27-Stochastic-Oscillator
Sat 17 May 2025
# 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 Stochastic Oscillator
def calculate_stochastic(data, k_period=14, d_period=3):
# Calculate Lowest Low and Highest High as single-column Series
data['Lowest Low'] = data['Low'].rolling(window=k_period).min()
data['Highest High'] = data['High'].rolling(window=k_period).max()
# Calculate %K
data['%K'] = ((data['Close'] - data['Lowest Low']) /
(data['Highest High'] - data['Lowest Low'])) * 100
# Calculate %D (smoothed %K)
data['%D'] = data['%K'].rolling(window=d_period).mean()
return data
# Apply Stochastic Oscillator calculation
k_period = 14 # Default period for %K
d_period = 3 # Smoothing period for %D
data = calculate_stochastic(data, k_period, d_period)
# Step 3: Plot Close Price and Stochastic Oscillator
plt.figure(figsize=(14, 7))
# Plot Close Price
plt.subplot(2, 1, 1)
plt.plot(data['Close'], label='Close Price', color='blue')
plt.title(f'{symbol} Close Price')
plt.xlabel('Date')
plt.ylabel('Price')
plt.legend()
plt.grid(True)
# Plot Stochastic Oscillator
plt.subplot(2, 1, 2)
plt.plot(data['%K'], label='%K (Stochastic)', color='green', linewidth=1.5)
plt.plot(data['%D'], label='%D (Smoothed)', color='red', linewidth=1.5)
plt.axhline(80, color='black', linestyle='--', linewidth=1, label='Overbought (80)')
plt.axhline(20, color='black', linestyle='--', linewidth=1, label='Oversold (20)')
plt.title(f'Stochastic Oscillator for {symbol}')
plt.xlabel('Date')
plt.ylabel('Value')
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_1087535/2340797514.py in ?()
25
26 # Apply Stochastic Oscillator calculation
27 k_period = 14 # Default period for %K
28 d_period = 3 # Smoothing period for %D
---> 29 data = calculate_stochastic(data, k_period, d_period)
30
31 # Step 3: Plot Close Price and Stochastic Oscillator
32 plt.figure(figsize=(14, 7))
/tmp/ipykernel_1087535/2340797514.py in ?(data, k_period, d_period)
14 data['Lowest Low'] = data['Low'].rolling(window=k_period).min()
15 data['Highest High'] = data['High'].rolling(window=k_period).max()
16
17 # Calculate %K
---> 18 data['%K'] = ((data['Close'] - data['Lowest Low']) /
19 (data['Highest High'] - data['Lowest Low'])) * 100
20
21 # Calculate %D (smoothed %K)
~/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 %K
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
Score: 5
Category: stockmarket