# 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
from scipy.signal import argrelextrema

# 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: Calculate ZigZag Indicator
def calculate_zigzag(data, threshold=5):
    # Identify local maxima and minima
    data['Local Max'] = data['Close'][argrelextrema(data['Close'].values, comparator=np.greater, order=5)[0]]
    data['Local Min'] = data['Close'][argrelextrema(data['Close'].values, comparator=np.less, order=5)[0]]

    # Combine maxima and minima
    turning_points = pd.concat([data['Local Max'].dropna(), data['Local Min'].dropna()])
    turning_points = turning_points.sort_index()

    # Filter significant changes
    zigzag = []
    last_value = None
    for index, value in turning_points.items():
        if last_value is None or abs((value - last_value) / last_value * 100) >= threshold:
            zigzag.append((index, value))
            last_value = value

    zigzag_df = pd.DataFrame(zigzag, columns=['Date', 'Value']).set_index('Date')
    return zigzag_df

# Apply ZigZag calculation
threshold = 5  # Define the percentage change threshold
zigzag = calculate_zigzag(data, threshold)

# Step 3: Plot Close Price and ZigZag Indicator
plt.figure(figsize=(14, 7))

# Plot Close Price
plt.plot(data['Close'], label='Close Price', color='blue', linewidth=1)
plt.scatter(zigzag.index, zigzag['Value'], color='red', label='ZigZag Turning Points', zorder=3)
plt.plot(zigzag['Value'], color='green', linestyle='--', linewidth=1, label='ZigZag Line')

plt.title(f'{symbol} ZigZag Indicator (Threshold: {threshold}%)')
plt.xlabel('Date')
plt.ylabel('Price')
plt.legend(loc='best')
plt.grid(True)

plt.tight_layout()
plt.show()

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



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

KeyError                                  Traceback (most recent call last)

Cell In[5], line 35
     33 # Apply ZigZag calculation
     34 threshold = 5  # Define the percentage change threshold
---> 35 zigzag = calculate_zigzag(data, threshold)
     37 # Step 3: Plot Close Price and ZigZag Indicator
     38 plt.figure(figsize=(14, 7))


Cell In[5], line 15, in calculate_zigzag(data, threshold)
     13 def calculate_zigzag(data, threshold=5):
     14     # Identify local maxima and minima
---> 15     data['Local Max'] = data['Close'][argrelextrema(data['Close'].values, comparator=np.greater, order=5)[0]]
     16     data['Local Min'] = data['Close'][argrelextrema(data['Close'].values, comparator=np.less, order=5)[0]]
     18     # Combine maxima and minima


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/pandas/core/frame.py:4108, in DataFrame.__getitem__(self, key)
   4106     if is_iterator(key):
   4107         key = list(key)
-> 4108     indexer = self.columns._get_indexer_strict(key, "columns")[1]
   4110 # take() does not accept boolean indexers
   4111 if getattr(indexer, "dtype", None) == bool:


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/pandas/core/indexes/base.py:6200, in Index._get_indexer_strict(self, key, axis_name)
   6197 else:
   6198     keyarr, indexer, new_indexer = self._reindex_non_unique(keyarr)
-> 6200 self._raise_if_missing(keyarr, indexer, axis_name)
   6202 keyarr = self.take(indexer)
   6203 if isinstance(key, Index):
   6204     # GH 42790 - Preserve name from an Index


File ~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/pandas/core/indexes/base.py:6249, in Index._raise_if_missing(self, key, indexer, axis_name)
   6247 if nmissing:
   6248     if nmissing == len(indexer):
-> 6249         raise KeyError(f"None of [{key}] are in the [{axis_name}]")
   6251     not_found = list(ensure_index(key)[missing_mask.nonzero()[0]].unique())
   6252     raise KeyError(f"{not_found} not in index")


KeyError: "None of [Index([  11,   32,   42,   58,   73,   81,  108,  119,  139,  169,  177,  196,\n        221,  236,  243,  257,  267,  281,  303,  324,  333,  339,  364,  383,\n        393,  408,  421,  436,  467,  475,  490,  505,  512,  526,  545,  564,\n        578,  589,  598,  609,  624,  632,  660,  678,  694,  712,  722,  734,\n        743,  777,  786,  798,  809,  818,  828,  836,  850,  869,  880,  899,\n        923,  931,  950, 1004],\n      dtype='int64', name='Ticker')] are in the [columns]"

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