Merge branch 'degree' into students

.gitignore

@@ -17,3 +17,4 @@ src/cache
 .idea
 **/__pycache__
 
+*.ipynb

script/analysis/degree_analysis.py

@@ -34,3 +34,32 @@ def general_ira(df):
     fixed = df[df.SITUACAO.isin(Situation.SITUATION_AFFECT_IRA)]
     fixed = fixed[fixed.MEDIA_FINAL <= 100]
     return (fixed.MEDIA_FINAL.mean(), fixed.MEDIA_FINAL.std())
+
+def total_evasion_rate(df):
+    students = df['MATR_ALUNO'].drop_duplicates()
+    total_student = students.shape[0]
+    total_evasion = students.loc[(df.FORMA_EVASAO != EvasionForm.EF_ATIVO) & (df.FORMA_EVASAO != EvasionForm.EF_FORMATURA) & (df.FORMA_EVASAO != EvasionForm.EF_REINTEGRACAO)].shape[0]
+
+    return total_evasion / total_student
+
+def average_graduation_time(df):
+    graduates = df.loc[(df.FORMA_EVASAO == EvasionForm.EF_FORMATURA)]
+    total_graduate = graduates.shape[0]
+    average_time = 0
+    year_end = int(df['ANO'].max())
+    semester_end = graduates['PERIODO'].max()
+    for index, row in graduates.iterrows():
+        if pd.notnull(row['ANO_EVASAO']):
+            year_end = int(row['ANO_EVASAO'])
+            try: 
+                semester_end = int(row['SEMESTRE_EVASAO'])
+            except ValueError:
+                semester_end = graduates['PERIODO'].max()
+        year = int(row['ANO_INGRESSO'])
+        semester = int(row['SEMESTRE_INGRESSO'])
+        difference = 2 * (year_end - year) + (semester_end - semester) + 1
+        average_time += difference
+    average_time /= total_graduate
+    average_time /= 2
+
+    return average_time
\ No newline at end of file

script/base/dataframe_base.py

@@ -30,6 +30,7 @@ def load_dataframes(cwd='.'):
                 dataframes.append(dh)
 
     dataframe = fix_dataframes(dataframes)
+
     dh = DataframeHolder(dataframe)
     #~ dh.students.aggregate(teste)
 #    print(dh.students['MEDIA_FINAL'].aggregate(teste))
@@ -94,9 +95,12 @@ def fix_admission(df):
 
 
 def fix_evasion(df):
+    evasionForms = [x[1] for x in EvasionForm.EVASION_FORM]
+    df.loc[~df.FORMA_EVASAO.isin(evasionForms), 'FORMA_EVASAO'] = 100
     for evasion in EvasionForm.EVASION_FORM:
         #~ df.loc[df.FORMA_EVASAO.str.contains(evasion[1]).fillna(1.0), 'FORMA_EVASAO'] = evasion[0]
         df.loc[df.FORMA_EVASAO == evasion[1], 'FORMA_EVASAO'] = evasion[0]
+
         #~ if(evasion[0] == 100):
             #~ for x in df.FORMA_EVASAO.str.contains(evasion[1]).fillna(False):
                 #~ if(x != 0.0):

script/build_cache.py

@@ -22,7 +22,8 @@ def build_cache(dataframe):
     path += "/curso"
     build_path(path)
 
-#    generate_degree_data(path, dataframe)
+    generate_student_data(path, dataframe)
+    generate_degree_data(path, dataframe)
     generate_student_data(path,dataframe)
 #    generate_student_list(path)
 #    generate_admission_data(path)
@@ -34,6 +35,8 @@ def generate_degree_data(path, dataframe):
     average_graduation(dataframe)
     general_failure(dataframe)
     general_ira(dataframe)
+    total_evasion_rate(dataframe)
+    average_graduation_time(dataframe)
     pass
 
 def generate_student_data(path,dataframe):

script/main.py

@@ -3,13 +3,13 @@ import time
 from base.dataframe_base import load_dataframes
 from build_cache import build_cache
 from datetime import timedelta
+from analysis.degree_analysis import *
 
 def main():
     start_time = time.clock()
     start_time_exec = time.time()
 
     dataframe = load_dataframes(os.getcwd() + '/' + 'base')
-
     build_cache(dataframe)
 
     cpu_time = timedelta(seconds=round(time.clock() - start_time))