historic chart and filter form updated

dm_regional_app/charts.py

@@ -19,9 +19,19 @@ def prediction_chart(prediction: Prediction):
 def historic_chart(data: PopulationStats):
  df_pp = data.stock.unstack().reset_index()
  df_pp.columns = ["from", "date", "value"]
+ df = df_pp[["date", "value"]].groupby(by="date").sum().reset_index()
 
  # visualise prediction using unstacked dataframe
- fig = px.line(df_pp, y="value", x="date", color="from")
- fig.update_layout(title="Prediction")
+ fig = px.line(
+ df,
+ y="value",
+ x="date",
+ labels={
+ "value": "Number of children",
+ "date": "Date",
+ },
+ )
+ fig.update_layout(title="Historic data")
+ fig.update_yaxes(rangemode="tozero")
  fig_html = fig.to_html(full_html=False)
  return fig_html

dm_regional_app/forms.py

@@ -3,6 +3,7 @@
 from crispy_forms.helper import FormHelper
 from crispy_forms.layout import Column, Layout, Row, Submit
 from django import forms
+from django_select2 import forms as s2forms
 
 
 class PredictFilter(forms.Form):
@@ -29,35 +30,58 @@ class HistoricDataFilter(forms.Form):
  label="End Date",
  required=True,
  )
- la = forms.ChoiceField(label="Local Authority", required=False, choices=[])
+ la = forms.MultipleChoiceField(
+ widget=s2forms.Select2MultipleWidget,
+ label="Local Authority",
+ required=False,
+ choices=[],
+ )
  placement_types = forms.MultipleChoiceField(
- widget=forms.CheckboxSelectMultiple,
+ widget=s2forms.Select2MultipleWidget,
  label="Placement Type",
  required=False,
  choices=[],
  )
+ age_bins = forms.MultipleChoiceField(
+ widget=s2forms.Select2MultipleWidget,
+ label="Age",
+ required=False,
+ choices=[],
+ )
+ uasc = forms.ChoiceField(
+ label="UASC",
+ required=False,
+ choices=[("all", "All"), (True, "UASC only"), (False, "Exclude UASC")],
+ initial="all",
+ )
 
  def __init__(self, *args, **kwargs):
  la_choices = kwargs.pop("la_choices")
  placement_type_choices = kwargs.pop("placement_type_choices")
+ age_bin_choices = kwargs.pop("age_bin_choices")
 
  super().__init__(*args, **kwargs)
- self.fields["la"].choices = [("all", "All")] + [(la, la) for la in la_choices]
- self.fields["la"].initial = "all"
+ self.fields["la"].choices = [(la, la) for la in la_choices]
  self.fields["placement_types"].choices = [
  (placement_type, placement_type)
  for placement_type in placement_type_choices
  ]
+ self.fields["age_bins"].choices = [
+ (age_bin, age_bin) for age_bin in age_bin_choices
+ ]
+
  self.helper = FormHelper()
  self.helper.layout = Layout(
  Row(
- Column("start_date", css_class="form-group col-md-6 mb-0"),
- Column("end_date", css_class="form-group col-md-6 mb-0"),
+ Column("start_date", css_class="form-group col-md-3 mb-0"),
+ Column("end_date", css_class="form-group col-md-3 mb-0"),
  css_class="form-row",
  ),
  Row(
- Column("la", css_class="form-group col-md-6 mb-0"),
- Column("placement_types", css_class="form-group col-md-4 mb-0"),
+ Column("la", css_class="form-group col-md-3 mb-0"),
+ Column("placement_types", css_class="form-group col-md-3 mb-0"),
+ Column("age_bins", css_class="form-group col-md-3 mb-0"),
+ Column("uasc", css_class="form-group col-md-3 mb-0"),
  css_class="form-row",
  ),
  Submit("submit", "Filter"),
@@ -72,8 +96,9 @@ def filter_by_end_date(self, data: pd.DataFrame):
  return data
 
  def filter_by_la(self, data: pd.DataFrame):
- if self.cleaned_data["la"] != "all":
- data = data.loc[data.LA == self.cleaned_data["la"]]
+ if self.cleaned_data["la"] != []:
+ loc = data.LA.astype(str).isin(self.cleaned_data["la"])
+ data = data.loc[loc]
  return data
 
  def filter_by_placement_type(self, data: pd.DataFrame):
@@ -84,9 +109,24 @@ def filter_by_placement_type(self, data: pd.DataFrame):
  data = data.loc[loc]
  return data
 
+ def filter_by_age_bin(self, data: pd.DataFrame):
+ if self.cleaned_data["age_bins"] != []:
+ loc = data.age_bin.astype(str).isin(self.cleaned_data["age_bins"])
+ data = data.loc[loc]
+ return data
+
+ def filter_by_uasc(self, data: pd.DataFrame):
+ if self.cleaned_data["uasc"] == "True":
+ data = data.loc[data.UASC == True]
+ elif self.cleaned_data["uasc"] == "False":
+ data = data.loc[data.UASC == True]
+ return data
+
  def apply_filters(self, data: pd.DataFrame):
  data = self.filter_by_start_date(data)
  data = self.filter_by_end_date(data)
  data = self.filter_by_la(data)
  data = self.filter_by_placement_type(data)
+ data = self.filter_by_age_bin(data)
+ data = self.filter_by_uasc(data)
  return data

dm_regional_app/management/commands/sandbox.py

@@ -24,4 +24,8 @@ def handle(self, *args, **kwargs):
  dc = DemandModellingDataContainer(datastore, config)
  pop = PopulationStats(dc.enriched_view, config)
 
- print(pop.stock)
+ data = dc.enriched_view
+ print(data.loc[data.UASC == True])
+
+ # print(pop.stock)
+ # print(dc.enriched_view)

dm_regional_app/templates/dm_regional_app/views/historic.html

@@ -1,23 +1,32 @@
 {% extends "dm_regional_app/base.html" %}
 {% load crispy_forms_tags %}
 {% block content %}
+ <br>
+ <h1>Viewing the SSDA903 data</h1>
+ <br>
+ <p>Explore the make-up of the care population as represented in the SSDA903 returns. You can filter the data to see the pattern of new care episodes over time across dimensions such as placement type, provider type, child age, child ethnicity, child gender, and whether the new placement followed a breakdown.</p>
+ <br>
+ <p><i>Select the period of data in the SSDA903 dataset you want to explore</i></p>
  {{ form.media }}
  <form method="POST">
  {% csrf_token %}
  {% crispy form %}
  </form>
+ <br>
  <div class="row">
  <div class="col">
  <h1>Total # of entry into care</h1>
- <p>{{ entry_into_care_count }}</p>
+ <p><h1 class="display-2">{{ entry_into_care_count }}</h1></p>
  </div>
  <div class="col">
  <h1>Total # of exiting care</h1>
- <p>{{ exiting_care_count }}</p>
+ <p><h1 class="display-2">{{ exiting_care_count }}</h1></p>
  </div>
 </div>
 <div class="alert alert-primary" role="alert">
  {{chart|safe}}
-
 </div>
+<div class="d-flex bd-highlight mb-3">
+ <div class="ms-auto p-2 bd-highlight"><a class="btn btn-primary" href="{% url 'prediction' %}">Next</a></div>
+ </div>
 {% endblock %}

dm_regional_app/views.py

@@ -80,6 +80,7 @@ def historic_data(request):
  request.POST,
  la_choices=datacontainer.unique_las,
  placement_type_choices=datacontainer.unique_placement_types,
+ age_bin_choices=datacontainer.unique_age_bins,
  )
  if form.is_valid():
  data = form.apply_filters(datacontainer.enriched_view)
@@ -97,6 +98,7 @@ def historic_data(request):
  },
  la_choices=datacontainer.unique_las,
  placement_type_choices=datacontainer.unique_placement_types,
+ age_bin_choices=datacontainer.unique_age_bins,
  )
  data = datacontainer.enriched_view
 

dm_regional_site/settings.py

@@ -42,6 +42,7 @@
  "crispy_forms",
  "crispy_bootstrap5",
  "bootstrap_datepicker_plus",
+ "django_select2",
 ]
 
 MIDDLEWARE = [

pyproject.toml

@@ -16,6 +16,7 @@ crispy-bootstrap5 = "^2024.2"
 python-decouple = "^3.8"
 faker = "^23.3.0"
 django-bootstrap-datepicker-plus = "^5.0.5"
+django-select2 = "^8.1.2"
 
 
 [tool.poetry.group.dev.dependencies]

ssda903/datacontainer.py

@@ -4,7 +4,6 @@
 from functools import cached_property
 from typing import Optional
 
-
 import numpy as np
 import pandas as pd
 
@@ -117,7 +116,7 @@ def combined_datasets(self) -> pd.DataFrame:
  merged = merged.merge(uasc[["CHILD", "DUC"]], how="left", on="CHILD")
 
  # create UASC flag if DECOM is less than DUC
- merged["UASC"] = np.where(merged["DECOM"] < merged["DUC"], 1, 0)
+ merged["UASC"] = np.where(merged["DECOM"] < merged["DUC"], True, False)
 
  return merged
 
@@ -203,6 +202,10 @@ def unique_las(self) -> pd.Series:
  def unique_placement_types(self) -> pd.Series:
  return self.enriched_view.placement_type.unique()
 
+ @cached_property
+ def unique_age_bins(self) -> pd.Series:
+ return self.enriched_view.age_bin.unique()
+
  def _add_ages(self, combined: pd.DataFrame) -> pd.DataFrame:
  """
  Calculates the age of the child at the start and end of the episode and adds them as columns