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Handle missing median time data in metrics #6

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Handle missing median time data in metrics #6

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36 changes: 29 additions & 7 deletions streamlit_app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,10 @@ def seconds_to_time(seconds):
valid_times = [time_obj for time_obj in parsed_times if not pd.isna(time_obj)]

# Konvertieren zu Sekunden
seconds_list = [time_to_seconds(time_obj) for time_obj in valid_times]
seconds_list = [time_to_seconds(time_obj) for time_obj in valid_times if time_obj is not None]

if not seconds_list:
return None

# Median berechnen
median_seconds = sorted(seconds_list)[len(seconds_list) // 2]
Expand Down Expand Up @@ -369,8 +372,15 @@ def load_ml_model(symbol):
with col3:

median_time = median_time_calcualtion(df["breakout_time"])
st.metric("Median breakout time:", value=str(median_time),
delta=f"Mode breakout time: {df.breakout_time.mode()[0]}")
breakout_mode_series = df.breakout_time.dropna()
breakout_mode_values = breakout_mode_series.mode()
breakout_mode = breakout_mode_values[0] if not breakout_mode_values.empty else None
breakout_value = str(median_time) if median_time is not None else "No breakout time data"
breakout_delta = (f"Mode breakout time: {breakout_mode}" if breakout_mode is not None
else "Mode breakout time: N/A")

st.metric("Median breakout time:", value=breakout_value,
delta=breakout_delta)
breakout = st.button("See Distribution", key="breakout")

if breakout:
Expand All @@ -386,8 +396,14 @@ def load_ml_model(symbol):
else:
median_retracement_value = df.retracement_level.median()

st.metric("Median retracement before HoS/LoS:", value=str(median_retracement),
delta=f"Median retracement value: {median_retracement_value}",
retracement_value = (str(median_retracement)
if median_retracement is not None else "No retracement time data")
retracement_delta = (f"Median retracement value: {median_retracement_value}"
if not pd.isna(median_retracement_value)
else "Median retracement value: N/A")

st.metric("Median retracement before HoS/LoS:", value=retracement_value,
delta=retracement_delta,
)
retracement = st.button("See Distribution", key="retracement")

Expand All @@ -406,8 +422,14 @@ def load_ml_model(symbol):
else:
median_expansion_value = df.expansion_level.median()

st.metric("Median time of max expansion:", value=str(median_expansion),
delta=f"Median expansion value: {median_expansion_value}",
expansion_value = (str(median_expansion)
if median_expansion is not None else "No expansion time data")
expansion_delta = (f"Median expansion value: {median_expansion_value}"
if not pd.isna(median_expansion_value)
else "Median expansion value: N/A")

st.metric("Median time of max expansion:", value=expansion_value,
delta=expansion_delta,
)
expansion = st.button("See distribution", key="expansion")

Expand Down