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
