回答編集履歴
4
欠損処理忘れていたので追加
test
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@@ -96,7 +96,9 @@
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# 上昇2、下降1、変動なし3、欠損None
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df_diff["Sign"] = df_diff["CalcPrice"].apply(lambda x: 1 if x < 0 else 2 if x > 0 else 3)
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df_diff["Sign"] = df_diff["CalcPrice"].apply((lambda x: 1 if x < 0 else 2 if x > 0 else 3 if x == 0 else None))
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3
30秒の条件訂正
test
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@@ -102,7 +102,7 @@
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# 30秒以内変動がないものを欠損
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df_diff["Sign"] = df_diff["Sign"].mask((df_diff["CurrentPriceTime"]
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df_diff["Sign"] = df_diff["Sign"].mask((df_diff["CurrentPriceTime"] < pd.Timedelta(seconds=30)) & (df_diff["Sign"] == 3))
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2
勘違いしていたので修正
test
CHANGED
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@@ -1,6 +1,6 @@
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1
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9:00から15:00の内11:30から12:30は
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1
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9:00から15:00の内11:30から12:30は0
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2
2
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3
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同一銘柄の
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3
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同一銘柄のを上がったら2、下がったら1、変動なしのうち30秒以上は3、30秒以内は欠損にしています
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@@ -74,7 +74,7 @@
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InTime= df["CurrentPriceTime"].dt.time.apply(
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lambda d: (datetime.time(8) < d < datetime.time(11, 30))
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@@ -84,7 +84,7 @@
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df1 = df.loc[
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df1 = df.loc[:, ["SymbolName", "CurrentPriceTime", "CalcPrice"]]
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@@ -96,17 +96,23 @@
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# 30秒以上は欠損
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df_diff["
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df_diff["Sign"] = df_diff["CalcPrice"].apply(lambda x: 1 if x < 0 else 2 if x > 0 else 3)
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df_diff["CurrentPriceTime"] < pd.Timedelta(seconds=30)
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)
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# 30秒以内変動がないものを欠損
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df["Sign"] = df_diff["C
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df_diff["Sign"] = df_diff["Sign"].mask((df_diff["CurrentPriceTime"] > pd.Timedelta(seconds=30)) & (df_diff["Sign"] == 3))
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# 時間外を0
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df_diff.loc[~InTime, "Sign"] = 0
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df["Sign"] = df_diff["Sign"]
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1
抽出の書き方変更
test
CHANGED
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@@ -84,7 +84,7 @@
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df1 = df[df["InTime"]
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df1 = df.loc[df["InTime"], ["SymbolName", "CurrentPriceTime", "CalcPrice"]]
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