# Created: 20250104

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml312-2024; pyv: 3.12.7 | packaged by Anaconda, Inc. | (main, Oct  4 2024, 13:27:36) [GCC 11.2.0]'

# !pip install mplfinance

print(pyu.ps2("yfinance pandas matplotlib"))

yfinance==0.2.51
pandas==2.2.3
matplotlib==3.9.3

import yfinance as yf
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
import mplfinance as mpf

# Step 1: Download historical data
symbol = "^GSPC"  # S&P 500 as an example
start = "2023-12-01"
end = "2023-12-31"
data = yf.download(symbol, start=start, end=end)

# Step 2: Calculate Heikin Ashi Candles
def calculate_heikin_ashi(data):
    ha_data = data[['Open', 'High', 'Low', 'Close']].copy()

    ha_data['HA Close'] = (data['Open'] + data['High'] + data['Low'] + data['Close']) / 4
    ha_data['HA Open'] = (data['Open'].shift(1) + data['Close'].shift(1)) / 2
    ha_data['HA High'] = ha_data[['High', 'HA Open', 'HA Close']].max(axis=1)
    ha_data['HA Low'] = ha_data[['Low', 'HA Open', 'HA Close']].min(axis=1)

    return ha_data[['HA Open', 'HA High', 'HA Low', 'HA Close']]

# Apply Heikin Ashi calculation
ha_data = calculate_heikin_ashi(data)

# Step 3: Plot Heikin Ashi Candles
ha_candles = ha_data.rename(columns={'HA Open': 'open', 'HA High': 'high', 'HA Low': 'low', 'HA Close': 'close'})
mpf.plot(ha_candles, type='candle', style='charles', title=f'{symbol} Heikin Ashi Candles', ylabel='Price', ylabel_lower='Volume')

[*********************100%***********************]  1 of 1 completed



---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

Cell In[13], line 28
     26 # Step 3: Plot Heikin Ashi Candles
     27 ha_candles = ha_data.rename(columns={'HA Open': 'open', 'HA High': 'high', 'HA Low': 'low', 'HA Close': 'close'})
---> 28 mpf.plot(ha_candles, type='candle', style='charles', title=f'{symbol} Heikin Ashi Candles', ylabel='Price', ylabel_lower='Volume')


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/mplfinance/plotting.py:533, in plot(data, **kwargs)
    531     pnf_results = _construct_pnf_scatter(axA1,ptype,dates,xdates,opens,highs,lows,closes,volumes,config,style)
    532 else:
--> 533     collections =_construct_mpf_collections(ptype,dates,xdates,opens,highs,lows,closes,volumes,config,style)
    535 if ptype == 'pnf':
    536     volumes    = pnf_results['pnf_volumes']


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/mplfinance/_utils.py:93, in _construct_mpf_collections(ptype, dates, xdates, opens, highs, lows, closes, volumes, config, style)
     91 collections = None
     92 if ptype == 'candle' or ptype == 'candlestick':
---> 93     collections = _construct_candlestick_collections(xdates, opens, highs, lows, closes,
     94                                                      marketcolors=style['marketcolors'],config=config )
     96 elif ptype =='hollow_and_filled':
     97         collections = _construct_hollow_candlestick_collections(xdates, opens, highs, lows, closes,
     98                                                      marketcolors=style['marketcolors'],config=config )


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/mplfinance/_utils.py:665, in _construct_candlestick_collections(dates, opens, highs, lows, closes, marketcolors, config)
    637 def _construct_candlestick_collections(dates, opens, highs, lows, closes, marketcolors=None, config=None):
    638     """Represent the open, close as a bar line and high low range as a
    639     vertical line.
    640 
   (...)
    662         (lineCollection, barCollection)
    663     """
--> 665     _check_input(opens, highs, lows, closes)
    667     if marketcolors is None:
    668         marketcolors = _get_mpfstyle('classic')['marketcolors']


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/mplfinance/_utils.py:58, in _check_input(opens, closes, highs, lows)
     56 same_numnans = len(o) == len(h) == len(l) == len(c)
     57 if not same_numnans:
---> 58     raise ValueError('O,H,L,C must have the same amount of missing data!')
     60 same_missing = ((o == h).all() and
     61                 (o == l).all() and
     62                 (o == c).all()
     63                )
     64 if not same_missing:


ValueError: O,H,L,C must have the same amount of missing data!

def show_graph(symbol):

pass

show_graph("AMZN")

---------------------------------------------------------------------------

NameError                                 Traceback (most recent call last)

Cell In[5], line 1
----> 1 show_graph("AMZN")


NameError: name 'show_graph' is not defined