class DatasetIntegrityView(View):
TITLE = "Dataset Integrity Overview"
N_COLUMNS = 3
N_ROWS = 2
def __init__(self, parent, controller):
super().__init__(parent, controller)
self.state_bar = StateBar(self, controller.status)
self.table = Table(self, controller.overview)
self.update_button = tk.Button(self,
text="Check for update",
command=Callback(
self.controller.update_app))
self.layout()
def layout(self):
self.navigation.grid(row=0,
column=0,
columnspan=self.N_COLUMNS,
sticky="we")
self.title.grid(row=1, column=0)
self.state_bar.grid(row=1, column=1)
self.update_button.grid(row=1, column=2)
self.table.grid(row=2,
column=0,
columnspan=self.N_COLUMNS,
pady=(25, ))
self.make_flexible(n_rows=self.N_ROWS, n_cols=self.N_COLUMNS)
self.grid(row=0, column=0, sticky="nsew")
def update(self):
self.state_bar.update(self.controller.status)
self.table.update(self.controller.overview)
def exposure_summary_page(exposure):
page = html.Div([
Header(),
html.Div([
HalfRowCard("TIV by State",
Table(exposure.tiv_by_state(), display_header=True)),
HalfRowCard("TIV by State",
TIVBarGraph(exposure.tiv_by_state(), "State"))
],
className="row "),
html.Div([
HalfRowCard(
"TIV by Occupancy",
Table(exposure.tiv_by_occupancy(), display_header=True)),
HalfRowCard("TIV by Occupancy",
TIVBarGraph(exposure.tiv_by_occupancy(), "Occupancy"))
],
className="row "),
html.Div([
HalfRowCard(
"TIV by State",
Table(exposure.tiv_by_construction(), display_header=True)),
HalfRowCard(
"TIV by State",
TIVBarGraph(exposure.tiv_by_construction(), "Construction"))
],
className="row "),
],
className="container")
return page
def __init__(self, parent, controller):
super().__init__(parent, controller)
self.state_bar = StateBar(self, controller.status)
self.table = Table(self, controller.overview)
self.update_button = tk.Button(self,
text="Check for update",
command=Callback(
self.controller.update_app))
self.layout()
def overview_page(summary, company_facts, key_losses):
page = html.Div([
Header(),
html.Div([
HalfRowCard("Summary", TextArea(summary, "summary")),
HalfRowCard("Key Info", Table(company_facts))
],
className="row"),
html.Div([
FullRowCard("Key Losses", Table(key_losses, display_header=True))
],
className="row")
],
className="container")
return page
def ep_curve_page(ep_curves):
page = html.Div([
Header(),
html.Div([
HalfRowCard("EP all peril", Table(ep_curves.get_ep_curves(['netprecat'], ['ALL'], ['AEP', 'OEP']), display_header=True)),
HalfRowCard("EP all peril", EPGraph(ep_curves.get_ep_curves(['netprecat'], ['ALL'], ['AEP', 'OEP'])))
], className="row "),
html.Div([
HalfRowCard("EP Windstorm", Table(ep_curves.get_ep_curves(['netprecat'], ['Windstorm'], ['AEP', 'OEP']), display_header=True)),
HalfRowCard("EP Windstorm", EPGraph(ep_curves.get_ep_curves(['netprecat'], ['Windstorm'], ['AEP', 'OEP'])))
], className="row "),
html.Div([
HalfRowCard("EP Earthquake", Table(ep_curves.get_ep_curves(['netprecat'], ['Earthquake'], ['AEP', 'OEP']), display_header=True)),
HalfRowCard("EP Earthquake", EPGraph(ep_curves.get_ep_curves(['netprecat'], ['Earthquake'], ['AEP', 'OEP'])))
], className="row "),
], className="container")
return page
def add_data_table(self, identifier, dataframe, name, plot_options=None):
"""add a datatable to the root-level section
Args:
identifier (str): MP category ID (`mp_cat_id`)
dataframe (pandas.DataFrame): tabular data as Pandas DataFrame
name (str): table name, optional if only one table in section
plot_options (dict): options for according plotly graph
"""
# TODO: optional table name, required if multiple tables per root-level section
table_start = mp_level01_titles[1] + '_'
if not name.startswith(table_start):
name = table_start + name
name = ''.join([replacements.get(c, c) for c in name])
self.document.rec_update(
nest_dict(Table(dataframe).to_dict(), [identifier, name]))
self.document[identifier].insert_default_plot_options(
dataframe, name, update_plot_options=plot_options)
from utils import Data
from constants import peak_values_and_dates, slope_changes_and_dates, insights
from components import DatePickerRange, Table, BarPlot, BoxPlot, InteractivePlot
import dash_html_components as html
from dash.dependencies import Input, Output
from datetime import datetime
## Data Loading
data = Data()
prepared_data = data.retrieve_prepared_data()
splitted_data = data.retrieve_splitted_date_data()
# Importing components
date_picker_range = DatePickerRange()
table = Table()
bar_plot = BarPlot()
box_plot = BoxPlot()
interactive_plot = InteractivePlot()
## App Layout
app.layout = html.Div(
[
html.H1('Data Report',
style={
'textAlign': 'center',
'background': '7f44f8',
'color': 'white'
}),
html.Div([
'Date selector for the interactive graphic',
open('./assets/data_remaining_persons.pkl', 'rb'))
remaining_places = pickle.load(open('./assets/data_remaining_places.pkl',
'rb'))
cos_sim_matrix = pd.read_pickle("./assets/data_cosine_similarity_matrix.pkl")
overview = html.Div(
id="body1",
children=[
Header("overview"),
html.Div(id="ColumnBlockOverview",
children=[
Scatter(overview_tsne),
BarOverview(overview_persons),
html.Div(id="tableHeadline",
children=[html.H4(["Collection of Books"])]),
Table(author_data[["Title", "Author",
"Publishing Date"]]),
]),
html.Div(id="MapBlock", children=[Map(overview_places)])
])
book = html.Div(
id="body1",
children=[
Header("book"),
Dropdown("book", list(specific_entities.keys())),
html.Div(id="ColumnBlockBook",
children=[
Author(),
html.Div(
id="specTitBox",
children=[html.H1(id="specificTitle", children=[])]),