知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
105 lines
3.7 KiB
Python
105 lines
3.7 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2024/5/12 22:30
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Desc: 百度地图慧眼-百度迁徙数据
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"""
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import json
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import pandas as pd
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import requests
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from akshare.event.cons import province_dict, city_dict
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def migration_area_baidu(
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area: str = "重庆市", indicator: str = "move_in", date: str = "20230922"
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) -> pd.DataFrame:
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"""
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百度地图慧眼-百度迁徙-XXX迁入地详情
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百度地图慧眼-百度迁徙-XXX迁出地详情
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以上展示 top100 结果，如不够 100 则展示全部
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迁入来源地比例: 从 xx 地迁入到当前区域的人数与当前区域迁入总人口的比值
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迁出目的地比例: 从当前区域迁出到 xx 的人口与从当前区域迁出总人口的比值
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https://qianxi.baidu.com/?from=shoubai#city=0
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:param area: 可以输入 省份 或者 具体城市 但是需要用全称
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:type area: str
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:param indicator: move_in 迁入 move_out 迁出
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:type indicator: str
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:param date: 查询的日期 20200101 以后的时间
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:type date: str
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:return: 迁入地详情/迁出地详情的前 50 个
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:rtype: pandas.DataFrame
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"""
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city_dict.update(province_dict)
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inner_dict = dict(zip(city_dict.values(), city_dict.keys()))
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if inner_dict[area] in province_dict.keys():
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dt_flag = "province"
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else:
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dt_flag = "city"
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url = "https://huiyan.baidu.com/migration/cityrank.jsonp"
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params = {
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"dt": dt_flag,
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"id": inner_dict[area],
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"type": indicator,
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"date": date,
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}
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r = requests.get(url, params=params)
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data_text = r.text[r.text.find("({") + 1 : r.text.rfind(");")]
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data_json = json.loads(data_text)
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temp_df = pd.DataFrame(data_json["data"]["list"])
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temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
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return temp_df
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def migration_scale_baidu(
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area: str = "广州市",
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indicator: str = "move_in",
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) -> pd.DataFrame:
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"""
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百度地图慧眼-百度迁徙-迁徙规模
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迁徙规模指数：反映迁入或迁出人口规模，城市间可横向对比城市迁徙边界采用该城市行政区划，包含该城市管辖的区、县、乡、村
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https://qianxi.baidu.com/?from=shoubai#city=0
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:param area: 可以输入 省份 或者 具体城市 但是需要用全称
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:type area: str
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:param indicator: move_in 迁入 move_out 迁出
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:type indicator: str
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:return: 时间序列的迁徙规模指数
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:rtype: pandas.DataFrame
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"""
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city_dict.update(province_dict)
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inner_dict = dict(zip(city_dict.values(), city_dict.keys()))
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if inner_dict[area] in province_dict.keys():
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dt_flag = "province"
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else:
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dt_flag = "city"
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url = "https://huiyan.baidu.com/migration/historycurve.jsonp"
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params = {
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"dt": dt_flag,
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"id": inner_dict[area],
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"type": indicator,
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}
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r = requests.get(url, params=params)
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json_data = json.loads(r.text[r.text.find("({") + 1 : r.text.rfind(");")])
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temp_df = pd.DataFrame.from_dict(json_data["data"]["list"], orient="index")
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temp_df.index = pd.to_datetime(temp_df.index)
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temp_df.reset_index(inplace=True)
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temp_df.columns = ["日期", "迁徙规模指数"]
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temp_df["日期"] = pd.to_datetime(temp_df["日期"], errors="coerce").dt.date
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temp_df["迁徙规模指数"] = pd.to_numeric(temp_df["迁徙规模指数"], errors="coerce")
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return temp_df
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if __name__ == "__main__":
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migration_area_baidu_df = migration_area_baidu(
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area="杭州市", indicator="move_out", date="20240401"
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)
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print(migration_area_baidu_df)
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migration_scale_baidu_df = migration_scale_baidu(
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area="广州市",
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indicator="move_in",
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)
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print(migration_scale_baidu_df)
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