# 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

# 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 Pivot Range
def calculate_pivot_range(data):
    data['Pivot Point'] = (data['High'] + data['Low'] + data['Close']) / 3
    data['R1'] = 2 * data['Pivot Point'] - data['Low']
    data['R2'] = data['Pivot Point'] + (data['High'] - data['Low'])
    data['S1'] = 2 * data['Pivot Point'] - data['High']
    data['S2'] = data['Pivot Point'] - (data['High'] - data['Low'])
    return data

# Apply Pivot Range calculation
data = calculate_pivot_range(data)

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

# Plot Close Price
plt.plot(data['Close'], label='Close Price', color='blue', linewidth=1)
plt.plot(data['Pivot Point'], label='Pivot Point (P)', color='black', linestyle='--')
plt.plot(data['R1'], label='Resistance 1 (R1)', color='green', linestyle='--')
plt.plot(data['R2'], label='Resistance 2 (R2)', color='lime', linestyle='--')
plt.plot(data['S1'], label='Support 1 (S1)', color='red', linestyle='--')
plt.plot(data['S2'], label='Support 2 (S2)', color='orange', linestyle='--')

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

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



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

ValueError                                Traceback (most recent call last)

/tmp/ipykernel_1326968/2158972586.py in ?()
     17     data['S2'] = data['Pivot Point'] - (data['High'] - data['Low'])
     18     return data
     19 
     20 # Apply Pivot Range calculation
---> 21 data = calculate_pivot_range(data)
     22 
     23 # Step 3: Plot Close Price and Pivot Range
     24 plt.figure(figsize=(14, 7))


/tmp/ipykernel_1326968/2158972586.py in ?(data)
     12 def calculate_pivot_range(data):
     13     data['Pivot Point'] = (data['High'] + data['Low'] + data['Close']) / 3
---> 14     data['R1'] = 2 * data['Pivot Point'] - data['Low']
     15     data['R2'] = data['Pivot Point'] + (data['High'] - data['Low'])
     16     data['S1'] = 2 * data['Pivot Point'] - data['High']
     17     data['S2'] = data['Pivot Point'] - (data['High'] - data['Low'])


~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/pandas/core/frame.py in ?(self, key, value)
   4297             self._setitem_frame(key, value)
   4298         elif isinstance(key, (Series, np.ndarray, list, Index)):
   4299             self._setitem_array(key, value)
   4300         elif isinstance(value, DataFrame):
-> 4301             self._set_item_frame_value(key, value)
   4302         elif (
   4303             is_list_like(value)
   4304             and not self.columns.is_unique


~/miniconda3/envs/ml312-2024/lib/python3.12/site-packages/pandas/core/frame.py in ?(self, key, value)
   4455 
   4456             return self.isetitem(locs, value)
   4457 
   4458         if len(value.columns) > 1:
-> 4459             raise ValueError(
   4460                 "Cannot set a DataFrame with multiple columns to the single "
   4461                 f"column {key}"
   4462             )


ValueError: Cannot set a DataFrame with multiple columns to the single column R1

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