How to plot the ICHIMOKU indicator using python and plotly

In this micro video you will learn: How to plot the Ichimoku indicator using python and plotly
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Code Snippet: ?

import plotly.graph_objs as go
import pandas as pd
import numpy as np
import yfinance as yf

# Load data
df = yf.download('^HSI', period='1y')

# Calculate Ichimoku indicator
high = df['High']
low = df['Low']
close = df['Close']
conversion_period = 9
base_period = 26
lagging_line_period = 52
displacement = 26

# Tenkan-sen (Conversion Line)
conversion_line_high = high.rolling(window=conversion_period).max()
conversion_line_low = low.rolling(window=conversion_period).min()
conversion_line = (conversion_line_high + conversion_line_low) / 2

# Kijun-sen (Base Line)
base_line_high = high.rolling(window=base_period).max()
base_line_low = low.rolling(window=base_period).min()
base_line = (base_line_high + base_line_low) / 2

# Senkou Span A (Leading Span A)
leading_span_a = ((conversion_line + base_line) / 2).shift(displacement)

# Senkou Span B (Leading Span B)
lagging_line = close.shift(-lagging_line_period)
lagging_line_high = lagging_line.rolling(window=base_period).max()
lagging_line_low = lagging_line.rolling(window=base_period).min()
leading_span_b = ((lagging_line_high + lagging_line_low) / 2).shift(displacement)

# Plot candlestick chart
fig = go.Figure(data=[go.Candlestick(x=df.index,
open=df['Open'],
high=df['High'],
low=df['Low'],
close=df['Close'],
name='Candlestick')])

# Plot Tenkan-sen and Kijun-sen
fig.add_trace(go.Scatter(x=df.index, y=conversion_line, line=dict(color='orange', width=1), name='Tenkan-sen'))
fig.add_trace(go.Scatter(x=df.index, y=base_line, line=dict(color='blue', width=1), name='Kijun-sen'))

# Plot Senkou Span A and Senkou Span B as a filled area
fig.add_trace(go.Scatter(x=df.index, y=leading_span_a, line=dict(color='green', width=1), fill='tonexty', name='Senkou Span A'))
fig.add_trace(go.Scatter(x=df.index, y=leading_span_b, line=dict(color='red', width=1), fill='tonexty', name='Senkou Span B'))
Ichimoku indicator
# Add titles and axis labels
fig.update_layout(title='Ichimoku Indicator',
xaxis_title='Date',
yaxis_title='Price (€)')

# Show the plot
fig.show()


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#python #ichimoku #plotly