File size: 2,547 Bytes
6164f9e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import os
# --- 1. File Selection ---
file_name = 'XAUUSDc_M3_data.csv'
def process_and_plot_rdbs(csv_file_path):
if not os.path.exists(csv_file_path):
print(f"Error: {csv_file_path} not found.")
return
# Load and clean headers
df = pd.read_csv(csv_file_path, skipinitialspace=True)
df.columns = df.columns.str.strip().str.replace('\ufeff', '')
# Parse time and sort
df['time'] = pd.to_datetime(df['time'], errors='coerce')
df.dropna(subset=['time'], inplace=True)
df.sort_values('time', inplace=True)
df.reset_index(drop=True, inplace=True)
# Calculate Indicator: RDBSin = individual range / spread
# RDBSin_value calculation
df['range'] = df['high'] - df['low']
df['RDBSin'] = df['range'] / df['spread']
# Identify time gaps (M3 = 3 minutes)
expected_diff = pd.Timedelta(minutes=3)
df['TimeDiff'] = df['time'].diff()
gaps = df[df['TimeDiff'] > expected_diff]
# Create Subplots
fig = make_subplots(
rows=2, cols=1,
shared_xaxes=True,
vertical_spacing=0.05,
row_heights=[0.7, 0.3]
)
# Top Pane: OHLC Candlestick
fig.add_trace(
go.Candlestick(
x=df['time'],
open=df['open'],
high=df['high'],
low=df['low'],
close=df['close'],
name='XAUUSD OHLC'
),
row=1, col=1
)
# Bottom Pane: RDBSin Indicator
fig.add_trace(
go.Scatter(
x=df['time'],
y=df['RDBSin'],
mode='lines',
name='RDBSin',
line=dict(color='blue', width=1.5)
),
row=2, col=1
)
# Visualizing Gaps: Red with 10% opacity
for idx, row in gaps.iterrows():
start_time = df['time'].iloc[idx-1]
end_time = row['time']
fig.add_vrect(
x0=start_time, x1=end_time,
fillcolor="red", opacity=0.1,
line_width=0, row="all", col=1
)
# Formatting
fig.update_layout(
template="plotly_white",
title="XAUUSD M3: RDBS Indicator Analysis",
xaxis_rangeslider_visible=False,
height=900,
showlegend=True
)
fig.update_yaxes(title_text="Price", row=1, col=1)
fig.update_yaxes(title_text="RDBSin Value", row=2, col=1)
fig.show(renderer="colab")
# Execute
process_and_plot_rdbs(file_name) |