fix merge conflicts

script/analysis/student_analysis.py

-import re
 import pandas as pd
-import numpy as np
 from utils.situations import *
 
-def average_ira(df):
-    print(df)
-    new_df = df.dropna(subset=['MEDIA_FINAL'])
-    new_df = new_df[new_df['MEDIA_FINAL'] <= 100]
-    if not new_df.empty:
-        grade = np.sum(new_df['MEDIA_FINAL']*new_df['CH_TOTAL'])
-        total_ch = np.sum(new_df['CH_TOTAL']) * 100
+def average_ira(d):
+    temp = d.dropna(subset=['MEDIA_FINAL'])
+    temp = temp[temp['MEDIA_FINAL'] <= 100]
+    if not temp.empty:
+        #print(temp[['MEDIA_FINAL', 'CH_TOTAL']])
+        aux = np.sum(temp['MEDIA_FINAL']*temp['CH_TOTAL'])
+        ch_total = np.sum(temp['CH_TOTAL']) * 100
+        print(aux/ch_total)
 
-    return grade/total_ch
-
-def pass_rate(dt):
-    new_dt = dt[dt['SITUACAO'].isin(Situation.SITATUION_PASS)]
-    
+def aluno_turmas(df):
+	students = {}
+	df = df.dropna(subset=['MEDIA_FINAL'])
+	total_students = len(df["MATR_ALUNO"])
+	for i in range(total_students):
+		matr = (df["MATR_ALUNO"][i])
+		if(not (matr in students)):
+			students[matr] = []
+		
+		for s in Situation.SITUATIONS:
+			if(s[0] == df["SITUACAO"][i]):
+				situacao = s[1]
+				break
+		ano = (df["ANO"][i])
+		codigo = (df["COD_ATIV_CURRIC"][i])
+		nome = (df["NOME_ATIV_CURRIC"][i])
+		nota = (df["MEDIA_FINAL"][i])
+		semestre = (df["PERIODO"][i])
+		
+		students[matr].append({
+			"ano": ano,
+			"codigo": codigo,
+			"nome": nome,
+			"nota": nota,
+			"semestre": semestre,
+			"situacao": situacao
+		})
+	print(students)
+	#~ lines = (df[["MATR_ALUNO","ANO","COD_ATIV_CURRIC","NOME_ATIV_CURRIC","MEDIA_FINAL","PERIODO","SITUACAO"]])
+	#~ for st in (df.groupby("MATR_ALUNO")):
+		#~ print(st[1]["MATR_ALUNO"])
+		#~ print(st[1]["ANO"])
+		#~ print(st[1]["COD_ATIV_CURRIC"])
+		#~ print(st[1]["NOME_ATIV_CURRIC"])
+		#~ print(st[1]["MEDIA_FINAL"])
+		#~ print(st[1]["PERIODO"])
+		#~ print(st[1]["SITUACAO"])
+		#~ print("")
+	#~ total_student = df['MATR_ALUNO'].drop_duplicates()
+	#~ for st in total_student:
+		#~ students[st] = []
+		#~ hist = df[df["MATR_ALUNO"]==st]
+		#~ for matr in hist:
+			#~ print(hist["ANO"])
+			#~ print(hist[matr]["COD_ATIV_CURRIC"])
+			#~ print(hist[matr]["NOME_ATIV_CURRIC"])
+			#~ print(hist[matr]["MEDIA_FINAL"])
+			#~ print(hist[matr]["PERIODO"])
+			#~ print(hist[matr]["SITUACAO"])
+			#~ print(hist[matr])
+			#~ print("")

script/base/dataframe_base.py

@@ -32,9 +32,9 @@ def load_dataframes(cwd='.'):
     dataframe = fix_dataframes(dataframes)
 
     dh = DataframeHolder(dataframe)
-
-
-    return dh
+    #~ dh.students.aggregate(teste)
+#    print(dh.students['MEDIA_FINAL'].aggregate(teste))
+    return dataframe
 
 
 def read_excel(path, planilha='Planilha1'):
@@ -96,4 +96,11 @@ def fix_admission(df):
 
 def fix_evasion(df):
     for evasion in EvasionForm.EVASION_FORM:
-        df.loc[df.FORMA_EVASAO.str.contains(evasion[1]).fillna(False), 'FORMA_EVASAO'] = evasion[0]
+        #~ 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):
+                    #~ print(x)
+    #~ print(df.FORMA_EVASAO.str.contains(evasion[1]).fillna(5))
+    #~ print(df[['MATR_ALUNO','FORMA_EVASAO']])

script/build_cache.py

@@ -6,8 +6,9 @@ import math
 from datetime import timedelta
 from pathlib import Path
 from utils.utils import build_path
-import analysis.degree_analysis as de_an
-import analysis.student_analysis as st_an
+from analysis.degree_analysis import *
+from analysis.student_analysis import *
+
 try:
     to_unicode = unicode
 except NameError:
@@ -23,7 +24,7 @@ def build_cache(dataframe):
 
     generate_student_data(path, dataframe)
 #    generate_degree_data(path, dataframe)
-#    generate_student_data(path)
+    generate_student_data(path,dataframe)
 #    generate_student_list(path)
 #    generate_admission_data(path)
 #    generate_admission_list(path)
@@ -36,19 +37,8 @@ def generate_degree_data(path, dataframe):
     de_an.general_ira(dataframe)
     pass
 
-
-def teste(d):
-    temp = d.dropna(subset=['MEDIA_FINAL'])
-    temp = temp[temp['MEDIA_FINAL'] <= 100]
-    if not temp.empty:
-        #print(temp[['MEDIA_FINAL', 'CH_TOTAL']])
-        aux = np.sum(temp['MEDIA_FINAL']*temp['CH_TOTAL'])
-        ch_total = np.sum(temp['CH_TOTAL']) * 100
-        print(aux/ch_total)
-
-def generate_student_data(path, dataframe):
-#    student_df = dataframe.groupby('MATR_ALUNO')
-    dataframe.students.aggregate(teste)
+def generate_student_data(path,dataframe):
+    aluno_turmas(dataframe)
     pass
 
 def generate_student_list(path):