You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
91 lines
4.0 KiB
91 lines
4.0 KiB
5 years ago
|
import pandas as pd
|
||
|
|
import pyecharts.options as opts
|
||
|
|
from pyecharts.charts import Pie
|
||
|
|
import re
|
||
|
|
|
||
|
|
|
||
|
|
with open('data/房源信息.txt','rb') as file:
|
||
|
|
house_list = []
|
||
|
|
while True:
|
||
|
|
line = file.readline()
|
||
|
|
if not line:
|
||
|
|
break
|
||
|
|
line = eval(line.decode('utf-8'))
|
||
|
|
line['面积'] = int(re.findall('\d+',line['面积'])[0])
|
||
|
|
line['价格'] = int(re.findall('\d+',line['价格'])[0])
|
||
|
|
house_list.append(line)
|
||
|
|
house_list_DF = pd.DataFrame(house_list)
|
||
|
|
xingzhengqu = [item for item in set(house_list_DF.get(key='行政区')) if item]
|
||
|
|
|
||
|
|
# 租房面积统计
|
||
|
|
bins = [-1,30,60,90,120,200,300,400,10000]
|
||
|
|
attr = ['0-30平方米','30-60平方米','60-90平方米','90-120平方米','120-200平方米','200-300平方米','300-400平方米','400+平方米']
|
||
|
|
tmpDF = house_list_DF.groupby(pd.cut(house_list_DF['面积'],bins = bins,labels=attr)).size().reset_index(name = 'count')
|
||
|
|
value = list(map(int,tmpDF['count'].values))
|
||
|
|
pie = Pie(init_opts=opts.InitOpts(width='800px',height='800px'))
|
||
|
|
pie.add('',zip(attr,value)).set_global_opts(title_opts=opts.TitleOpts(title='租房面积统计'))
|
||
|
|
pie.render('images/house/广州租房面积统计.html')
|
||
|
|
|
||
|
|
# 求每个区的每平方米的租房单价
|
||
|
|
from pyecharts.charts import TreeMap
|
||
|
|
def getAvgPrice(xingzhengqu):
|
||
|
|
totalPrice = 0
|
||
|
|
totalArea = 0
|
||
|
|
for item in house_list:
|
||
|
|
if item['行政区'] == xingzhengqu:
|
||
|
|
totalArea = totalArea + item['面积']
|
||
|
|
totalPrice = totalPrice + item['价格']
|
||
|
|
return totalPrice / totalArea if totalArea >0 else 1
|
||
|
|
# 获取每个区 单月每平方米的价格
|
||
|
|
def getTotalAvgPrice():
|
||
|
|
totalAvgPriceList = []
|
||
|
|
totalAvgPriceDirList = []
|
||
|
|
for index, item in enumerate(xingzhengqu):
|
||
|
|
avg_price = getAvgPrice(item)
|
||
|
|
totalAvgPriceList.append(round(avg_price,3))
|
||
|
|
totalAvgPriceDirList.append({'value':round(avg_price,3),'name':item + " ￥" + str(round(avg_price,3))})
|
||
|
|
return totalAvgPriceDirList
|
||
|
|
# 获取每月每平方米的价格
|
||
|
|
data = getTotalAvgPrice()
|
||
|
|
treemap = TreeMap(init_opts=opts.InitOpts(width='900px',height='800px'))
|
||
|
|
treemap.add('广州各区房租单价:平方米/月',data,label_opts=opts.LabelOpts(is_show=True, position='inside',font_size=13))
|
||
|
|
treemap.render('images/house/广州各区房租单价.html')
|
||
|
|
|
||
|
|
# 获取每个区 单日每平方米的价格
|
||
|
|
from pyecharts.charts import Bar
|
||
|
|
totalAvgPriceList = []
|
||
|
|
for index,item in enumerate(xingzhengqu):
|
||
|
|
avg_price = getAvgPrice(item)
|
||
|
|
totalAvgPriceList.append(round(avg_price/30,3))
|
||
|
|
attr, value = (xingzhengqu,totalAvgPriceList)
|
||
|
|
bar = Bar(init_opts=opts.InitOpts(width='900px',height='800px'))
|
||
|
|
bar.add_xaxis(attr)
|
||
|
|
bar.add_yaxis("广州",value)
|
||
|
|
bar.set_global_opts(title_opts=opts.TitleOpts(title='广州各区房租单价:平方米/日'))
|
||
|
|
bar.render('images/house/广州每日每平方米的价格.html')
|
||
|
|
|
||
|
|
# 获取户型数据
|
||
|
|
from pyecharts.charts import WordCloud
|
||
|
|
def getRooms():
|
||
|
|
results = house_list_DF.groupby('房间').size().reset_index(name='count')
|
||
|
|
room_list = list(results.房间.values)
|
||
|
|
weight_list = list(map(int,results['count'].values))
|
||
|
|
return (room_list, weight_list)
|
||
|
|
attr, value = getRooms()
|
||
|
|
wordcloud = WordCloud(init_opts=opts.InitOpts(width='900px',height='400px'))
|
||
|
|
wordcloud.add('',zip(attr,value),word_size_range=[2,100])
|
||
|
|
wordcloud.render('images/house/广州户型数据.html')
|
||
|
|
|
||
|
|
# 获取各个区的房源比重
|
||
|
|
from pyecharts.charts import Pie
|
||
|
|
def getAreaWeight():
|
||
|
|
result = house_list_DF.groupby('行政区').size().reset_index(name='count')
|
||
|
|
areaName = list(result.行政区.values)
|
||
|
|
areaWeight = list(map(int,result['count'].values))
|
||
|
|
areaName_tmp = []
|
||
|
|
for index,item in enumerate(areaName):
|
||
|
|
areaName_tmp.append(item + str(round(areaWeight[index]/sum(areaWeight)*100,2))+'%')
|
||
|
|
return zip(areaName_tmp,areaWeight)
|
||
|
|
pie = Pie(init_opts=opts.InitOpts(width='600px',height='400px'))
|
||
|
|
pie.add('',getAreaWeight()).set_global_opts(title_opts=opts.TitleOpts(title='广州房源分布'))
|
||
|
|
pie.render('images/house/广州房源分布.html')
|