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testing cache
Browse files- app.py +2 -1
- research_hod_lod.ipynb +0 -0
app.py
CHANGED
@@ -37,6 +37,7 @@ def convert_to_datetime(time_str, pst_now):
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return datetime.combine(pst_now.date(), time_obj.time())
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# Function to determine the emoji for each time
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def get_time_emojis(times, pst_now):
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pst_now_time = pst_now.time()
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us_holidays = get_us_holidays()
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@@ -432,7 +433,7 @@ with st.form("choose_model"):
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# st.subheader('New Prediction')
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int_labels = ['(
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# df_probas = res1.groupby(pd.qcut(res1['Predicted'],5)).agg({'True':[np.mean,len,np.sum]})
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data['ClosePct'] = (data['Close'] / data['PrevClose']) - 1
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return datetime.combine(pst_now.date(), time_obj.time())
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# Function to determine the emoji for each time
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@st.cache_data
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def get_time_emojis(times, pst_now):
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pst_now_time = pst_now.time()
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us_holidays = get_us_holidays()
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# st.subheader('New Prediction')
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int_labels = ['(0, .20]', '(.20, .40]', '(.40, .60]', '(.60, .80]', '(.80, .1]']
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# df_probas = res1.groupby(pd.qcut(res1['Predicted'],5)).agg({'True':[np.mean,len,np.sum]})
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data['ClosePct'] = (data['Close'] / data['PrevClose']) - 1
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research_hod_lod.ipynb
CHANGED
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