Merge pull request #274 from naxa-developers/develop

Develop

core/admin.py

@@ -1,7 +1,7 @@
 from django.contrib import admin
 from .models import Partner, Program, Sector, SubSector, MarkerCategory, MarkerValues, Province, District, GapaNapa, \
     FiveW, Indicator, IndicatorValue, TravelTime, GisLayer, Project, PartnerContact, Output, ProvinceDummy, \
-    Notification, BudgetToSecondTier, BudgetToFirstTier, Cmp, Filter, GisStyle, GisPop, NepalSummary, FeedbackForm,FAQ,TermsAndCondition
+    Notification, BudgetToSecondTier, BudgetToFirstTier, Cmp, Filter, GisStyle, GisPop, NepalSummary, FeedbackForm,FAQ,TermsAndCondition,NationalStatistic,Manual
 
 # Register your models here.
 
@@ -33,4 +33,6 @@
 admin.site.register(NepalSummary)
 admin.site.register(FeedbackForm)
 admin.site.register(FAQ)
-admin.site.register(TermsAndCondition)
+admin.site.register(TermsAndCondition)
+admin.site.register(NationalStatistic)
+admin.site.register(Manual)

core/filters.py

@@ -1,36 +1,41 @@
 from .models import FiveW
 from django.db.models import Sum
+from django.db.models import Q
 
 
-def fivew(supplier, program, component, sector, sub_sector, markers, markers_value, count):
-    name_list = ['supplier', 'program', 'component', 'sector', 'sub_sector', 'markers', 'markers_value']
-    value_list = [supplier, program, component, sector, sub_sector, markers, markers_value]
+def fivew(supplier, program, component, sector, sub_sector, markers, markers_value, count, stat):
+    name_list = ['supplier', 'program', 'component', 'sector', 'sub_sector', 'markers', 'markers_value', 'stat']
+    value_list = [supplier, program, component, sector, sub_sector, markers, markers_value, stat]
     key_list = ['supplier_id__in', 'program_id__in', 'component_id__code__in', 'program_id__sector__id__in',
                 'program_id__sub_sector__id__in',
-                'program_id__marker_category__id__in', 'program_id__marker_value__id__in']
+                'program_id__marker_category__id__in', 'program_id__marker_value__id__in', 'status__in']
     filter_dict = {}
     for index, x in enumerate(value_list):
         if x and name_list[index] not in count:
             filter_dict[key_list[index]] = x
 
-    dat_values = FiveW.objects.filter(**filter_dict).values('id', 'allocated_budget', 'province_id__code',
-                                                            'district_id__code', 'municipality_id__code',
-                                                            'component_id',
-                                                            'program_id', 'allocated_budget', 'program_id__name',
-                                                            'component_id__name', 'supplier_id__name',
-                                                            'program_id__sector__name', 'program_id__sub_sector__name',
-                                                            'program_id__marker_category__name',
-                                                            'program_id__marker_value__value').distinct()
-
-    dat_values = dat_values.exclude(
-        municipality_id__code='-1',
-        district_id__code='-1',
-        province_id__code='-1')
-    # print(dat_values.aggregate(Sum('allocated_budget')))
+    dat_values = FiveW.objects.filter(**filter_dict).values('id')
+
     return dat_values
 
 
-def fivew_province(province, supplier, program, component, sector, sub_sector, markers, markers_value, count):
+def fivew_province(province, supplier, program, component, sector, sub_sector, markers, markers_value, count, stat):
+    name_list = ['province', 'supplier', 'program', 'component', 'sector', 'sub_sector', 'markers', 'markers_value',
+                 'stat']
+    value_list = [province, supplier, program, component, sector, sub_sector, markers, markers_value, stat]
+    key_list = ['province_id__in', 'supplier_id__in', 'program_id__in', 'component_id__code__in',
+                'program_id__sector__id__in', 'program_id__sub_sector__id__in',
+                'program_id__marker_category__id__in', 'program_id__marker_value__id__in', 'status__in']
+    filter_dict = {}
+    for index, x in enumerate(value_list):
+        if x and name_list[index] not in count:
+            filter_dict[key_list[index]] = x
+
+    dat_values = FiveW.objects.filter(**filter_dict).values('id')
+    return dat_values
+
+
+def sankey(province, supplier, program, component, sector, sub_sector, markers, markers_value, count):
     name_list = ['province', 'supplier', 'program', 'component', 'sector', 'sub_sector', 'markers', 'markers_value']
     value_list = [province, supplier, program, component, sector, sub_sector, markers, markers_value]
     key_list = ['province_id__in', 'supplier_id__in', 'program_id__in', 'component_id__code__in',
@@ -41,70 +46,40 @@ def fivew_province(province, supplier, program, component, sector, sub_sector, m
         if x and name_list[index] not in count:
             filter_dict[key_list[index]] = x
 
-    dat_values = FiveW.objects.filter(**filter_dict).values('id', 'allocated_budget', 'province_id__code',
-                                                            'district_id__code', 'municipality_id__code',
-                                                            'component_id',
-                                                            'program_id', 'allocated_budget', 'program_id__name',
-                                                            'component_id__name', 'supplier_id__name',
-                                                            'program_id__sector__name', 'program_id__sub_sector__name',
-                                                            'program_id__marker_category__name',
-                                                            'program_id__marker_value__value').distinct()
-
-    dat_values = dat_values.exclude(
-        municipality_id__code='-1',
-        district_id__code='-1',
-        province_id__code='-1')
+    dat_values = FiveW.objects.filter(**filter_dict).values('id')
+
     return dat_values
 
 
-def fivew_municipality(municipality, supplier, program, component, sector, sub_sector, markers, markers_value, count):
-    name_list = ['municipality', 'supplier', 'program', 'component', 'sector', 'sub_sector', 'markers', 'markers_value']
-    value_list = [municipality, supplier, program, component, sector, sub_sector, markers, markers_value]
+def fivew_municipality(municipality, supplier, program, component, sector, sub_sector, markers, markers_value, count,
+                       stat):
+    name_list = ['municipality', 'supplier', 'program', 'component', 'sector', 'sub_sector', 'markers', 'markers_value',
+                 'stat']
+    value_list = [municipality, supplier, program, component, sector, sub_sector, markers, markers_value, stat]
     key_list = ['municipality_id__in', 'supplier_id__in', 'program_id__in', 'component_id__code__in',
                 'program_id__sector__id__in', 'program_id__sub_sector__id__in',
-                'program_id__marker_category__id__in', 'program_id__marker_value__id__in']
+                'program_id__marker_category__id__in', 'program_id__marker_value__id__in', 'status__in']
     filter_dict = {}
     for index, x in enumerate(value_list):
         if x and name_list[index] not in count:
             filter_dict[key_list[index]] = x
 
-    dat_values = FiveW.objects.filter(**filter_dict).values('id', 'allocated_budget', 'province_id__code',
-                                                            'district_id__code', 'municipality_id__code',
-                                                            'component_id',
-                                                            'program_id', 'allocated_budget', 'program_id__name',
-                                                            'component_id__name', 'supplier_id__name',
-                                                            'program_id__sector__name', 'program_id__sub_sector__name',
-                                                            'program_id__marker_category__name',
-                                                            'program_id__marker_value__value').distinct()
-    dat_values = dat_values.exclude(
-        municipality_id__code='-1',
-        district_id__code='-1',
-        province_id__code='-1')
+    dat_values = FiveW.objects.filter(**filter_dict).values('id')
+
     return dat_values
 
 
-def fivew_district(district, supplier, program, component, sector, sub_sector, markers, markers_value, count):
-    name_list = ['district', 'supplier', 'program', 'component', 'sector', 'sub_sector', 'markers', 'markers_value']
-    value_list = [district, supplier, program, component, sector, sub_sector, markers, markers_value]
+def fivew_district(district, supplier, program, component, sector, sub_sector, markers, markers_value, count, stat):
+    name_list = ['district', 'supplier', 'program', 'component', 'sector', 'sub_sector', 'markers', 'markers_value',
+                 'stat']
+    value_list = [district, supplier, program, component, sector, sub_sector, markers, markers_value, stat]
     key_list = ['district_id__in', 'supplier_id__in', 'program_id__in', 'component_id__code__in',
                 'program_id__sector__id__in', 'program_id__sub_sector__id__in',
-                'program_id__marker_category__id__in', 'program_id__marker_value__id__in']
+                'program_id__marker_category__id__in', 'program_id__marker_value__id__in', 'status__in']
     filter_dict = {}
     for index, x in enumerate(value_list):
         if x and name_list[index] not in count:
             filter_dict[key_list[index]] = x
-    print(filter_dict)
-    dat_values = FiveW.objects.filter(**filter_dict).values('id', 'allocated_budget', 'province_id__code',
-                                                            'district_id__code', 'municipality_id__code',
-                                                            'component_id',
-                                                            'program_id', 'allocated_budget', 'program_id__name',
-                                                            'component_id__name', 'supplier_id__name',
-                                                            'program_id__sector__name', 'program_id__sub_sector__name',
-                                                            'program_id__marker_category__name',
-                                                            'program_id__marker_value__value').distinct()
-    dat_values = dat_values.exclude(
-        municipality_id__code='-1',
-        district_id__code='-1',
-        province_id__code='-1'
-    )
+    dat_values = FiveW.objects.filter(**filter_dict).values('id')
+
     return dat_values

core/management/commands/new_indicator.py

@@ -4,6 +4,7 @@
 from django.core.exceptions import ObjectDoesNotExist, MultipleObjectsReturned
 from core.models import Indicator
 import math
+import json
 
 
 class Command(BaseCommand):
@@ -18,35 +19,42 @@ def handle(self, *args, **kwargs):
         # print(os.path.exists("/home/sumit/django_projects/dvs/data_csv"))
         # print(os.path.isfile(path))
         df1 = pd.read_csv(path)
-        df = df1.fillna('')
+        df2 = df1.fillna('')
+        df = df2.drop_duplicates(subset=['Indicators'])
         # print(df['Level'][0])
         # print(len(df))
         upper_range = len(df)
         correct_data = []
         for row in range(0, upper_range):
-            if df['Indicator '][row] == '':
+            if df['Indicators'][row] == '':
                 pass
             else:
                 try:
                     try:
-                        test = Indicator.objects.get(indicator=(df['Indicator '][row]).strip())
-                        test.full_title = df['Title '][row]
+                        test = Indicator.objects.get(indicator=(df['Indicators'][row]).strip())
+                        test.full_title = df['Fulltitle'][row]
                         test.abstract = df['Abstract'][row]
-                        test.category = (df['Category '][row]).strip()
-                        test.source = df['Source '][row]
-                        test.url = df['URL'][row]
+                        test.category = (df['Category'][row]).strip()
+                        test.source = df['Source'][row]
+                        test.url = df['Link'][row]
                         test.federal_level = 'all'
+                        test.unit = df['Unit'][row]
+                        test.is_dashboard = json.loads(str(df['Show on Dashboard '][row]).lower())
+                        test.is_regional_profile = json.loads(str(df['Show on Profile '][row]).lower())
                         test.save()
                         self.stdout.write('Successfully Updated' + str(test.full_title) + 'data')
                     except ObjectDoesNotExist:
                         correct_data.append(Indicator(
-                            indicator=(df['Indicator '][row]).strip(),
-                            full_title=df['Title '][row],
+                            indicator=(df['Indicators'][row]).strip(),
+                            full_title=df['Fulltitle'][row],
                             abstract=df['Abstract'][row],
-                            category=(df['Category '][row]).strip(),
-                            source=df['Source '][row],
-                            url=df['URL'][row],
-                            federal_level='all'
+                            category=(df['Category'][row]).strip(),
+                            source=df['Source'][row],
+                            url=df['Link'][row],
+                            federal_level='all',
+                            unit=df['Unit'][row],
+                            is_dashboard=json.loads(str(df['Show on Dashboard '][row]).lower()),
+                            is_regional_profile=json.loads(str(df['Show on Dashboard '][row]).lower())
                         ))
                 except Exception as e:
                     print(e)

core/management/commands/new_indicator_data.py

@@ -1,6 +1,23 @@
 from django.core.management.base import BaseCommand
 import pandas as pd
 from core.models import Indicator, IndicatorValue, GapaNapa, District
+from django.core.exceptions import ObjectDoesNotExist
+
+
+def gapanapa(code):
+    try:
+        obj = GapaNapa.objects.get(hlcit_code=str(code))
+    except ObjectDoesNotExist:
+        obj = None
+    return obj
+
+
+def valuedata(val):
+    try:
+        data = float(val)
+    except:
+        data = 0
+    return data
 
 
 class Command(BaseCommand):
@@ -12,29 +29,26 @@ def add_arguments(self, parser):
     def handle(self, *args, **kwargs):
         path = kwargs['path']
 
-        df = pd.read_csv(path)
+        df1 = pd.read_csv(path)
+        df = df1.fillna('')
         upper_range = len(df)
         print("Wait Data is being Loaded")
-        indicator_name = ((path.split('/'))[-1]).replace('.csv', '')
-
         try:
             indicator_value = [
                 IndicatorValue(
-                    indicator_id=Indicator.objects.get(indicator=indicator_name),
-                    gapanapa_id=GapaNapa.objects.get(hlcit_code=df['hlcit_id'][row]),
-                    value=float(df['value'][row]),
+                    indicator_id=Indicator.objects.get(indicator=df['Indicators'][row].strip()),
+                    gapanapa_id=gapanapa(df['Hlcit Id'][row]),
+                    national_average=float(df['National Average '][row]),
+                    province_average=float(df['Province average '][row]),
+                    district_average=float(df['District Average '][row]),
+                    value=valuedata(df['Value'][row]),
 
                 ) for row in range(0, upper_range)
             ]
             indicator_data = IndicatorValue.objects.bulk_create(indicator_value)
 
             if indicator_data:
                 self.stdout.write('Successfully loaded Indicator Value  ..')
-            # for row in range(0, upper_range):
-            #     print(df['District_ID'][row])
-            #     d = District.objects.get(code=df['District_ID'][row])
-            #     print(d.name)
-
 
         except Exception as e:
-            print(e)
+            print(e)

core/migrations/0171_nationalstatistic.py

@@ -0,0 +1,20 @@
+# Generated by Django 2.2.10 on 2021-04-19 09:00
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('core', '0170_auto_20210406_1554'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='NationalStatistic',
+            fields=[
+                ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('url', models.URLField(blank=True, null=True)),
+            ],
+        ),
+    ]

core/migrations/0172_auto_20210420_1226.py

@@ -0,0 +1,28 @@
+# Generated by Django 2.2.10 on 2021-04-20 06:41
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('core', '0171_nationalstatistic'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='indicatorvalue',
+            name='district_average',
+            field=models.FloatField(default=0),
+        ),
+        migrations.AddField(
+            model_name='indicatorvalue',
+            name='national_average',
+            field=models.FloatField(default=0),
+        ),
+        migrations.AddField(
+            model_name='indicatorvalue',
+            name='province_average',
+            field=models.FloatField(default=0),
+        ),
+    ]

core/migrations/0173_indicator_is_regional_profile.py

@@ -0,0 +1,18 @@
+# Generated by Django 2.2.10 on 2021-04-21 09:11
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('core', '0172_auto_20210420_1226'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='indicator',
+            name='is_regional_profile',
+            field=models.BooleanField(default=True),
+        ),
+    ]

core/migrations/0174_nationalstatistic_title.py

@@ -0,0 +1,18 @@
+# Generated by Django 2.2.10 on 2021-04-23 04:51
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('core', '0173_indicator_is_regional_profile'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='nationalstatistic',
+            name='title',
+            field=models.CharField(blank=True, max_length=500, null=True),
+        ),
+    ]