第Python采集股票數(shù)據(jù)并制作可視化柱狀圖目錄前言模塊使用開發(fā)環(huán)境代碼實(shí)現(xiàn)步驟代碼數(shù)據(jù)可視化

前言

嗨嘍！大家好呀，這里是魔王~

雪球,聰明的投資者都在這里-4300萬投資者都在用的投資社區(qū),

滬深港美全球市場實(shí)時行情,股票基金債券免費(fèi)資訊,與投資高手實(shí)戰(zhàn)交流。

模塊使用

requestspipinstallrequests(數(shù)據(jù)請求第三方模塊)

re#正則表達(dá)式去匹配提取數(shù)據(jù)

json

pandas

pyecharts

開發(fā)環(huán)境

Python3.8解釋器

Pycharm2025.2版本

代碼實(shí)現(xiàn)步驟

發(fā)送請求訪問網(wǎng)站獲取數(shù)據(jù)解析數(shù)據(jù)(提取數(shù)據(jù))保存數(shù)據(jù)做柱狀圖簡單的可視化

代碼

#1.發(fā)送請求訪問網(wǎng)站

headers={

'User-Agent':'Mozilla/5.0(WindowsNT10.0;Win64;x64)AppleWebKit/537.36(KHTML,likeGecko)Chrome/97.0.4692.71Safari/537.36'

url='/service/v5/stock/screener/quote/listpage=1size=30order=descorder_by=amountexchange=CNmarket=CNtype=sha_=1641730868838'

response=requests.get(url=url,headers=headers)

#2.獲取數(shù)據(jù)

json_data=response.json()

#3.數(shù)據(jù)解析(篩選數(shù)據(jù))

data_list=json_data['data']['list']

fordataindata_list:

data1=data['symbol']

data2=data['name']

data3=data['current']

data4=data['chg']

data5=data['percent']

data6=data['current_year_percent']

data7=data['volume']

data8=data['amount']

data9=data['turnover_rate']

data10=data['pe_ttm']

data11=data['dividend_yield']

data12=data['market_capital']

print(data1,data2,data3,data4,data5,data6,data7,data8,data9,data10,data11,data12)

data_dict={

'股票代碼':data1,

'股票名稱':data2,

'當(dāng)前價':data3,

'漲跌額':data4,

'漲跌幅':data5,

'年初至今':data6,

'成交量':data7,

'成交額':data8,

'換手率':data9,

'市盈率(TTM)':data10,

'股息率':data11,

'市值':data12,

csv_write.writerow(data_dict)

4.保存地址

file=open('data2.csv',mode='a',encoding='utf-8',newline='')

csv_write=csv.DictWriter(file,fieldnames=['股票代碼','股票名稱','當(dāng)前價','漲跌額','漲跌幅','年初至今','成交量','成交額','換手率','市盈率(TTM)','股息率','市值'])

csv_write.writeheader()

運(yùn)行效果

數(shù)據(jù)可視化

data_df=pd.read_csv('data2.csv')

df=data_df.dropna()