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all_map.py
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import re
from django.db.models.functions import Cast, Replace
from django.forms import FloatField
from django.utils import timezone
from pyecharts.charts import Pie, Line, WordCloud, Map
from pyecharts import options as opts
from pyecharts.globals import ThemeType, SymbolType
from mainapp import models
from django_pandas.io import read_frame
import jieba
from warehouse.models import Scenery, Evaluate, SpiderLog
from pyecharts import options as opts
from pyecharts.charts import Map
class AllMap():
"""
1: 长沙景点分布地图
2: 景点评分数据表格
3: 景点浏览人数数据表格
4: 人数百分比饼图
5: 词云
6: 浏览时间折线图
7: 景点数量折线图
8: 评分折线图
"""
def __init__(self):
qs = Scenery.objects.all()
self.df = read_frame(qs=qs)
# 更新时间
self.spider_time = timezone.localtime(SpiderLog.objects.last().spider_time).strftime('%Y-%m-%d %H:%M:%S')
# p1 p6
qs = Scenery.objects.filter(city__isnull=False)
df_p1 = read_frame(qs)
df_p1["county"] = df_p1["city"].map(lambda x: self.get_county(x))
self.map_data = df_p1.groupby("county").count()["scenery_name"]
self.map_data = self.map_data.sort_values()
# p4
qs = Scenery.objects.exclude(people_percent="0%").all()
self.df_p4 = read_frame(qs=qs)
self.df_p4["people_percent"] = self.df_p4["people_percent"].str.replace("%", "").astype(int)
# p2
self.scenery_obj = Scenery.objects.filter(score__isnull=False).exclude(score=0).all().order_by("-score")
def get_county(self, full_county_name):
county_list = ['芙蓉区', '天心区', '岳麓区', '望城区', '雨花区', '开福区', '宁乡市', '浏阳市', '长沙县', '宁乡县']
for i in county_list:
if i in full_county_name:
return i
def get_p1(self, h, w, is_show=False):
"""长沙景点分布地图"""
max_ = int(self.map_data.values.max())
map = (
Map(init_opts=opts.InitOpts(height=h, width=w))
.add("商家数量", [[i[0], int(i[1])] for i in zip(self.map_data.index, self.map_data.values)], maptype='长沙', is_roam=False,
label_opts=opts.LabelOpts(color="#FFF", is_show=True), is_map_symbol_show=False)
.set_global_opts(
title_opts=opts.TitleOpts(is_show=False, title="title"),
legend_opts=opts.LegendOpts(is_show=is_show, textstyle_opts=opts.TextStyleOpts(color="#fff")), # 去掉图例
visualmap_opts=opts.VisualMapOpts(max_=max_, textstyle_opts=opts.TextStyleOpts(color="#fff"))
)
.render_embed()
)
return map
def get_p2(self):
"""景点评分数据表格"""
return self.scenery_obj
def get_p3(self):
"""景点浏览人数数据表格"""
return self.df_p4.sort_values('people_percent', ascending=False).to_dict("records")
def get_p4(self, h, w, is_show=False):
"""景点人数分布"""
sum = self.df_p4["people_percent"].sum()
self.df_p4["percent_p4"] = self.df_p4["people_percent"].map(lambda x: round(float(x)/sum*100, 2))
# 货物重量比
c = (
Pie(init_opts=opts.InitOpts(height=h, width=w))
.add("", self.df_p4[["scenery_name", "percent_p4"]].values,
label_opts=opts.LabelOpts(color="#fff", is_show=False))
.set_global_opts(
legend_opts=opts.LegendOpts(is_show=is_show, textstyle_opts=opts.TextStyleOpts(color="#FFF")))
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}%", color="#FFF"))
.render_embed()
)
return c
def get_p5(self, h, w, is_show=False):
"""词云"""
import time
# start = time.time()
words = []
evaluates = Evaluate.objects.all()[:100]
for evaluate in evaluates:
txt = evaluate.content
pattern = re.compile(r"\d+")
filtered_text = re.sub(pattern, "", txt)
words += jieba.lcut(str(filtered_text))
counts = {} # 创建一个空字典
stopwords = ('0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '的', '是', '在', '等')
for word in words:
if word not in stopwords:
if len(word) <= 1:
continue
counts[word] = counts.get(word, 0) + 1
excludes = ['...']
for word in excludes:
del counts[word]
items = list(counts.items()) # 将无序的字典类型转换为可排序的列表类型
items.sort(key=lambda x: x[1], reverse=True)
# items = items[:number]
# 设置词云图
wordcloud = (
WordCloud(init_opts=opts.InitOpts(height=h, width=w))
.add(series_name="出现数量", data_pair=items, word_size_range=[20, 100], shape=SymbolType.DIAMOND)
.set_global_opts(
title_opts=opts.TitleOpts(title="评论词云", title_textstyle_opts=opts.TextStyleOpts(font_size=23), is_show=False),
legend_opts=opts.LegendOpts(is_show=False, textstyle_opts=opts.TextStyleOpts(color="#fff")),
tooltip_opts=opts.TooltipOpts(is_show=True),
# 设置白色主题
visualmap_opts=opts.VisualMapOpts(is_show=False, max_=50, min_=0, range_color=["#FFFFFF", "#FFFFFF"]),
)
)
return wordcloud.render_embed()
def get_play_time1(self, play_time):
"""格式化时间，全部转为小时(int)"""
# 是否为时间段，时间段默认按最长的时间计算
if(' - ' in play_time):
play_time = play_time.split(' - ')[-1]
# 开始格式化
hour = 0
if('小时' in play_time):
hour = float(play_time.replace("小时", ""))
elif("天" in play_time):
hour = int(play_time.replace("天", "")) * 24
# print(f"{play_time} --> {str(hour)}小时")
return hour
def get_p6(self,h, w, is_show=False):
"""6: 浏览时间折线图"""
qs = Scenery.objects.filter(play_time__isnull=False).all()
df_p6 = read_frame(qs)
df_p6["play_time"]=df_p6["play_time"].map(lambda x: self.get_play_time1(x))
play_time_data = df_p6.groupby("play_time")["scenery_name"].count()
# print(play_time_data)
# [[i[0], int(i[1])] for i in zip(map_data.index, map_data.values)]
p6 = (
Line(init_opts=opts.InitOpts(height=h, width=w))
.add_xaxis([str(i) + "小时" for i in play_time_data.index.tolist()])
.add_yaxis("景点数量", play_time_data.values.tolist(), is_smooth=True,
label_opts=opts.LabelOpts(is_show=is_show, color="#fff"))
.set_series_opts(
areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
)
.set_global_opts(
legend_opts=opts.LegendOpts(is_show=is_show, textstyle_opts=opts.TextStyleOpts(color="white")),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color="#fff"),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#fff")),
splitline_opts=opts.SplitLineOpts(is_show=True,
linestyle_opts=opts.LineStyleOpts(
color="#fff")),
axistick_opts=opts.AxisTickOpts(is_align_with_label=True),
is_scale=False,
boundary_gap=False,
),
yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color="#fff"),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#fff")),
splitline_opts=opts.SplitLineOpts(is_show=True,
linestyle_opts=opts.LineStyleOpts(
color="#fff")))
)
)
return p6.render_embed()
def get_p7(self,h, w, is_show=False):
"""7: 评分折线图"""
df_p7 = read_frame(self.scenery_obj)
# print(df_p7["scenery_name"].tolist())
p7 = (
Line(init_opts=opts.InitOpts(height=h, width=w))
.add_xaxis(df_p7["scenery_name"].tolist())
.add_yaxis("景点评分", df_p7["score"].tolist(), is_smooth=True,
label_opts=opts.LabelOpts(is_show=is_show, color="#fff"))
.set_series_opts(
areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
)
.set_global_opts(
legend_opts=opts.LegendOpts(is_show=is_show, textstyle_opts=opts.TextStyleOpts(color="white")),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color="#fff"),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#fff")),
splitline_opts=opts.SplitLineOpts(is_show=True,
linestyle_opts=opts.LineStyleOpts(
color="#fff")),
axistick_opts=opts.AxisTickOpts(is_align_with_label=True),
is_scale=False,
boundary_gap=False,
),
yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color="#fff"),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#fff")),
splitline_opts=opts.SplitLineOpts(is_show=True,
linestyle_opts=opts.LineStyleOpts(
color="#fff")))
)
)
return p7.render_embed()
def get_p8(self,h, w, is_show=False):
"""8: 景点数量折线图"""
p8 = (
Line(init_opts=opts.InitOpts(height=h, width=w))
.add_xaxis(self.map_data.index.tolist())
.add_yaxis("景点数量", self.map_data.values.tolist(), is_smooth=True,
label_opts=opts.LabelOpts(is_show=is_show, color="#fff"))
.set_series_opts(
areastyle_opts=opts.AreaStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
)
.set_global_opts(
legend_opts=opts.LegendOpts(is_show=is_show, textstyle_opts=opts.TextStyleOpts(color="white")),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color="#fff"),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#fff")),
splitline_opts=opts.SplitLineOpts(is_show=True,
linestyle_opts=opts.LineStyleOpts(
color="#fff")),
axistick_opts=opts.AxisTickOpts(is_align_with_label=True),
is_scale=False,
boundary_gap=False,
),
yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color="#fff"),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#fff")),
splitline_opts=opts.SplitLineOpts(is_show=True,
linestyle_opts=opts.LineStyleOpts(
color="#fff")))
)
)
return p8.render_embed()