category} for task_category in sorted( [ task_category for task_category in data["TASK_CATEGORY"].unique() if task_category ] ) ], multi=True, placeholder="Select Task Category", id="census-task_category-selector" ) ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": clinician, "value": clinician,} for clinician in sorted( [ patient for patient in data[ "ASSIGNED_TO" ].unique() if patient ] ) if clinician ], multi=True, placeholder="Select a Clinician", id="census-clinician-selector", ) ), ddk.ControlItem( dcc.Dropdown( multi=True, placeholder="Select a Patient", id="census-patient-selector", ) ), ddk.ControlItem( dcc.DatePickerRange( id="census-date-picker", min_date_allowed=pd.to_datetime( data["SCHEDULED_DATE"].min() ), max_date_allowed=max_date, initial_visible_month=max_date, start_date=max_date - timedelta(days=30), end_date=max_date, ), ), ddk.ControlItem( html.Button( id="census-select-all-rows", children="Select all matching records", style={"margin": "auto"}, n_clicks=0, ) ), html.Div( [ ddk.Modal( id="census-modal-btn-outer", children=[ html.Button( id="census-expand-modal-2", n_clicks=0, children="Take action", ), ], target_id="census-modal-content", hide_target=True, style={"float": "right"}, ), ], style={"margin": "auto"}, ), ], width=30, style={"overflow": "scroll"}, ), ddk.Card(id="census-time-series"), ] ), #ddk.Row(id="census-pie-charts"), ddk.Card( children=[ ddk.CardHeader( children=[ html.Div( "Table of selected tasks", style={"float": "left"}, ), html.Div( [ ddk.Modal( id="census-modal-btn-outer", children=[ html.Button( id="census-expand-modal", n_clicks=0, children="Take action", ) ], target_id="census-modal-content", hide_target=True, style={"float": "right"}, ), ddk.Block( id="census-modal-content", children=html.Div(id="census-modal-div"), style={ "width": "50%", "margin": "auto", "overflow": "scroll", }, ), ] ), ] ), ddk.Block( ddk.DataTable( columns=[ {"name": i.replace("_", " ").title(), "id": i} for i in data.columns if (i != 'BRANCH') ], filter_action="native", page_action="native", page_size=50, row_selectable="multi", id="census-data-table", style_cell={'fontSize': 12, 'font-family': 'sans-serif'} ), style={"overflow": "scroll"} ), ] ), ] ) return children
def layout(): # load data for display orders_history_data = chart_utils.get_loaded_data("VW_ORDERS_HISTORY_FULL", "DATASET") remove_cols = ['BRANCH', 'COLUMN_MAPPING', 'COLUMN_PARAMETERS'] type_arr = chart_utils.get_options(orders_history_data, "TYPE") physician_arr = chart_utils.get_options(orders_history_data, "PHYSICIAN") patient_arr = chart_utils.get_options(orders_history_data, "TYPE") remove_cols = ['BRANCH', 'PAYOR', 'INTERNAL_REFERRAL_SOURCE',] max_date = datetime.now() pending_df = orders_history_data.loc[ orders_history_data["DATA_SOURCE_ARRAY"].str.contains(r'ORDERSPENDINGMDS', na=True)] history_df = orders_history_data.loc[ orders_history_data["DATA_SOURCE_ARRAY"].str.contains(r'ORDERSHISTORY', na=True)] tbs_df = orders_history_data.loc[ orders_history_data["DATA_SOURCE_ARRAY"].str.contains(r'ORDERSTOBESENT', na=True)] children = html.Div( [ ddk.Row( [ ddk.DataCard( id='orders_tobe_sent_count', value=tbs_df.shape[0], label = 'To Be Sent' ), ddk.DataCard( id='orders_pending_mds_count', value=pending_df.shape[0] , label='Pending MD Signature' ), ddk.DataCard( id='orders_history_count', value=history_df.shape[0] , label='Total Orders' ), ] ), ddk.Row( [ ddk.ControlCard( [ html.Details( [ html.Summary("About this app"), html.P( """Select attributes to fine tune graphs and tables.""" ), ] ), ddk.ControlItem( dcc.Dropdown( options=type_arr, multi=True, placeholder="Select Type", id="orders-type-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=physician_arr, multi=True, placeholder="Select Physician", id="orders-physician-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=patient_arr, multi=True, placeholder="Select Patient", id="orders-patient-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.DatePickerRange( id="orders-date-picker", min_date_allowed=pd.to_datetime( orders_history_data["ORDER_DATE"].min() ), max_date_allowed=max_date, initial_visible_month=max_date, start_date=max_date - timedelta(days=700), end_date=max_date, ), ), ddk.ControlItem( html.Button( id="orders-select-all-rows", children="Select all matching records", style={"margin": "auto"}, n_clicks=0, ) ), ], width=25, style={"overflow": "scroll"}, ), ddk.Card( width=75, children=[ ddk.CardHeader( children=[ html.Div( "Combined Orders View", style={"float": "left"}, ), ] ), ddk.Block( ddk.DataTable( columns=[ {"name": i.replace("_", " ").title(), "id": i} for i in orders_history_data.columns if (i not in remove_cols) ], data=orders_history_data.sort_values(by="PHYSICIAN").to_dict("records"), filter_action="native", page_action="native", page_size=50, row_selectable="multi", id="orders-history-data-table", style_cell={'fontSize': 12, 'font-family': 'sans-serif'}, style_table = {'overflowX': 'auto'}, ), style={"overflow": "scroll"} ), ] ), ] ), ] ) return children
def layout(): # load data for display authorizations_data = chart_utils.get_loaded_data("VW_AUTHORIZATIONS", "DATASET") patient_status_arr = chart_utils.get_options(authorizations_data, "PATIENTSTATUS") discipline_arr = chart_utils.get_options(authorizations_data, "DISCIPLINE") auth_type_arr = chart_utils.get_options(authorizations_data, "AUTHORIZATION_TYPE") payer_arr = chart_utils.get_options(authorizations_data, "PAYER") patient_arr = chart_utils.get_options(authorizations_data, "PATIENT") remove_cols = ['BRANCH','COLUMN_MAPPING', 'COLUMN_PARAMETERS' ] max_date = datetime.now() #pending_df = authorizations_data.loc[authorizations_data["DATA_SOURCE_ARRAY"].str.contains(r'authsPENDINGMDS', na=True)] #history_df = authorizations_data.loc[authorizations_data["DATA_SOURCE_ARRAY"].str.contains(r'authsHISTORY', na=True)] #tbs_df = authorizations_data.loc[ authorizations_data["DATA_SOURCE_ARRAY"].str.contains(r'authsTOBESENT', na=True)] children = html.Div( [ ddk.Row( [ ddk.DataCard( id='auths_patient_status_count', value=12 ,#tbs_df.shape[0], label = 'Patient Status Count' ), ddk.DataCard( id='auths_auth_type_count', value=13,#pending_df.shape[0] , label='Authorization Type Count' ), ddk.DataCard( id='auths_total_count', value=authorizations_data.shape[0] , label='Total Authorizations' ), ] ), ddk.Row( [ ddk.ControlCard( [ html.Details( [ html.Summary("About this app"), html.P( """Select attributes to fine tune graphs and tables.""" ), ] ), ddk.ControlItem( dcc.Dropdown( options=auth_type_arr, multi=True, placeholder="Select Authorization Type", id="auths-auth-type-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=discipline_arr, multi=True, placeholder="Select Discipline", id="auths-discipline-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=patient_arr, multi=True, placeholder="Select Patient", id="auths-patient-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=patient_status_arr, multi=True, placeholder="Select Discipline", id="auths-patientstatus-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=payer_arr, multi=True, placeholder="Select Payer", id="auths-payer-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.DatePickerRange( id="auths-date-picker", min_date_allowed=pd.to_datetime( authorizations_data["START_DATE"].min() ), max_date_allowed=max_date, initial_visible_month=max_date, start_date=max_date - timedelta(days=700), end_date=max_date +timedelta(days=700), ), ), ddk.ControlItem( html.Button( id="auths-select-all-rows", children="Select all matching records", style={"margin": "auto"}, n_clicks=0, ) ), ], width=25, style={"overflow": "scroll"}, ), ddk.Card( width=75, children=[ ddk.CardHeader( children=[ html.Div( "Combined auths View", style={"float": "left"}, ), ] ), ddk.Block( ddk.DataTable( columns=[ {"name": i.replace("_", " ").title(), "id": i} for i in authorizations_data.columns if (i not in remove_cols) ], data=authorizations_data.sort_values(by="START_DATE").to_dict("records"), filter_action="native", page_action="native", page_size=50, row_selectable="multi", id="auths-history-data-table", style_cell={'fontSize': 12, 'font-family': 'sans-serif'}, style_table = {'overflowX': 'auto'}, ), style={"overflow": "scroll"} ), ] ), ] ), ] ) return children
def layout(): # load data for display orders_history_data = chart_utils.get_loaded_data("VIEW_ORDERSHISTORY", "DATASET") orders_pending_mds_data = chart_utils.get_loaded_data("VIEW_ORDERSMANAGEMENT_ORDERSPENDINGMDS", "DATASET") orders_tobe_sent_data = chart_utils.get_loaded_data("VIEW_ORDERSTOBESENT", "DATASET") max_date = datetime.now() order_number_data = pd.concat( [orders_history_data["ORDER_NUMBER"], orders_pending_mds_data["ORDER_NUMBER"], orders_tobe_sent_data["ORDER_NUMBER"]]) physician_data = pd.concat( [orders_history_data["PHYSICIAN"], orders_pending_mds_data["PHYSICIAN"], orders_tobe_sent_data["PHYSICIAN"]]) ordertype_data = pd.concat( [orders_history_data["TYPE"], orders_pending_mds_data["TYPE"], orders_tobe_sent_data["TYPE"]]) patient_data = pd.concat( [orders_history_data["PATIENT"], orders_pending_mds_data["PATIENT"], orders_tobe_sent_data["PATIENT"]]) children = html.Div( [ ddk.Row( [ ddk.DataCard( id='orders_tobe_sent_count', value=orders_tobe_sent_data.shape[0], label = 'To Be Sent' ), ddk.DataCard( id='orders_pending_mds_count', value=orders_pending_mds_data.shape[0] , label='Pending MD Signature' ), ddk.DataCard( id='orders_history_count', value=orders_history_data.shape[0] , label='Total Orders' ), ] ), ddk.Row( [ ddk.ControlCard( [ html.Details( [ html.Summary("About this app"), html.P( """Select attributes to fine tune graphs and tables.""" ), ] ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": orderstype, "value": orderstype} for orderstype in sorted( [ orderstype for orderstype in ordertype_data.unique() if orderstype ] ) ], multi=True, placeholder="Select Type", id="orders-type-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": physician, "value": physician} for physician in sorted( [ physician for physician in physician_data.unique() if physician ] ) ], multi=True, placeholder="Select Physician", id="orders-physician-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": patient, "value": patient} for patient in sorted( [ patient for patient in patient_data.unique() if patient ] ) ], multi=True, placeholder="Select Patient", id="orders-patient-selector" # value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.DatePickerRange( id="order-date-picker", min_date_allowed=pd.to_datetime( orders_history_data["ORDER_DATE"].min() ), max_date_allowed=max_date, initial_visible_month=max_date, start_date=max_date - timedelta(days=30), end_date=max_date, ), ), ddk.ControlItem( html.Button( id="orders_tob_esent-select-all-rows", children="Select all matching records", style={"margin": "auto"}, n_clicks=0, ) ), ], width=30, style={"overflow": "scroll"}, ), ddk.Card( children=[ ddk.CardHeader( children=[ html.Div( "Table of selected tasks", style={"float": "left"}, ), ] ), ddk.Block( ddk.DataTable( columns=[ {"name": i.replace("_", " ").title(), "id": i} for i in orders_history_data.columns if (i != 'BRANCH') ], data=orders_history_data.sort_values(by="PHYSICIAN").to_dict("records"), filter_action="native", page_action="native", page_size=50, row_selectable="multi", id="orders-history-data-table", style_cell={'fontSize': 12, 'font-family': 'sans-serif'} ), style={"overflow": "scroll"} ), ] ), ] ), ] ) return children
def layout(): # load data for display episodicdata = chart_utils.get_loaded_data("AXXESS_API.RAW.MEDICARE_MCRADV_VISITPLANNING_NOAUTH", "DATASET") pervisitdata = chart_utils.get_loaded_data("AXXESS_API.RAW.MANAGEDCARE_VISITPLANNING_NOAUTH", "DATASET") currentepisodic = chart_utils.get_loaded_data("AXXESS_API.RAW.VW_MEDICARE_MCRADV_VISITPLANNING_CURRENT_EPISODES","DATASET") lupa_riskdata = chart_utils.get_loaded_data("AXXESS_API.RAW.VW_MEDICARE_MCRADV_LUPA_RISK", "DATASET") #reorder the columns ''' new_order = ['INS_CODE', 'INITIAL_TIMELY_FILING', 'MRN', 'PATIENT', 'PATIENT_STATUS', 'DATE_OF_BIRTH', 'EPISODE_START_DATE', 'EPISODE_END_DATE', 'PHYSICIAN_NAME', 'PHYSICIAN_PHONE', 'PHYSICIAN_FACSIMILE', 'ORDERS_DETAILS', 'CONSOLIDATED_COMMENTS', 'COLOR', 'USER_UPDATE_DATE', 'NEW_COMMENTS', 'EPISODE_UNEARNED_AMOUNT', 'EPISODE_EARNED_AMOUNT', 'EPISODE_BILLED_AMOUNT', 'EPISODE_ADJUSTMENTS' ] ''' gl_mrn_arr = chart_utils.get_options(episodicdata, "MRN") gl_ins_code_arr = chart_utils.get_options(episodicdata, "INS_CODE") gl_patient_arr = chart_utils.get_options(episodicdata, "PATIENT") gl_patient_status_arr = chart_utils.get_options(episodicdata, "PATIENT_STATUS") gl_pcc_arr = chart_utils.get_options(currentepisodic, "CASE_MANAGER_NAME") gl_lupa_risk_arr = chart_utils.get_options(currentepisodic, "LUPA_RISK") remove_cols = ['INS_CODE', 'OASIS_STATUS', 'OASIS_DETAILS', 'EPISODE_PRIMARY_INSURANCE_NAME', 'DATE_OF_BIRTH', 'PHONE','PHYSICIAN_FACSIMILE', 'PHYSICIAN_NAME', 'PHYSICIAN_PHONE', 'ZIP', 'ORDERS_STATUS', 'ORDERS_DETAILS', 'EARLY_LUPA_RISK', 'LATE_LUPA_RISK', 'EARLY_ORIGINAL_PROSPECTIVE_PAY', 'LATE_ORIGINAL_PROSPECTIVE_PAY', 'TOTAL_COST', 'TOTAL_PROFIT', 'EARLY_COST', 'EARLY_PROFIT', 'LATE_COST', 'LATE_PROFIT', 'EPISODE_BILLED_AMOUNT', 'EPISODE_ADJUSTMENTS', 'EPISODE_EARNED_AMOUNT', 'EPISODE_UNEARNED_AMOUNT', 'SCHEDULE_ACTIVE', 'COMPLETED_VISITS', 'TOTAL_VISITS' , 'TOTAL_BILLABLE_HHA_VISITS' ] max_date = pd.to_datetime(episodicdata['EPISODE_END_DATE']).max() today = dt.now().date() sixtydaysprior = today sixtydaysprior += datetime.timedelta(days=-60) #min_date = pd.to_datetime(episodicdata['EPISODE_END_DATE']).min() children = html.Div([ # block on the right ddk.Block( width=100, children=[ ddk.Row([ ddk.Block( children=[ ddk.ControlCard( orientation='horizontal', width = 100, children=[ ddk.ControlItem( dcc.Dropdown( options=gl_ins_code_arr, multi=True, placeholder="Select", id="vp-ins-code-selector", # value=["Not Yet Started", "Saved"], style = { 'fontSize': 12, 'font-family': 'sans-serif', } ), width = 10, label='Billing Code', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ddk.ControlItem( dcc.Dropdown( options=gl_patient_arr, multi=True, placeholder="Select", id="vp-patient-selector", style = { 'fontSize': 12, 'font-family': 'sans-serif', } ), width=10, label='Patient', label_text_alignment='center', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ddk.ControlItem( dcc.Dropdown( options=gl_mrn_arr, multi=True, placeholder="Select", id="vp-mrn-selector", style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), width =10, label='MRN', label_text_alignment='center', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ddk.ControlItem( dcc.Dropdown( options=gl_patient_status_arr, id="vp-patient-status-selector", multi=True, placeholder="Select", value=['Active'], style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), width = 10, label = 'Patient Status', label_text_alignment='center', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ddk.ControlItem( dcc.Slider( id='vp-margin-slider', min=-50, max=100, step=10, marks={-50: '-50', -40: '-40', -20: '-20', -10: '-10', 0: '0', 10: '10', 20: '20', 40: '40', 60: '60', 80: '80', 100: '100', }, value=20, ), width = 20, label='Margin (%)', label_text_alignment='center', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ddk.ControlItem( dcc.Dropdown( options=gl_pcc_arr, multi=True, placeholder="select", id="vp-case-manager-selector", style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), width=10, label='Case Manager', label_text_alignment= 'center', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ddk.ControlItem( dcc.DatePickerRange( id="vp-episode-picker", min_date_allowed=pd.to_datetime(episodicdata['EPISODE_START_DATE'].min() ), max_date_allowed=max_date, initial_visible_month=max_date, start_date=sixtydaysprior, end_date=max_date ), width = 20, label='Episode Range', label_text_alignment='center', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ddk.ControlItem( dcc.Dropdown( options=gl_lupa_risk_arr, multi=True, placeholder="select", id="vp-lupa-risk-selector", style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), width=10, label='LUPA RISK', label_text_alignment='center', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ], ) ] ), ]), ddk.Row([ ddk.Card( children=[ ddk.CardHeader( title="VISIT PLANNING", children=[ html.Div( [ ddk.Modal( id="vp-modal-btn-outer", children=[ html.Button( id="vp-expand-modal", n_clicks=0, children="Take action", ) ], target_id="vp-modal-content", hide_target=True, style={"float": "right"}, ), ddk.Block( id="vp-modal-content", children=html.Div(id="vp-modal-div"), style={ "width": "50%", "margin": "auto", "overflow": "scroll", }, ), ddk.DataCard( id='vp_episodic_selected_count', value=currentepisodic.shape[0], label='Episodic Selected Count', style={ 'fontSize': 12, 'font-family': 'sans-serif', } ), ] ), ], ), ddk.Block( dcc.Tabs(id='tabs-example', value='tab-1', children=[ dcc.Tab(label='EPISODIC', children=[generate_table_layout(episodicdata, "","vp_episodic-table", "MRN", remove_cols)] ), dcc.Tab(label='PERVISIT', children=[generate_table_layout(pervisitdata, "","vp_pervisit-table", "MRN", remove_cols)]), ] ), ) ] ), ]), ] ) ]) return children
"width": "auto", }, ), ddk.Title('NRC IRAP - Corporate Funding in Canada from 2018-2020'), ]), # end of ddk.Header ddk.Block( # left-hand column width=20, children=[ dcc.Tabs([ dcc.Tab( label='Map Filters', children=[ ddk.ControlCard( id='map-controls', children=[ ddk.CardHeader(title='Search for Funding'), ddk.ControlItem(dcc.Dropdown( id='province-dropdown', options=[{ 'label': i, 'value': i } for i in province_list], multi=True, clearable=False, value=province_list), label='Province'), ddk.ControlItem(dcc.Dropdown( id='naics-dropdown', options=[{ 'label': i, 'value': i
def generate_table_layout(table_df, title, tableid, sort_cols, remove_cols): children = html.Div( [ ddk.Card( children=[ ddk.CardHeader( children=[ html.Div( title, style={"float": "left"}, ), ] ), ddk.Block( ddk.DataTable( columns=[ {"name": i.replace("_", " ").title(), "id": i} for i in table_df.columns if (i not in remove_cols) ], data=table_df.sort_values(by=sort_cols).to_dict("records"), filter_action="native", sort_action="native", page_action="native", # page_size=10, row_selectable="multi", id=tableid, style_cell={ 'height': 'auto', # all three widths are needed # 'minWidth': '180px', 'width': '180px', 'maxWidth': '180px', 'fontSize': 12, 'font-family': 'sans-serif', 'whiteSpace': 'pre', #'wordBreak': 'break-all', 'textAlign': 'center' }, style_cell_conditional=[ { 'if': {'column_id': c}, 'textAlign': 'left' } for c in ['ORDERS_DETAILS', 'OASIS_DETAILS', 'AUTH #|AUTH TYPE|RANGE|DISCIPLINE|AUTHORIZED|USED|UNUSED|UNITS'] ] + [ { 'if': {'column_id': c}, 'width': '100px', 'textAlign': 'right' } for c in ['1-30 days Disc: T/S/C/M','31-60 days Disc: T/S/C/M', 'Visits Disc: T/S/C/M'] ] + [{'if': {'column_id': 'CONSOLIDATED_COMMENTS'}, 'width': '100px', 'whiteSpace': 'normal', 'textAlign': 'left' }, {'if': {'column_id': 'MRN'}, 'width': '90px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'INS_CODE'}, 'width': '40px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'PATIENT_STATUS'}, 'width': '60px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'INSURANCE'}, 'width': '60px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'PATIENT'}, 'width': '60px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'EPISODE_START_DATE'}, 'width': '70px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'EPISODE_END_DATE'}, 'width': '70px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'AUTH_REQUIRED'}, 'width': '45px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'EPISODE_UNEARNED_AMOUNT'}, 'width': '70px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'EPISODE_EARNED_AMOUNT'}, 'width': '70px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'EPISODE_BILLED_AMOUNT'}, 'width': '70px', 'whiteSpace': 'normal', 'textAlign': 'center' }, {'if': {'column_id': 'EPISODE_ADJUSTMENTS'}, 'width': '70px', 'whiteSpace': 'normal', 'textAlign': 'center' }, ], style_data_conditional=[ { 'if': {'row_index': 'odd'}, 'backgroundColor': 'rgb(248, 248, 248)' } ] + [ {'if': {'column_id': 'TOTAL_MARGIN', 'filter_query': '{TOTAL_MARGIN} < 20'}, 'color': 'red'} ], style_header={ 'backgroundColor': 'rgb(230, 230, 230)', 'fontWeight': 'bold', 'whiteSpace': 'normal', 'textAlign': 'center' }, style_table={'overflowX': 'auto', 'overflowY': 'scroll'}, #style_table={'overflowX': 'auto', 'maxHeight': '400px', 'overflowY': 'scroll'}, ), style={"overflow": "scroll"} ), ] ), ] ) return children
import dash import dash_design_kit as ddk import plotly.express as px import pandas as pd app = dash.Dash(__name__) server = app.server # expose server variable for Procfile df = pd.DataFrame({ "Fruit": ["Apples", "Oranges", "Bananas", "Apples", "Oranges", "Bananas"], "Amount": [4, 1, 2, 2, 4, 5], "City": ["SF", "SF", "SF", "Montreal", "Montreal", "Montreal"] }) fig = px.bar(df, x="Fruit", y="Amount", color="City", barmode="group") app.layout = ddk.App( show_editor=True, children=[ ddk.Header([ddk.Title('Hello Dash')]), ddk.Card(children=[ ddk.CardHeader( title='Dash: A Web application framework for Python.'), ddk.Graph(figure=fig) ]) ])
def layout(): # load data for display episodesummdata = chart_utils.get_loaded_data( "AXXESS_API.USER_INPUTS.VW_PENDING_ORDERS_TF_SIMPLE", "DATASET") #reorder the columns new_order = [ 'INS_CODE', 'INITIAL_TIMELY_FILING', 'MRN', 'PATIENT', 'PATIENT_STATUS', 'DATE_OF_BIRTH', 'EPISODE_START_DATE', 'EPISODE_END_DATE', 'PHYSICIAN_NAME', 'PHYSICIAN_PHONE', 'PHYSICIAN_FACSIMILE', 'ORDERS_DETAILS', 'CONSOLIDATED_COMMENTS', 'COLOR', 'USER_UPDATE_DATE', 'NEW_COMMENTS', 'EPISODE_UNEARNED_AMOUNT', 'EPISODE_EARNED_AMOUNT', 'EPISODE_BILLED_AMOUNT', 'EPISODE_ADJUSTMENTS' ] episodesummdata = episodesummdata[new_order] claimsdetailsdata = chart_utils.get_loaded_data( "AXXESS_API.RAW.VW_ALLPAYOR_BILLING_CLAIMS_DETAILS", "DATASET") # print(episodesummdata.columns) # print(claimsdetailsdata.columns) gl_mrn_arr = chart_utils.get_options(episodesummdata, "MRN") gl_ins_code_arr = chart_utils.get_options(episodesummdata, "INS_CODE") gl_patient_arr = chart_utils.get_options(episodesummdata, "PATIENT") gl_patient_status_arr = chart_utils.get_options(episodesummdata, "PATIENT_STATUS") remove_cols = ['BRANCH', 'COLUMN_MAPPING', 'COLUMN_PARAMETERS'] max_date = pd.to_datetime(episodesummdata['EPISODE_END_DATE']).max() min_date = pd.to_datetime(episodesummdata['EPISODE_END_DATE']).min() children = html.Div([ # block on the right ddk.Block( width=100, children=[ ddk.Row([ ddk.Block(children=[ ddk.ControlCard( orientation='horizontal', width=100, children=[ html.Details([ html.Summary("Filter here"), html. P("""Select attributes to fine tune tables.""" ), ]), ddk.ControlItem( dcc.Dropdown( options=gl_ins_code_arr, multi=True, placeholder="Select Ins code", id="op-ins-code-selector" # value=["Not Yet Started", "Saved"], )), ddk.ControlItem( dcc.Dropdown( options=gl_patient_arr, multi=True, placeholder="Select Patient", id="op-patient-selector" # value=["Not Yet Started", "Saved"], )), ddk.ControlItem( dcc.Dropdown( options=gl_mrn_arr, multi=True, placeholder="Select MRN", id="op-mrn-selector" # value=["Not Yet Started", "Saved"], )), ddk.ControlItem( dcc.DatePickerRange( id="op-episode-picker", min_date_allowed=pd.to_datetime( episodesummdata[ 'EPISODE_START_DATE'].min()), max_date_allowed=max_date, initial_visible_month=max_date, start_date=min_date, end_date=max_date), ), ddk.ControlItem( html.Button( id="op-select-all-rows", children="Select all matching records", style={"margin": "auto"}, n_clicks=0, )), ], ) ]), ]), ddk.Row([ ddk.Card(children=[ ddk.CardHeader( title="Pending Orders", children=[ html.Div([ ddk.Modal( id="op-modal-btn-outer", children=[ html.Button( id="op-expand-modal", n_clicks=0, children="Take action", ) ], target_id="op-modal-content", hide_target=True, style={"float": "right"}, ), ddk.Block( id="op-modal-content", children=html.Div(id="op-modal-div"), style={ "width": "50%", "margin": "auto", "overflow": "scroll", }, ), ]), ], ), ddk.Block(children=[ generate_table_layout( episodesummdata, "PENDING ORDERS", "pending_tf-table", "MRN", remove_cols) ]) ]), ]), ddk.Row([ ddk.Block(children=[ generate_table_layout( claimsdetailsdata, "CLAIMS DETAILS", "op_claims_details-table", "MRN", remove_cols) ]) ]), ]) ]) return children
def Graphs(): df_streamtube = ddk.datasets.df_streamtube() df_choropleth = ddk.datasets.df_choropleth() df_scattergeo = ddk.datasets.df_scattergeo() df_iris = ddk.datasets.df_iris() x = [1, 2, 3] labels = ['Montreal', 'Tofu Bowl', 'Tropical Beaches'] labels_long = [ 'Montreal', 'New York City', 'Tokyo', 'Cincinatti', 'Miami', 'London', 'Vancouver' ] values_long = [1, 2, 3, 1, 5, 6, 7] y1 = [3, 1, 2] y2 = [4, 10, 4] y3 = [5, 2, 3] y4 = [9, 3, 8] y5 = [10, 5, 12] y6 = [11, 8, 10] y7 = [1, 2, 1] y8 = [5, 3, 1] z = [5, 3, 1] matrix = [ [1, 2, 3], [4, 1, 2], [1, 3, 4] ] open = [33.0, 33.3, 33.5, 33.0, 34.1] high = [33.1, 33.3, 33.6, 33.2, 34.8] low = [32.7, 32.7, 32.8, 32.6, 32.8] close = [33.0, 32.9, 33.3, 33.1, 33.1] dates = [dt(year=2013, month=10, day=10), dt(year=2013, month=11, day=10), dt(year=2013, month=12, day=10), dt(year=2014, month=1, day=10), dt(year=2014, month=2, day=10)] r = [0.5, 1, 2, 2.5, 3, 4] theta = [35, 70, 120, 155, 205, 240] datas = [ [ {'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines'}, ], [ {'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y3, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y4, 'mode': 'lines'}, ], [ {'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y3, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y4, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y5, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y6, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y7, 'mode': 'lines'}, {'type': 'scatter', 'x': x, 'y': y8, 'mode': 'lines'}, ], [ {'type': 'scatter', 'x': x, 'y': y1, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y2, 'mode': 'markers'}, ], [ {'type': 'scatter', 'x': x, 'y': y1, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y2, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y3, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y4, 'mode': 'markers'}, ], [ {'type': 'scatter', 'x': x, 'y': y1, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y2, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y3, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y4, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y5, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y6, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y7, 'mode': 'markers'}, {'type': 'scatter', 'x': x, 'y': y8, 'mode': 'markers'}, ], [ { 'type': 'scatter', 'x': x, 'y': y1, 'marker': {'color': y2}, 'mode': 'markers' }, ], [ {'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines+markers'}, {'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines+markers'}, ], [ {'type': 'bar', 'x': labels, 'y': y1}, {'type': 'bar', 'x': labels, 'y': y2}, ], [ {'type': 'bar', 'x': labels, 'y': y1}, {'type': 'bar', 'x': labels, 'y': y2}, {'type': 'bar', 'x': labels, 'y': y3}, {'type': 'bar', 'x': labels, 'y': y4}, ], [ {'type': 'bar', 'x': labels, 'y': y1}, {'type': 'bar', 'x': labels, 'y': y2}, {'type': 'bar', 'x': labels, 'y': y3}, {'type': 'bar', 'x': labels, 'y': y4}, {'type': 'bar', 'x': labels, 'y': y5}, {'type': 'bar', 'x': labels, 'y': y6}, {'type': 'bar', 'x': labels, 'y': y7}, {'type': 'bar', 'x': labels, 'y': y8}, ], [ {'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines', 'fill': 'tonexty'}, {'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines', 'fill': 'tonexty'}, ], [ {'type': 'heatmap', 'z': matrix} ], [ {'type': 'contour', 'z': matrix} ], [ {'type': 'histogram2d', 'x': x, 'y': y1} ], [ {'type': 'histogram2dcontour', 'x': x, 'y': y1} ], [ {'type': 'pie', 'labels': labels, 'values': y1} ], [ {'type': 'pie', 'labels': labels_long, 'values': values_long} ], [ {'type': 'box', 'y': y1}, {'type': 'box', 'y': y2} ], [ {'type': 'box', 'y': y1, 'boxpoints': 'all'}, {'type': 'box', 'y': y2, 'boxpoints': 'all'} ], [ {'type': 'violin', 'y': y1}, {'type': 'violin', 'y': y2} ], [ {'type': 'violin', 'y': y1, 'points': 'all'}, {'type': 'violin', 'y': y2, 'points': 'all'} ], [ {'type': 'histogram', 'y': y1} ], [ {'type': 'scatter3d', 'x': x, 'y': y1, 'z': z, 'mode': 'markers'}, {'type': 'scatter3d', 'x': x, 'y': y2, 'z': z, 'mode': 'markers'} ], [ {'type': 'scatter3d', 'x': x, 'y': y1, 'z': z, 'mode': 'lines'}, {'type': 'scatter3d', 'x': x, 'y': y2, 'z': z, 'mode': 'lines'} ], [ {'type': 'scatter3d', 'x': x, 'y': y1, 'z': z, 'mode': 'markers+lines'}, {'type': 'scatter3d', 'x': x, 'y': y2, 'z': z, 'mode': 'markers+lines'} ], [ {'type': 'surface', 'z': matrix} ], [ { 'type': 'cone', 'x': [row[0] for row in cone_data], 'y': [row[1] for row in cone_data], 'z': [row[2] for row in cone_data], 'u': [row[3] for row in cone_data], 'v': [row[4] for row in cone_data], 'w': [row[5] for row in cone_data], } ], [ { 'type': 'streamtube', 'x': df_streamtube['x'], 'y': df_streamtube['y'], 'z': df_streamtube['z'], 'u': df_streamtube['u'], 'v': df_streamtube['v'], 'w': df_streamtube['w'], 'sizeref': 0.5 } ], [ { 'type': 'choropleth', 'z': df_choropleth['GDP (BILLIONS)'], 'locations': df_choropleth['CODE'], 'text': df_choropleth['COUNTRY'] } ], [ { 'type': 'scattergeo', 'lon': df_scattergeo['long'], 'lat': df_scattergeo['lat'], 'mode': 'markers', } ], [ { 'type': 'scattermapbox', 'lon': df_scattergeo['long'], 'lat': df_scattergeo['lat'], 'mode': 'markers', } ], [ { 'type': 'candlestick', 'open': open, 'high': high, 'low': low, 'close': close } ], [ { 'type': 'ohlc', 'open': open, 'high': high, 'low': low, 'close': close } ], [ {'type': 'scatterternary', 'a': x, 'b': y1, 'c': y2, 'mode': 'markers'}, ], [ {'type': 'scatterternary', 'a': x, 'b': y1, 'c': y2, 'mode': 'lines'}, ], [ {'type': 'scatterpolar', 'r': r, 'theta': theta, 'mode': 'markers'}, ], [ {'type': 'scatterpolar', 'r': r, 'theta': theta, 'mode': 'lines'}, ], [ dict( type='parcoords', dimensions=list([ dict(range=[0,8], constraintrange=[4,8], label='Sepal Length', values=df_iris['sepal_length']), dict(range=[0,8], label='Sepal Width', values=df_iris['sepal_width']), dict(range=[0,8], label='Petal Length', values=df_iris['petal_length']), dict(range=[0,8], label='Petal Width', values=df_iris['petal_width']) ]) ) ], [ dict( type='sankey', node=dict( label=["Nuclear", "Wind Energy", "Thermal", "Bio Conversion", "Airline Industry", "Losses"], ), link=dict( source=[0, 1, 0, 2, 3, 3], target=[2, 3, 3, 4, 4, 5], value=[8, 4, 2, 8, 4, 2] ) ) ], [ { 'type': 'carpet', 'a': [4, 4, 4, 4.5, 4.5, 4.5, 5, 5, 5, 6, 6, 6], 'b': [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3], 'y': [2, 3.5, 4, 3, 4.5, 5, 5.5, 6.5, 7.5, 8, 8.5, 10], } ], [ { 'type': 'contourcarpet', 'a': [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], 'b': [4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6], 'z': [1, 1.96, 2.56, 3.0625, 4, 5.0625, 1, 7.5625, 9, 12.25, 15.21, 14.0625], }, { 'type': 'carpet', 'a': [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3], 'b': [4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6], 'x': [2, 3, 4, 5, 2.2, 3.1, 4.1, 5.1, 1.5, 2.5, 3.5, 4.5], 'y': [1, 1.4, 1.6, 1.75, 2, 2.5, 2.7, 2.75, 3, 3.5, 3.7, 3.75], } ] ] return html.Div([ ddk.Card(width=25, children=[ ddk.CardHeader(title=data[0]['type']), ddk.Graph( id='graph-{}'.format(i), figure={ 'data': data, 'layout': { 'title': 'Hello World', } } ) ]) for (i, data) in enumerate(datas) ])
def layout(): data = chart_utils.get_loaded_data("SCHEDULEREPORTS_VISITSBYSTATUS","DATASET") remove_cols = ['BRANCH','COLUMN_MAPPING', 'COLUMN_PARAMETERS'] max_date = datetime.now() children = html.Div( [ ddk.Row( [ ddk.ControlCard( [ html.Details( [ html.Summary("About this app"), html.P( """Select attributes to fine tune graphs and tables.""" ), ] ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": status, "value": status,} for status in sorted( [ patient for patient in data["STATUS"].unique() if patient ] ) ], multi=True, placeholder="Select Status", id="status-selector", value=["Not Yet Started", "Saved"], ) ), ddk.ControlItem( dcc.Dropdown( options=[ {"label": clinician, "value": clinician,} for clinician in sorted( [ patient for patient in data[ "ASSIGNED_TO" ].unique() if patient ] ) if clinician ], multi=True, placeholder="Select a Clinician", id="clinician-selector", ) ), ddk.ControlItem( dcc.Dropdown( multi=True, placeholder="Select a Patient", id="patient-selector", ) ), ddk.ControlItem( dcc.DatePickerRange( id="date-picker", min_date_allowed=pd.to_datetime( data["SCHEDULED_DATE"].min() ), max_date_allowed=max_date, initial_visible_month=max_date, start_date=max_date - timedelta(days=30), end_date=max_date, ), ), ddk.ControlItem( html.Button( id="select-all-rows", children="Select all matching records", style={"margin": "auto"}, n_clicks=0, ) ), html.Div( [ ddk.Modal( id="modal-btn-outer", children=[ html.Button( id="expand-modal-2", n_clicks=0, children="Take action", ), ], target_id="modal-content", hide_target=True, style={"float": "right"}, ), ], style={"margin": "auto"}, ), ], width=30, style={"overflow": "scroll"}, ), ddk.Card(id="time-series"), ] ), ddk.Row(id="pie-charts"), ddk.Card( children=[ ddk.CardHeader( title="Table of selected tasks", children=[ html.Div( [ ddk.Modal( id="modal-btn-outer", children=[ html.Button( id="expand-modal", n_clicks=0, children="Take action", ) ], target_id="modal-content", hide_target=True, style={"float": "right"}, ), ddk.Block( id="modal-content", children=html.Div(id="modal-div"), style={ "width": "50%", "margin": "auto", "overflow": "scroll", }, ), ] ), ], ), ddk.Block( ddk.DataTable( columns=[ {"name": i.replace("_", " ").title(), "id": i} for i in data.columns if (i not in remove_cols) ], data = data.sort_values(by="SCHEDULED_DATE").to_dict("records"), filter_action="native", page_action="native", page_size=25, row_selectable="multi", id="data-table", style_cell={'fontSize': 12, 'font-family': 'sans-serif'} ), style={"overflow": "scroll"} ), ] ), ] ) return children