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DataStruct 使用指南 ​

基本使用 ​

创建数据结构 ​

python
import pandas as pd
from FQData.DataStruct import StockDayData

df = pd.DataFrame({
    'date': pd.date_range('2024-01-01', periods=100),
    'code': '600000',
    'open': 10.0,
    'high': 10.5,
    'low': 9.8,
    'close': 10.2,
    'volume': 1000000
})

stock_day = StockDayData(df)
print(stock_day)
# < StockDayData with 1 securities >

访问数据 ​

python
print(f"证券代码: {stock_day.code.tolist()}")
print(f"开盘价: {stock_day.open.head()}")
print(f"收盘价: {stock_day.close.head()}")
print(f"成交量: {stock_day.volume.head()}")
print(f"数据长度: {len(stock_day)}")

数据类型 ​

股票数据 ​

python
from FQData.DataStruct import StockDayData, StockMinData

stock_day = StockDayData(df)

stock_min = StockMinData(min_df)

指数数据 ​

python
from FQData.DataStruct import IndexDayData, IndexMinData

index_day = IndexDayData(df)
index_min = IndexMinData(min_df)

期货数据 ​

python
from FQData.DataStruct import FutureDayData, FutureMinData

future_day = FutureDayData(df)
future_min = FutureMinData(min_df)

债券数据 ​

python
from FQData.DataStruct import Bond2StockDayData, Bond2StockMinData

bond_day = Bond2StockDayData(df)
bond_min = Bond2StockMinData(min_df)

数据操作 ​

切片访问 ​

python
first_10 = stock_day[:10]
last_10 = stock_day[-10:]

subset = stock_day[(stock_day.close > 10) & (stock_day.volume > 1000000)]

数据合并 ​

python
combined = stock_day_1 + stock_day_2

数据相减 ​

python
result = stock_day_all - stock_day_subset

反转数据 ​

python
reversed_data = stock_day.reverse()

数据转换 ​

转换为 DataFrame ​

python
df = stock_day.to_df()

转换为列表 ​

python
data_list = stock_day.to_list()

转换为字典 ​

python
data_dict = stock_day.to_dict('index')

转换为 numpy ​

python
np_array = stock_day.to_numpy()

分组与聚合 ​

按证券分组 ​

python
grouped = stock_day.groupby(level=1)

for code, group in grouped:
    print(f"证券代码: {code}, 数据量: {len(group)}")

应用函数 ​

python
def calc_return(data):
    return (data.close.iloc[-1] / data.close.iloc[0] - 1) * 100

returns = stock_day.add_func(calc_return)

滚动计算 ​

python
rolling_avg = stock_day.groupby(level=1).rolling(5).mean()

指标计算 ​

假设 stock_day 是 StockDayData 实例：

python
returns = stock_day.returns()

ma5 = stock_day.ma(5)
ma10 = stock_day.ma(10)
ma20 = stock_day.ma(20)

volatility = stock_day.volatility()

数据拆分 ​

按证券拆分 ​

python
splits = stock_day.splits

for stock in splits:
    print(f"代码: {stock.code[0]}, 长度: {len(stock)}")

拆分字典 ​

python
split_dict = stock_day.split_dicts

for code, data in split_dict.items():
    print(f"{code}: {len(data)} 条记录")

生成器 ​

面板迭代 ​

python
for panel in stock_day.panel_gen:
    print(f"日期: {panel.date}")

K 线迭代 ​

python
for idx, bar in stock_day.bar_gen:
    print(f"时间: {idx}, 收盘价: {bar['close']}")

证券迭代 ​

python
for stock in stock_day.security_gen:
    print(f"代码: {stock.code[0]}")

复权处理 ​

获取复权因子 ​

python
from FQData.DataStruct import fetch_stock_adj, fetch_stock_xdxr

adj_data = fetch_stock_adj(code='600000', start='2024-01-01')

xdxr_data = fetch_stock_xdxr(code='600000')

前复权转换 ​

python
from FQData.DataStruct import data_stock_to_fq

fq_data = data_stock_to_fq(original_data, adj_data)

stock_day_fq = StockDayData(fq_data, if_fq='qfq')

后复权转换 ​

python
from FQData.DataStruct import data_stock_fq_adj

hfq_data = data_stock_fq_adj(original_data, adj_data)

stock_day_hfq = StockDayData(hfq_data, if_fq='hfq')

数据重采样 ​

Tick 转 1 分钟 ​

python
from FQData.DataStruct import tick_resample_1min

min_data = tick_resample_1min(tick_data)

分钟重采样 ​

python
from FQData.DataStruct import min_resample

data_5min = min_resample(min_data, freq='5min')
data_15min = min_resample(min_data, freq='15min')
data_30min = min_resample(min_data, freq='30min')
data_60min = min_resample(min_data, freq='60min')

分钟转日线 ​

python
from FQData.DataStruct import min_to_day

daily_data = min_to_day(min_data)

日线重采样 ​

python
from FQData.DataStruct import day_resample

weekly = day_resample(daily, freq='W')
monthly = day_resample(daily, freq='M')
quarterly = day_resample(daily, freq='Q')
yearly = day_resample(daily, freq='Y')

期货分钟重采样 ​

python
from FQData.DataStruct import futuremin_resample

resampled = futuremin_resample(future_min, freq='5min')

实时数据 ​

python
from FQData.DataStruct import StockRealtimeData, FutureRealtimeData

stock_realtime = StockRealtimeData(code='600000')

future_realtime = FutureRealtimeData(code='IF2401')

from FQData.DataStruct import RealtimeSeries

series = RealtimeSeries(codes=['600000', '000001', '000002'])

查询操作 ​

数据查询 ​

python
result = stock_day.query('close > 10')

查找 Bar ​

python
bar = stock_day.find_bar('600000', '2024-01-15')
bar = stock_day.find_bar('600000', '2024-01-15 09:30:00')

获取字典 ​

python
data = stock_day.get_dict('2024-01-15', '600000')

流通市值 ​

python
from FQData.DataStruct import calc_marketvalue, data_marketvalue

mv = calc_marketvalue(data, adj_data)

mv_data = data_marketvalue(code='600000', start='2024-01-01')

多证券数据 ​

python
df_multi = pd.DataFrame({
    'date': pd.date_range('2024-01-01', periods=100).repeat(3),
    'code': ['600000'] * 100 + ['000001'] * 100 + ['000002'] * 100,
    'open': 10.0,
    'high': 10.5,
    'low': 9.8,
    'close': 10.2,
    'volume': 1000000
})

stock_multi = StockDayData(df_multi)
print(f"证券数量: {len(stock_multi.code)}")
print(f"证券列表: {stock_multi.code.tolist()}")

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