{
  "q": "TSLA stock price for the last 7 days",
  "percentile": "3",
  "numofpages": "3"
}

import matplotlib.pyplot as plt
import pandas as pd

# Given TSLA stock prices for the last 7 days
data = {
    'Date': ['2023-11-06', '2023-11-03', '2023-11-02', '2023-11-01', '2023-10-31', '2023-10-30', '2023-10-27'],
    'Close': [219.27, 219.96, 218.51, 205.66, 200.84, 197.36, 207.30]
}

# Create a DataFrame
df = pd.DataFrame(data)

# Convert the Date column to datetime
df['Date'] = pd.to_datetime(df['Date'])

# Sort the DataFrame by the Date
df.sort_values('Date', inplace=True)

# Plotting the data
plt.figure(figsize=(10,5))
plt.plot(df['Date'], df['Close'], marker='o')
plt.title('TSLA Stock Price - Last 7 Days')
plt.xlabel('Date')
plt.ylabel('Close Price (USD)')
plt.grid(True)
plt.xticks(rotation=45)
plt.tight_layout()  # Adjust the plot to ensure everything fits without overlap
plt.show()

TSLA Stock Price Graph

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