How to add labels to candlestick plots?

Question

https://www.kaggle.com/tencars/interactive-bollinger-bands-for-technical-analysis

I use the above method to draw candlestick plots with Bollinger Bands.

Could anybody let me know how to add additional labels to label certain features of the plots. For example, label the local minimum "close"es with a triangle pointing upward and label the local maximum "close"es with a triangle pointing downward.

score 1 · Answer 1 · answered Jun 26 '21 at 04:17

Since I couldn't download the kaggle data presented, I got the AAPL stock price from Yahoo Finance and used it as data. For the graph itself, I used the code in kaggle to change the color of each line to make a graph. For the text annotations, I used add_annotation(). The annotated data was set appropriately.

import pandas as pd
from datetime import datetime
import plotly.graph_objects as go
import yfinance as yf

df = yf.download("AAPL", start="2021-06-21", interval='1m', end="2021-06-22")
df.reset_index(inplace=True)
df.columns =['time', 'open', 'high', 'low', 'close', 'adj close', 'volume']
# Create a working copy of the last 2 hours of the data
btc_data = df.iloc[-240:].copy()

# Define the parameters for the Bollinger Band calculation
ma_size = 20
bol_size = 2

# Convert the timestamp data to a human readable format
btc_data.index = pd.to_datetime(btc_data.time, unit='ms')

# Calculate the SMA
btc_data.insert(0, 'moving_average', btc_data['close'].rolling(ma_size).mean())

# Calculate the upper and lower Bollinger Bands
btc_data.insert(0, 'bol_upper', btc_data['moving_average'] + btc_data['close'].rolling(ma_size).std() * bol_size)
btc_data.insert(0, 'bol_lower', btc_data['moving_average'] - btc_data['close'].rolling(ma_size).std() * bol_size)

# Remove the NaNs -> consequence of using a non-centered moving average
btc_data.dropna(inplace=True)

# Create an interactive candlestick plot with Plotly
fig = go.Figure(data=[go.Candlestick(x = btc_data.index,
                                     open = btc_data['open'],
                                     high = btc_data['high'],
                                     low = btc_data['low'],
                                     showlegend = False,
                                     close = btc_data['close'])])

# Plot the three lines of the Bollinger Bands indicator
parameter = ['moving_average', 'bol_lower', 'bol_upper']
colors = ['blue', 'orange', 'orange']
for param,c in zip(parameter, colors):
    fig.add_trace(go.Scatter(
        x = btc_data.index,
        y = btc_data[param],
        showlegend = False,
        line_color = c,
        mode='lines',
        line={'dash': 'solid'},
        marker_line_width=2, 
        marker_size=10,
        opacity = 0.8))
    
# Add title and format axes
fig.update_layout(
    title='Bitcoin price in the last 2 hours with Bollinger Bands',
    yaxis_title='BTC/USD')

x = '2021-06-21 10:56:00'
y = df['close'].max()
fig.add_annotation(x=x, y=y,
                   text='\U000025bc',
                   showarrow=False,
                   yshift=10)

xx = '2021-06-21 09:50:00'
yy = df['close'].min()
fig.add_annotation(x=xx, y=yy,
                   text='\U000025b2',
                   showarrow=False,
                   yshift=10)

fig.show()

Thanks. I have many such arrows to add. Do I need to call add_annotation in a for loop? Or there’s a way to put all arrow positions in an array. Then, call add_annotation once for all the arrows in the array? — user1424739, Jun 26 '21 at 10:51
I think it can be handled by loop processing as shown in [this answer](https://stackoverflow.com/questions/51637838/how-to-annotate-subplots-in-plotly-inside-a-for-loop). — r-beginners, Jun 26 '21 at 13:17

How to add labels to candlestick plots?

1 Answers1