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#!/usr/bin/python3
#-*-coding:utf-8-*-
# 绘制成绩与各用户行为数据之间的散点图
# 表格中数据的位置：0-成绩；1-观看视频次数；2-单元测验次数；3-文档；４-随堂测验
import matplotlib.pyplot as plt
import numpy as np
import xlrd
import xlwt
from xlrd import open_workbook
import random
plt.rcParams['font.sans-serif']=['SimHei'] # 显示中文不乱码
plt.rcParams['axes.unicode_minus'] = False # 显示负数不乱码
file = '/home/hadoop/桌面/py/res/mooc后台数据/个人行为信息.xlsx'
save_file = '/home/hadoop/桌面/py/res/mooc后台数据/个人行为信息02.xlsx'
## 读取表数据
def read_data(filename,sheet):
wb = open_workbook(filename)
s = wb.sheet_by_index(sheet)
data = [[]for i in range(s.ncols)]
for r in range(s.nrows):
# s.row_values(0)[0] 均为 float数据类型
if r == 0:
continue
for c in range(s.ncols):
data[c].append(s.row_values(r)[c])
return data
## 绘制散点图
def plot_scatter(x_data,y_data):
_,ax = plt.subplots()
ax.plot(x_data,y_data,'ro',label='观看视频次数')
# ax.plot(data[2],data[0],'bo',label='单元测试次数')
# ax.plot(data[3],data[0],'go',label='文档')
# ax.plot(data[])
ax.set_xlabel(u'观看视频次数')
ax.set_ylabel(u'成绩')
ax.set_title(u'成绩与观看视频次数的分布')
plt.show()
## 对数据进行shuffle操作
## data 数组
## ratio 分段数
def shuffle_data(data,ratio):
temp = [[] for i in range(ratio)]
qu = int(len(data) / ratio)
for i in range(ratio):
if i == ratio -1 :
temp[i] = data[i*qu:]
random.shuffle(temp[i])
break
temp[i] = data[i*qu : (i+1)*qu]
random.shuffle(temp[i])
r = []
for i in range(ratio):
r += temp[i]
return r
## 写入表格数据
## data 要写入的表格数据
## name 表的名称
def write_xls(workbook,data,name):
worksheet = workbook.add_sheet(name)
for c in range(len(data)):
for r in range(len(data[c])):
#print('the data is: ',data[c][r])
worksheet.write(r,c,data[c][r])
workbook = xlwt.Workbook(encoding = 'utf-8')
s2017 = read_data(file,0)
ns2017 = [[] for i in range(5)]
ns2017[0] = s2017[0]
s_data = shuffle_data(s2017[1],5)
ns2017[1] = s_data
s_data = shuffle_data(s2017[2],2)
ns2017[2] = s_data
s_data = shuffle_data(s2017[3],5)
ns2017[3] = s_data
s_data = shuffle_data(s2017[4],2)
ns2017[4] = s_data
write_xls(workbook,ns2017,u'2017年春季')
f2017 = read_data(file,1)
nf2017 = [[] for i in range(5)]
nf2017[0] = f2017[0]
s_data = shuffle_data(f2017[1],5)
nf2017[1] = s_data
s_data = shuffle_data(f2017[2],2)
nf2017[2] = s_data
s_data = shuffle_data(f2017[3],5)
nf2017[3] = s_data
s_data = shuffle_data(f2017[4],2)
nf2017[4] = s_data
write_xls(workbook,nf2017,u'2017年秋季')
s2018 = read_data(file,2)
ns2018 = [[] for i in range(5)]
ns2018[0] = s2018[0]
s_data = shuffle_data(s2018[1],5)
ns2018[1] = s_data
s_data = shuffle_data(s2018[2],2)
ns2018[2] = s_data
s_data = shuffle_data(s2018[3],5)
ns2018[3] = s_data
s_data = shuffle_data(s2018[4],2)
ns2018[4] = s_data
write_xls(workbook,ns2018,u'2018年春季')
f2018 = read_data(file,3)
nf2018 = [[] for i in range(5)]
nf2018[0] = f2018[0]
s_data = shuffle_data(f2018[1],5)
nf2018[1] = s_data
s_data = shuffle_data(f2018[2],2)
nf2018[2] = s_data
s_data = shuffle_data(f2018[3],5)
nf2018[3] = s_data
s_data = shuffle_data(f2018[4],2)
nf2018[4] = s_data
write_xls(workbook,nf2018,u'2018年秋季')
# plot_scatter(s_data,s2017[0])
# f2017 = read_data(file,1)
# s2018 = read_data(file,2)
# f2018 = read_data(file,3)
# plot_scatter(ns2017[2],ns2017[0])
workbook.save(save_file)