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https://ghfast.top/https://github.com/aeroxw/easy-tdx.git
synced 2026-09-12 19:14:16 +08:00
Justin Gu
00825eb24a
- K-line: daily+ periods output 'date' only, minute periods output 'datetime' - Transactions (tick-by-tick): combine date param + hour/minute into 'datetime' - XdxrRecord, HistoricalFundFlow: year/month/day merged to 'date' - MinuteBar: rename unknown_1 to _unknown_1 (hidden from DataFrame) - MinuteBar: add datetime column computed from bar index (A-share 240-bar pattern) - get_minute_time_data: use history endpoint only (current-day endpoint broken in pytdx too) - Update all examples to reflect new DataFrame column names
24 lines
913 B
Python
24 lines
913 B
Python
"""演示：获取个股当日资金流向（基于 L1 逐笔数据统计）。
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资金分为四级: 超大(>100万)、大(20-100万)、中(4-20万)、小(<4万)。
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"""
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import pandas as pd
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from easy_tdx import Market, TdxClient
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with TdxClient.from_best_host() as c:
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flow = c.get_fund_flow(Market.SH, "600519")
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# flow 是单行 DataFrame，转换为万元便于阅读
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in_cols = ["super_in", "large_in", "medium_in", "small_in"]
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out_cols = ["super_out", "large_out", "medium_out", "small_out"]
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df = pd.DataFrame(
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{
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"级别": ["超大单", "大单", "中单", "小单"],
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"流入(亿)": [flow[c].iloc[0] / 1e8 for c in in_cols],
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"流出(亿)": [flow[c].iloc[0] / 1e8 for c in out_cols],
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}
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)
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df["净流入(亿)"] = df["流入(亿)"] - df["流出(亿)"]
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print("贵州茅台 当日资金流向:")
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print(df.to_string(index=False))
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