weak = ex2_weak.index
# excellent = exellentPractice[w]
# weak = weakPractice[w]
excellentLine = []
weakLine = []
mixedLine = []
excellentLine_not_cleaned = []
weakLine_not_cleaned = []
mixedLine_not_cleaned = []
noOfCommunities = []
upper = 0.70
lower = 0.30
for i in range(0, len(graph_all_weeks[w].graph._node) - 1):
a1 = graphLearning.identifyCommunitiesType(communityListWeeks[w][i],
excellent, weak)
excellentLine.append(len(a1.loc[a1['excellentRate'] >= upper]))
weakLine.append(len(a1.loc[a1['excellentRate'] < lower]))
mixedLine.append(
len(a1.loc[(a1['excellentRate'] < upper)
& (a1['excellentRate'] >= lower)]))
a2 = graphLearning.identifyCommunitiesType(
communityListWeeks_not_cleaned[w][i], excellent, weak)
excellentLine_not_cleaned.append(
len(a2.loc[a2['excellentRate'] >= upper]))
weakLine_not_cleaned.append(len(a2.loc[a2['excellentRate'] < lower]))
mixedLine_not_cleaned.append(
len(a2.loc[(a2['excellentRate'] < upper)
& (a2['excellentRate'] >= lower)]))
weak = ex2_weak.index
# excellent = exellentPractice[w]
# weak = weakPractice[w]
excellentLine = []
weakLine = []
mixedLine = []
excellentLine_not_cleaned = []
weakLine_not_cleaned = []
mixedLine_not_cleaned = []
noOfCommunities = []
upper = 0.70
lower = 0.30
for i in range(0,len(graph_all_weeks[w].graph._node)-1):
a1 = graphLearning.identifyCommunitiesType(communityListWeeks[w][i], excellent, weak)
excellentLine.append(len(a1.loc[a1['excellentRate'] >= upper]))
weakLine.append(len(a1.loc[a1['excellentRate'] < lower]))
mixedLine.append(len(a1.loc[(a1['excellentRate'] <upper) & (a1['excellentRate'] >= lower)]))
a2 = graphLearning.identifyCommunitiesType(communityListWeeks_not_cleaned[w][i], excellent, weak)
excellentLine_not_cleaned.append(len(a2.loc[a2['excellentRate'] >= upper]))
weakLine_not_cleaned.append(len(a2.loc[a2['excellentRate'] < lower]))
mixedLine_not_cleaned.append(len(a2.loc[(a2['excellentRate'] < upper) & (a2['excellentRate'] >= lower)]))
noOfCommunities.append(i+2)
ax = fig.add_subplot(3,4,w+1)
graph.append(ax)
graph[countGraph].set_xlabel('Number of communities', fontsize = 15)
graph[countGraph].set_ylabel('Number of the communities in each group', fontsize = 15)