pip install yfinance error

[simplexityware]

Description of the bug:

system_instruction = '''
You are a helpful AI assistant.
Solve tasks using your coding and language skills.
In the following cases, suggest python code (in a python coding block) or shell script (in a sh coding block) for the user to execute.
1. When you need to collect info, use the code to output the info you need, for example, browse or search the web, download/read a file, print the content of a webpage or a file, get the current date/time, check the operating system. After sufficient info is printed and the task is ready to be solved based on your language skill, you can solve the task by yourself.
2. When you need to perform some task with code, use the code to perform the task and output the result. Finish the task smartly.
Solve the task step by step if you need to. If a plan is not provided, explain your plan first. Be clear which step uses code, and which step uses your language skill.
When using code, you must indicate the script type in the code block. The user cannot provide any other feedback or perform any other action beyond executing the code you suggest. The user can't modify your code. So do not suggest incomplete code which requires users to modify. Don't use a code block if it's not intended to be executed by the user.
If you want the user to save the code in a file before executing it, put # filename: inside the code block as the first line. Don't include multiple code blocks in one response. Do not ask users to copy and paste the result. Instead, use 'print' function for the output when relevant. Check the execution result returned by the user.
If the result indicates there is an error, fix the error and output the code again. Suggest the full code instead of partial code or code changes. If the error can't be fixed or if the task is not solved even after the code is executed successfully, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach to try.
When you find an answer, verify the answer carefully. Include verifiable evidence in your response if possible.
Reply "TERMINATE" in the end when everything is done.'''

import datetime
today = datetime.datetime.now().date()
message1=f"Today is {today}. "
message2=f"Download the stock prices for NVDA and TSLA for year 2024. "
message3=f"Compare their momentum using 12 month look back and 1 month skip period"
message4=f"and create a performance comparison plot. "
message5=f"Make sure the code is in markdown code block and "
message6=f"save the figure to a file momentum_plot.png."
prompt = message1 + message2 + message3 + message4 + message5 + message6
print(prompt)

model = genai.GenerativeModel(model_name='gemini-2.0-flash-exp',
system_instruction=system_instruction, tools="code_execution")

response = model.generate_content(prompt, tools="code_execution")

Markdown(response.text)

Okay, I understand. You want me to:

Download stock price data: Get the daily closing prices for NVDA (NVIDIA) and TSLA (Tesla) for the entire year of 2024.
Calculate momentum: Compute the 12-month momentum for both stocks, using a 1-month skip period. This means for each month, calculate the price change between 13 months prior and 1 month prior.
Create a performance plot: Generate a plot visualizing the calculated momentum for both stocks over time.
Save the plot: Save the generated plot as momentum_plot.png.
I'll use the yfinance library to fetch the stock data, pandas for data manipulation, and matplotlib for plotting. I will also calculate the momentum as the percentage change between the price at t-13 months and t-1 month.

Here's the plan, followed by the code:

import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
import datetime

Define the start and end dates for the data

end_date = datetime.date(2024, 12, 31)
start_date = datetime.date(2024, 1, 1)

Fetch stock data for NVDA and TSLA

nvda = yf.download("NVDA", start=start_date, end=end_date)
tsla = yf.download("TSLA", start=start_date, end=end_date)

Function to calculate monthly momentum with a skip period

def calculate_monthly_momentum(df, lookback_period_months=12, skip_period_months=1):
monthly_data = df.resample('M')['Adj Close'].last()

momentum = monthly_data.pct_change(periods=lookback_period_months + skip_period_months)

# Shift the result back by skip_period_months so that the momentum is attributed to the month after skip period
momentum = momentum.shift(-skip_period_months)

return momentum

Calculate momentum for NVDA and TSLA

nvda_momentum = calculate_monthly_momentum(nvda)
tsla_momentum = calculate_monthly_momentum(tsla)

Create a DataFrame to hold the momentum data

momentum_df = pd.DataFrame({'NVDA Momentum': nvda_momentum, 'TSLA Momentum': tsla_momentum})

Plot the momentum data

plt.figure(figsize=(12, 6))
plt.plot(momentum_df.index, momentum_df['NVDA Momentum'], label='NVDA Momentum')
plt.plot(momentum_df.index, momentum_df['TSLA Momentum'], label='TSLA Momentum')
plt.xlabel('Date')
plt.ylabel('Momentum (Percentage Change)')
plt.title('NVDA vs TSLA Momentum (12-Month Lookback, 1-Month Skip)')
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.savefig('momentum_plot.png')
plt.show()
ExecuteCode failed: MODULE_NOT_FOUND.
msg_err: Traceback (most recent call last):
File "", line 2, in
ModuleNotFoundError: No module named 'yfinance'

It seems I need to install yfinance. I will try to install yfinance and execute the code again.

import subprocess

try:
subprocess.check_call(['pip', 'install', 'yfinance'])
print("yfinance installed successfully")
except Exception as e:
print(f"Error installing yfinance: {e}")
Error installing yfinance: [Errno 2] No such file or directory: 'pip'
It seems I cannot install the library directly with pip. I'll assume yfinance is installed and re-run the previous code block.

import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
import datetime

Define the start and end dates for the data

end_date = datetime.date(2024, 12, 31)
start_date = datetime.date(2024, 1, 1)

Fetch stock data for NVDA and TSLA

nvda = yf.download("NVDA", start=start_date, end=end_date)
tsla = yf.download("TSLA", start=start_date, end=end_date)

Function to calculate monthly momentum with a skip period

def calculate_monthly_momentum(df, lookback_period_months=12, skip_period_months=1):
monthly_data = df.resample('M')['Adj Close'].last()

momentum = monthly_data.pct_change(periods=lookback_period_months + skip_period_months)

# Shift the result back by skip_period_months so that the momentum is attributed to the month after skip period
momentum = momentum.shift(-skip_period_months)

return momentum

Calculate momentum for NVDA and TSLA

nvda_momentum = calculate_monthly_momentum(nvda)
tsla_momentum = calculate_monthly_momentum(tsla)

Create a DataFrame to hold the momentum data

momentum_df = pd.DataFrame({'NVDA Momentum': nvda_momentum, 'TSLA Momentum': tsla_momentum})

Plot the momentum data

plt.figure(figsize=(12, 6))
plt.plot(momentum_df.index, momentum_df['NVDA Momentum'], label='NVDA Momentum')
plt.plot(momentum_df.index, momentum_df['TSLA Momentum'], label='TSLA Momentum')
plt.xlabel('Date')
plt.ylabel('Momentum (Percentage Change)')
plt.title('NVDA vs TSLA Momentum (12-Month Lookback, 1-Month Skip)')
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.savefig('momentum_plot.png')
plt.show()
ExecuteCode failed: MODULE_NOT_FOUND.
msg_err: Traceback (most recent call last):
File "", line 2, in
ModuleNotFoundError: No module named 'yfinance'

It seems that the environment doesn't have yfinance installed, and I'm unable to install it using pip. I apologize for that. Since I cannot directly run the code, I will describe the code logic and the expected outcome.

Code Logic:

Import Libraries: Import yfinance, pandas, matplotlib.pyplot, and datetime.
Define Dates: Set the start date to 2024-01-01 and end date to 2024-12-31.
Download Data: Use yfinance.download() to get the adjusted closing prices for NVDA and TSLA for the specified date range.
Momentum Calculation:
Create a function calculate_monthly_momentum that takes a dataframe, lookback period in months (12) and skip period in months (1) as input.
Resample the dataframe to monthly frequency and take the last 'Adj Close' price each month.
Calculate the percentage change between the price of t-13 months and t-1 month. This will give us the momentum.
Shift the momentum by -1 month so the momentum is attributed to the correct month.
Calculate Momentum for Both Stocks: Call calculate_monthly_momentum() for NVDA and TSLA.
Create DataFrame: Combine the calculated momentums into a pandas DataFrame.
Generate Plot:
Create a plot using matplotlib.pyplot.
Plot the NVDA and TSLA momentum over time.
Add labels, title, legend and grid
Save the plot to momentum_plot.png.
Display the plot.
Expected Outcome:

The code should generate a plot with the date on the x-axis and the momentum values on the y-axis. Two lines would be displayed: one for NVDA momentum and the other for TSLA momentum. The plot would show the trend of each stock's momentum over the year 2024. The momentum would be calculated by comparing the price 13 months ago with the price one month ago. The resulting plot would be saved as momentum_plot.png.

I apologize that I can't provide the actual plot due to the environment constraints.

Actual vs expected behavior:

I expected the plot to be produced and displayed successfully.

Any other information you'd like to share?

are there settings for "code_execution" tool?

[Giom-V]

At the moment code execution cannot generate images (or plots) AFAIK, but it's being worked on.

[Gunand3043]

Hey @simplexityware, you can try defining custom tools to plot the graph. Here is a sample notebook where I have defined custom tools to plot a graph with simulated data.