From 0951f6418e753585a78bcd179565a308e1fed3f3 Mon Sep 17 00:00:00 2001
From: odair mario <badwolves123@gmail.com>
Date: Thu, 14 Sep 2017 14:54:56 -0300
Subject: [PATCH] taxas sem padrao de projeto
---
script/analysis/course_analysis.py | 48 ++++++++++++++++++++++++++++++
1 file changed, 48 insertions(+)
diff --git a/script/analysis/course_analysis.py b/script/analysis/course_analysis.py
index e69de29..2c994c3 100644
--- a/script/analysis/course_analysis.py
+++ b/script/analysis/course_analysis.py
@@ -0,0 +1,48 @@
+# -*- coding: utf-8 -*-
+
+import pandas as pd
+import numpy as np
+
+def print_analise(d):
+ with pd.option_context('display.max_rows', None, 'display.max_columns', 27):
+ print(d)
+def analise(df):
+ c = df.groupby(['COD_ATIV_CURRIC']).size()
+ diciplinas = df.groupby(['COD_ATIV_CURRIC','SIGLA']).size().reset_index(name='counts')
+ i=diciplinas.groupby(['COD_ATIV_CURRIC','SIGLA']).apply(lambda x: x['counts'] / (c[x['COD_ATIV_CURRIC']].values[0])).reset_index(name='taxas')
+ print_analise(i)
+analise(df)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+#
+##f = lambda x: x / c[x]
+## p = df.groupby(['COD_ATIV_CURRIC','SIGLA']).size().apply(lambda x: (x /c['CI055'])*100)
+#k = (df.sort(['ANO','PERIODO']))
+##(p.apply(lambda x: print(p['COD_ATIV_CURRIC'])))
+#
+## # .size().reset_index(name = "count");
+## # c = p.groupby(['count','SIGLA']).size()
+## ''' percorre mais uma vez a serie para aplicar a funcao lambida, se a '''
+## c = lambda x: x+1
+## curses = df['COD_ATIV_CURRIC'].drop_duplicates()
+## 'MATR_ALUNO','
+#p
+#df = pd.read_excel("../base/historico.xls")
--
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