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place_analysis.py
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place_analysis.py
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import re
import numpy as np
import pandas as pd
from pyecharts import options as opts
from pyecharts.charts import Bar
"""
获取详细教程、获取代码帮助、提出意见建议
关注微信公众号「裸睡的猪」与猪哥联系
@Author : 猪哥
"""
# 去哪儿热门景点excel文件保存路径
PLACE_EXCEL_PATH = 'qunar_place.xlsx'
# 读取数据
DF = pd.read_excel(PLACE_EXCEL_PATH)
# 百度热力图模板
HOT_MAP_TEMPLATE_PATH = 'hot_map_template.html'
# 生成的国庆旅游景点热力图
PLACE_HOT_MAP_PATH = 'place_hot_map.html'
def analysis_sale():
"""
分析销量
:return:
"""
# 引入全局数据
global DF
df = DF.copy()
# 1、生成一个名称和销量的透视表
place_sale = df.pivot_table(index='name', values='sale')
# 2、根据销量排序
place_sale.sort_values('sale', inplace=True, ascending=True)
print(place_sale)
# 3、生成柱状图
place_sale_bar = (
Bar()
.add_xaxis(place_sale.index.tolist()[-20:])
.add_yaxis("", list(map(int, np.ravel(place_sale.values)))[-20:])
.reversal_axis()
.set_series_opts(label_opts=opts.LabelOpts(position="right"))
.set_global_opts(
title_opts=opts.TitleOpts(title="国庆旅游热门景点门票销量TOP20"),
yaxis_opts=opts.AxisOpts(name="景点名称"),
xaxis_opts=opts.AxisOpts(name="销量")
)
)
place_sale_bar.render('place-sale-bar.html')
def analysis_amount():
"""
分析销售额
:return:
"""
# 引入全局数据
global DF
df = DF.copy()
amount_list = []
for index, row in df.iterrows():
try:
# 销售额
amount = row['price'] * row['sale']
except Exception:
amount = 0
amount_list.append(amount)
df['amount'] = amount_list
# 生成一个名称和销量的透视表
place_amount = df.pivot_table(index='name', values='amount')
# 根据销售额排序
place_amount.sort_values('amount', inplace=True, ascending=True)
print(place_amount)
# 生成柱状图
place_amount_bar = (
Bar()
.add_xaxis(place_amount.index.tolist()[-20:])
.add_yaxis("", list(map(int, np.ravel(place_amount.values)))[-20:])
.reversal_axis()
.set_series_opts(label_opts=opts.LabelOpts(position="right"))
.set_global_opts(
title_opts=opts.TitleOpts(title="国庆旅游热门景点门票销售额TOP20"),
yaxis_opts=opts.AxisOpts(name="景点名称"),
xaxis_opts=opts.AxisOpts(name="销售额")
)
)
place_amount_bar.render('place-amount-bar.html')
def analysis_province():
"""
此功能未完成
分析省份旅游景点数
:return:
"""
# 引入全局数据
global DF
df = DF.copy()
province_list = []
for item in df.districts:
province_match = re.search(r'^([\u4e00-\u9fa5])*', item)
province_list.append(province_match[0])
print(province_list)
df['province'] = province_list
# province_star = df.groupby(['province', 'star'])
province_star = df.groupby(['province', 'star']).agg({'star': 'count'})
province_star_dict = {}
star = ['3A', '4A', '5A', '无']
star_index = 0
prev = ''
for province_star_index in province_star.index:
province_index = province_star_index[1]
if prev != province_index:
star_index = 0
province_star_dict['province_index'] = []
while True:
if province_index == star[star_index]:
province_star.star[province_star_index]
star_index += 1
province_star_dict
print(province_star)
def analysis_point_sale():
"""
生成热力图，使用百度地图api
:return:
"""
# 引入全局数据
global DF
df = DF.copy()
point_sale_list = []
for index, row in df.iterrows():
# 构建坐标数据
lng, lat = row['point'].split(',')
count = row['sale']
point_sale = {'lng': float(lng), 'lat': float(lat), 'count': count}
point_sale_list.append(point_sale)
print(point_sale_list)
data = f'var points ={str(point_sale_list)};'
# 替换模板中的坐标数据
with open(HOT_MAP_TEMPLATE_PATH, 'r', encoding="utf-8") as f1, open(PLACE_HOT_MAP_PATH, 'w',
encoding="utf-8") as f2:
s = f1.read()
# 替换数据
s2 = s.replace('%data%', data)
f2.write(s2)
f1.close()
f2.close()
def analysis_recommend():
"""
瞎推荐排行榜，高评分、销量少、价格便宜
:return:
"""
# 引入全局数据
global DF
df = DF.copy()
recommend_list = []
for index, row in df.iterrows():
try:
# 瞎推荐系数算法
recommend = (row['score'] * 1000) / (row['price'] * row['sale'])
except ZeroDivisionError:
recommend = 0
recommend_list.append(recommend)
df['recommend'] = recommend_list
# 生成一个名称和瞎推荐系数的透视表
place_recommend = df.pivot_table(index='name', values='recommend')
# 根据瞎推荐系数排序
place_recommend.sort_values('recommend', inplace=True, ascending=True)
print(place_recommend)
# 生成柱状图
place_recommend_bar = (
Bar()
.add_xaxis(place_recommend.index.tolist()[-20:])
.add_yaxis("", list(map(int, np.ravel(place_recommend.values)))[-20:])
.reversal_axis()
.set_series_opts(label_opts=opts.LabelOpts(position="right"))
.set_global_opts(
title_opts=opts.TitleOpts(title="国庆旅游热门景点瞎推荐TOP20"),
yaxis_opts=opts.AxisOpts(name="景点名称"),
xaxis_opts=opts.AxisOpts(name="瞎推荐系数")
)
)
place_recommend_bar.render('place-recommend-bar.html')
if __name__ == '__main__':
analysis_sale()
analysis_amount()
# analysis_province()
analysis_point_sale()
analysis_recommend()