# 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]'

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 numpy as np

# Step 1: Download historical data
symbol = "^GSPC"  # S&P 500 as an example
start = "2020-01-01"
end = "2023-12-31"
data = yf.download(symbol, start=start, end=end)

# Step 2: Identify a pivot point (e.g., the most recent low)
pivot_date = data['Close'].idxmin()  # Recent low
pivot_price = data['Close'].min()
pivot_index = data.index.get_loc(pivot_date)

# Step 3: Define Gann angles
angles = {
    '1x1': 45,
    '2x1': 63.5,
    '1x2': 26.5,
    '3x1': 71.5,
    '1x3': 18.5,
}

# Step 4: Plot Gann Fans
plt.figure(figsize=(14, 7))
plt.plot(data['Close'], label='Close Price', color='blue', linewidth=1)
plt.scatter(pivot_date, pivot_price, color='red', label='Pivot Point', zorder=3)

# Draw Gann angles
for label, angle in angles.items():
    # Create x values from the pivot point
    x = np.arange(0, len(data) - pivot_index)
    y = pivot_price + x * np.tan(np.radians(angle))

    # Adjust y values to align with the index
    gann_x = data.index[pivot_index : pivot_index + len(x)]
    gann_y = y[:len(gann_x)]  # Ensure lengths match

    plt.plot(gann_x, gann_y, label=f'Gann Fan {label}', linestyle='--')

# Customize plot
plt.title(f'{symbol} Gann Fans')
plt.xlabel('Date')
plt.ylabel('Price')
plt.legend(loc='best')
plt.grid(True)
plt.tight_layout()
plt.show()

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



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

InvalidIndexError                         Traceback (most recent call last)

Cell In[7], line 15
     13 pivot_date = data['Close'].idxmin()  # Recent low
     14 pivot_price = data['Close'].min()
---> 15 pivot_index = data.index.get_loc(pivot_date)
     17 # Step 3: Define Gann angles
     18 angles = {
     19     '1x1': 45,
     20     '2x1': 63.5,
   (...)
     23     '1x3': 18.5,
     24 }


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/pandas/core/indexes/datetimes.py:590, in DatetimeIndex.get_loc(self, key)
    582 def get_loc(self, key):
    583     """
    584     Get integer location for requested label
    585 
   (...)
    588     loc : int
    589     """
--> 590     self._check_indexing_error(key)
    592     orig_key = key
    593     if is_valid_na_for_dtype(key, self.dtype):


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/pandas/core/indexes/base.py:6059, in Index._check_indexing_error(self, key)
   6055 def _check_indexing_error(self, key):
   6056     if not is_scalar(key):
   6057         # if key is not a scalar, directly raise an error (the code below
   6058         # would convert to numpy arrays and raise later any way) - GH29926
-> 6059         raise InvalidIndexError(key)


InvalidIndexError: Ticker
^GSPC   2020-03-23
dtype: datetime64[ns]

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