3.10 Enhance data analysis components with type conversion and UI improvements
- Added type conversion for relevant columns in `VolumeAnalyzer` and `PriceMovementAnalyzer` to ensure consistent data handling and avoid type errors. - Refactored the `create_data_analysis_panel` function to implement a tabbed interface for volume and price movement analysis, improving user experience and organization of analysis tools. - Updated styles in `indicator_modal.py` for better layout and responsiveness of the modal component. - Marked unit testing of dashboard components as complete in the task list.
This commit is contained in:
Vasily.onl
parent
b4798bfc07
commit
38cbf9cd2f
@ -32,6 +32,15 @@ class VolumeAnalyzer:
|
||||
if df.empty or 'volume' not in df.columns:
|
||||
return {'error': 'DataFrame is empty or missing volume column'}
|
||||
|
||||
# Convert all relevant columns to float to avoid type errors with Decimal
|
||||
df = df.copy()
|
||||
numeric_cols = ['open', 'high', 'low', 'close', 'volume']
|
||||
for col in numeric_cols:
|
||||
if col in df.columns:
|
||||
df[col] = df[col].astype(float)
|
||||
if 'trades_count' in df.columns:
|
||||
df['trades_count'] = df['trades_count'].astype(float)
|
||||
|
||||
# Calculate volume statistics
|
||||
total_volume = df['volume'].sum()
|
||||
avg_volume = df['volume'].mean()
|
||||
@ -93,6 +102,13 @@ class PriceMovementAnalyzer:
|
||||
if df.empty or not all(col in df.columns for col in ['open', 'high', 'low', 'close']):
|
||||
return {'error': 'DataFrame is empty or missing required price columns'}
|
||||
|
||||
# Convert all relevant columns to float to avoid type errors with Decimal
|
||||
df = df.copy()
|
||||
numeric_cols = ['open', 'high', 'low', 'close', 'volume']
|
||||
for col in numeric_cols:
|
||||
if col in df.columns:
|
||||
df[col] = df[col].astype(float)
|
||||
|
||||
# Basic price statistics
|
||||
current_price = df['close'].iloc[-1]
|
||||
period_start_price = df['open'].iloc[0]
|
||||
@ -434,55 +450,28 @@ def create_price_movement_chart(symbol: str, timeframe: str = "1h", days_back: i
|
||||
|
||||
|
||||
def create_data_analysis_panel():
|
||||
"""Create the data analysis panel with volume and price movement tools."""
|
||||
"""Create the main data analysis panel with tabs for different analyses."""
|
||||
return html.Div([
|
||||
html.H3("📊 Data Analysis Tools", style={'margin-bottom': '20px'}),
|
||||
|
||||
# Analysis type selection - using regular dropdown instead of SegmentedControl
|
||||
html.Div([
|
||||
html.Label("Analysis Type:", style={'font-weight': 'bold', 'margin-right': '10px'}),
|
||||
dcc.Dropdown(
|
||||
id="analysis-type-selector",
|
||||
options=[
|
||||
{"label": "Volume Analysis", "value": "volume"},
|
||||
{"label": "Price Movement", "value": "price"},
|
||||
{"label": "Combined Stats", "value": "combined"}
|
||||
],
|
||||
value="volume",
|
||||
clearable=False,
|
||||
style={'width': '200px', 'display': 'inline-block'}
|
||||
)
|
||||
], style={'margin-bottom': '20px'}),
|
||||
|
||||
# Time period selector - using regular dropdown
|
||||
html.Div([
|
||||
html.Label("Analysis Period:", style={'font-weight': 'bold', 'margin-right': '10px'}),
|
||||
dcc.Dropdown(
|
||||
id="analysis-period-selector",
|
||||
options=[
|
||||
{"label": "1 Day", "value": "1"},
|
||||
{"label": "3 Days", "value": "3"},
|
||||
{"label": "7 Days", "value": "7"},
|
||||
{"label": "14 Days", "value": "14"},
|
||||
{"label": "30 Days", "value": "30"}
|
||||
],
|
||||
value="7",
|
||||
clearable=False,
|
||||
style={'width': '150px', 'display': 'inline-block'}
|
||||
)
|
||||
], style={'margin-bottom': '20px'}),
|
||||
|
||||
# Charts container
|
||||
html.Div(id="analysis-chart-container", children=[
|
||||
html.P("Chart container loaded - waiting for callback...")
|
||||
]),
|
||||
|
||||
# Statistics container
|
||||
html.Div(id="analysis-stats-container", children=[
|
||||
html.P("Stats container loaded - waiting for callback...")
|
||||
])
|
||||
|
||||
], style={'border': '1px solid #ccc', 'padding': '20px', 'margin-top': '20px'})
|
||||
dcc.Tabs(
|
||||
id="data-analysis-tabs",
|
||||
value="volume-analysis",
|
||||
children=[
|
||||
dcc.Tab(label="Volume Analysis", value="volume-analysis", children=[
|
||||
html.Div(id='volume-analysis-content', children=[
|
||||
html.P("Content for Volume Analysis")
|
||||
]),
|
||||
html.Div(id='volume-stats-container', children=[
|
||||
html.P("Stats container loaded - waiting for callback...")
|
||||
])
|
||||
]),
|
||||
dcc.Tab(label="Price Movement", value="price-movement", children=[
|
||||
html.Div(id='price-movement-content', children=[
|
||||
dmc.Alert("Select a symbol and timeframe to view price movement analysis.", color="blue")
|
||||
])
|
||||
]),
|
||||
],
|
||||
)
|
||||
], id='data-analysis-panel-wrapper')
|
||||
|
||||
|
||||
def format_number(value: float, decimals: int = 2) -> str:
|
||||
|
||||
@ -262,22 +262,15 @@ def create_indicator_modal():
|
||||
}
|
||||
),
|
||||
html.Div(id='save-indicator-feedback', style={'margin-top': '10px'})
|
||||
], style={'text-align': 'right', 'border-top': '1px solid #eee', 'padding-top': '15px'})
|
||||
|
||||
], style={'display': 'flex', 'justify-content': 'flex-end', 'margin-top': '20px', 'border-top': '1px solid #eee', 'padding-top': '15px'})
|
||||
], style={
|
||||
'background-color': 'white',
|
||||
'margin': '5% auto',
|
||||
'padding': '30px',
|
||||
'background': 'white',
|
||||
'padding': '20px',
|
||||
'border-radius': '8px',
|
||||
'box-shadow': '0 4px 6px rgba(0, 0, 0, 0.1)',
|
||||
'width': '600px',
|
||||
'max-width': '90%',
|
||||
'max-height': '80%',
|
||||
'overflow-y': 'auto'
|
||||
'box-shadow': '0 4px 8px rgba(0,0,0,0.1)'
|
||||
})
|
||||
],
|
||||
id='indicator-modal',
|
||||
style={
|
||||
], id='indicator-modal-content', style={
|
||||
'display': 'none',
|
||||
'position': 'fixed',
|
||||
'z-index': '1001',
|
||||
|
||||
@ -88,7 +88,7 @@
|
||||
- [x] 3.7 Add the chart time range selector and trigger for realtime data or historical data (when i analyze specified time range i do not want it to reset with realtime data triggers and callbacks)
|
||||
- [-] 3.8 Setup real-time dashboard updates using Redis callbacks (DEFERRED: Redis is not used for real-time dashboard updates now)
|
||||
- [x] 3.9 Add data export functionality for analysis (CSV/JSON export)
|
||||
- [ ] 3.10 Unit test basic dashboard components and data visualization
|
||||
- [x] 3.10 Unit test basic dashboard components and data visualization
|
||||
|
||||
- [ ] 4.0 Strategy Engine and Bot Management Framework
|
||||
- [ ] 4.1 Design and implement base strategy interface class
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user