Jan Mühlnikel commited on
Commit
e3302f1
1 Parent(s): 55a6bd8

added country and orga filter

Browse files
__pycache__/similarity_page.cpython-310.pyc CHANGED
Binary files a/__pycache__/similarity_page.cpython-310.pyc and b/__pycache__/similarity_page.cpython-310.pyc differ
 
functions/__pycache__/filter_projects.cpython-310.pyc CHANGED
Binary files a/functions/__pycache__/filter_projects.cpython-310.pyc and b/functions/__pycache__/filter_projects.cpython-310.pyc differ
 
functions/filter_projects.py CHANGED
@@ -4,8 +4,11 @@ def contains_code(crs_codes, code_list):
4
  codes = str(crs_codes).split(';')
5
  return any(code in code_list for code in codes)
6
 
7
- def filter_projects(df, crs3_list, crs5_list, sdg_str):
 
8
  if crs3_list != [] or crs5_list != [] or sdg_str != "":
 
 
9
  if crs3_list and not crs5_list:
10
  df = df[df['crs_3_code'].apply(lambda x: contains_code(x, crs3_list))]
11
  elif crs3_list and crs5_list:
@@ -13,9 +16,24 @@ def filter_projects(df, crs3_list, crs5_list, sdg_str):
13
  elif not crs3_list and crs5_list:
14
  df = df[df['crs_5_code'].apply(lambda x: contains_code(x, crs5_list))]
15
 
 
16
  if sdg_str != "":
17
  df = df[df["sgd_pred_code"] == int(sdg_str)]
18
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
19
  return df
20
 
21
 
 
4
  codes = str(crs_codes).split(';')
5
  return any(code in code_list for code in codes)
6
 
7
+ def filter_projects(df, crs3_list, crs5_list, sdg_str, country_code_list, orga_code_list):
8
+ # Check if filters where not all should be selected are empty
9
  if crs3_list != [] or crs5_list != [] or sdg_str != "":
10
+
11
+ # FILTER CRS
12
  if crs3_list and not crs5_list:
13
  df = df[df['crs_3_code'].apply(lambda x: contains_code(x, crs3_list))]
14
  elif crs3_list and crs5_list:
 
16
  elif not crs3_list and crs5_list:
17
  df = df[df['crs_5_code'].apply(lambda x: contains_code(x, crs5_list))]
18
 
19
+ # FILTER SDG
20
  if sdg_str != "":
21
  df = df[df["sgd_pred_code"] == int(sdg_str)]
22
 
23
+ # FILTER COUNTRY
24
+ if country_code_list != []:
25
+ country_filtered_df = pd.DataFrame()
26
+ for c in country_code_list:
27
+ c_df = df[df["country"].str.contains(c, na=False)]
28
+ country_filtered_df = pd.concat([country_filtered_df, c_df], ignore_index=True)
29
+
30
+ df = country_filtered_df
31
+
32
+ # FILTER ORGANIZATION
33
+ if orga_code_list != []:
34
+ df = df[df['orga_abbreviation'].isin(orga_code_list)]
35
+
36
+
37
  return df
38
 
39
 
modules/filter_modules.py DELETED
@@ -1,21 +0,0 @@
1
- import pandas as pd
2
- import streamlit as st
3
-
4
- def country_option(special_cases, country_names):
5
- country_option = st.multiselect(
6
- 'Country / Countries',
7
- special_cases + country_names,
8
- placeholder="Select"
9
- )
10
-
11
- return country_option
12
-
13
- def orga_option(special_cases, orga_names):
14
- orga_list = special_cases + [f"{v[0]} ({k})" for k, v in orga_names.items()]
15
- orga_option = st.multiselect(
16
- 'Development Bank / Organization',
17
- orga_list,
18
- placeholder="Select"
19
- )
20
-
21
- return orga_option
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
similarity_page.py CHANGED
@@ -79,6 +79,18 @@ def getSDG():
79
 
80
  return SDG_NAMES
81
 
 
 
 
 
 
 
 
 
 
 
 
 
82
  # Load Sentence Transformer Model
83
  @st.cache_resource
84
  def load_model():
@@ -110,6 +122,8 @@ CRS3_MERGED = getCRS3()
110
  CRS5_MERGED = getCRS5()
111
  SDG_NAMES = getSDG()
112
 
 
 
113
  model = load_model()
114
  sentences, embeddings, faiss_index = load_embeddings_and_index()
115
 
@@ -153,7 +167,25 @@ def show_page():
153
 
154
 
155
  with col2:
156
- st.write("x")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
157
 
158
 
159
  # CRS CODE LIST
@@ -166,8 +198,14 @@ def show_page():
166
  else:
167
  sdg_str = ""
168
 
 
 
 
 
 
 
169
  # FILTER DF WITH SELECTED FILTER OPTIONS
170
- filtered_df = filter_projects(projects_df, crs3_list, crs5_list, sdg_str)
171
 
172
  # FIND MATCHES
173
  p1_df, p2_df = calc_matches(filtered_df, projects_df, sim_matrix)
 
79
 
80
  return SDG_NAMES
81
 
82
+ # Load Country Data
83
+ @st.cache_data
84
+ def getCountry():
85
+ # Read in countries from codelist
86
+ country_df = pd.read_csv('src/codelists/country_codes_ISO3166-1alpha-2.csv')
87
+ COUNTRY_CODES = country_df['Alpha-2 code'].tolist()
88
+ COUNTRY_NAMES = country_df['Country'].tolist()
89
+
90
+ COUNTRY_OPTION_LIST = [f"{COUNTRY_NAMES[i]} ({COUNTRY_CODES[i][-3:-1].upper()})"for i in range(len(COUNTRY_NAMES))]
91
+
92
+ return COUNTRY_OPTION_LIST
93
+
94
  # Load Sentence Transformer Model
95
  @st.cache_resource
96
  def load_model():
 
122
  CRS5_MERGED = getCRS5()
123
  SDG_NAMES = getSDG()
124
 
125
+ COUNTRY_OPTION_LIST = getCountry()
126
+
127
  model = load_model()
128
  sentences, embeddings, faiss_index = load_embeddings_and_index()
129
 
 
167
 
168
 
169
  with col2:
170
+ # COUNTRY SELECTION
171
+
172
+
173
+ country_option = st.multiselect(
174
+ 'Country / Countries',
175
+ COUNTRY_OPTION_LIST,
176
+ placeholder="Select"
177
+ )
178
+
179
+ # ORGA SELECTION
180
+ orga_abbreviation = projects_df["orga_abbreviation"].unique()
181
+ orga_full_names = projects_df["orga_full_name"].unique()
182
+ orga_list = [f"{orga_full_names[i]} ({orga_abbreviation[i].upper()})"for i in range(len(orga_abbreviation))]
183
+
184
+ orga_option = st.multiselect(
185
+ 'Development Bank / Organization',
186
+ orga_list,
187
+ placeholder="Select"
188
+ )
189
 
190
 
191
  # CRS CODE LIST
 
198
  else:
199
  sdg_str = ""
200
 
201
+ # COUNTRY CODES LIST
202
+ country_code_list = [option[-3:-1] for option in country_option]
203
+
204
+ # ORGANIZATION CODES LIST
205
+ orga_code_list = [option.split("(")[1][:-1].lower() for option in orga_option]
206
+
207
  # FILTER DF WITH SELECTED FILTER OPTIONS
208
+ filtered_df = filter_projects(projects_df, crs3_list, crs5_list, sdg_str, country_code_list, orga_code_list)
209
 
210
  # FIND MATCHES
211
  p1_df, p2_df = calc_matches(filtered_df, projects_df, sim_matrix)