import glob, os
import xlrd
import networkx as nx
import pandas as pd
import numpy as np
from my_network import remove_edges, read_edgelist, weight, all_graph_info, bipartite_graph, stock_network, graph_structure_info
from my_plots import density, hist_plt, hist_log_bin
import matplotlib.pyplot as plt
from my_dataframes import drop_duplicate, drop_emptycell, stock_status, summary
import seaborn as sns
os.chdir('E:/financial_network/data/threshold/transformed')
df1 = pd.read_excel('2015-1_transformed.xlsx', 'Sheet1')
df1 = pd.DataFrame(df1)
df1 = drop_duplicate(df1)
df1 = drop_emptycell(df1)
os.chdir('E:/financial_network/data/threshold/stock_alpha/0.95_2015-1')
df = pd.read_excel('node_degree_weight-back_up.xlsx', 'Sheet1')
df = pd.DataFrame(df)
q1 = 451 #30%
q2 = 946 #60%
q3 = 1490 #90%
k0 = df[df.out_degree == 0]['nodes']
k1 = df[df.out_degree <= q1]
k1 = k1[k1.out_degree > 0]['nodes']
k2 = df[df.out_degree <= q2]
k2 = k2[k2.out_degree > q1]['nodes']
k3 = df[df.out_degree <= q3]
k3 = k3[k3.out_degree > q2]['nodes']
def zhexian(x, filename):
plt.figure()
x.plot()
plt.title(filename)
plt.savefig(filename + ".png")
plt.clf()
os.chdir('/Users/shine/work_hard/financial_network/data/threshold/stock_alpha')
V = nx.read_graphml('2015-1_95.graphml')
#t_list = ['601318.SH', '601166.SH', '600036.SH', '600016.SH', '600030.SH','600000.SH','300059.SZ','002183.SZ','000002.SZ']
t_list = ['000732.SZ']
decline = pd.read_excel('6.12-7.8_decline-manual.xlsx', sheet_name='Sheet1')
decline = pd.DataFrame(decline)
decline = drop_emptycell(decline)
decline = drop_duplicate(decline)
for i in t_list:
decline1 = decline[decline.source == i]
if len(decline1) != 0: #判断一下是否为空
#print decline1
x = decline1.iloc[:, 1:18].transpose()
node = decline1.iloc[0, 0]
#zhexian(x, node+'_decline')
lower = []
os.chdir('/Users/shine/work_hard/financial_network/data/status_wind_612_710')
FileList = glob.glob('*.xlsx') #for workingfile in filelist
print FileList
print "FileList length is", len(FileList) #共20个文件