usa egg prices

eggs.py

import requests
import pandas as pd

def download_data(url, filename):
    """Downloads data from a given URL and saves it as a CSV file.

    Args:
        url: The URL of the data to download.
        filename: The name of the CSV file to save the data to.
    """
    try:
        response = requests.get(url)
        response.raise_for_status()  # Raise an exception for bad status codes

        with open(filename, 'wb') as f:
            f.write(response.content)

        print(f"Data downloaded successfully and saved to {filename}")

    except requests.exceptions.RequestException as e:
        print(f"Error downloading data: {e}")
    except Exception as e:
        print(f"An unexpected error occurred: {e}")

# Example usage:
url = "https://fred.stlouisfed.org/graph/fredgraph.csv?bgcolor=%23ebf3fb&chart_type=line&drp=0&fo=open%20sans&graph_bgcolor=%23ffffff&height=450&mode=fred&recession_bars=on&txtcolor=%23444444&ts=12&tts=12&width=1140&nt=0&thu=0&trc=0&show_legend=yes&show_axis_titles=yes&show_tooltip=yes&id=APU0000708111&scale=left&cosd=1980-01-01&coed=2024-12-01&line_color=%230073e6&link_values=false&line_style=solid&mark_type=none&mw=3&lw=3&ost=-99999&oet=99999&mma=0&fml=a&fq=Monthly&fam=avg&fgst=lin&fgsnd=2020-02-01&line_index=1&transformation=lin&vintage_date=2025-02-12&revision_date=2025-02-12&nd=1980-01-01"
filename = "eggs.csv"
download_data(url, filename)



import matplotlib.pyplot as plt
import pandas as pd

# Assuming eggs.csv is in the current working directory of the notebook.
# If it's in a different location, adjust the filepath accordingly.

try:
  eggs = pd.read_csv('eggs.csv')
  # Convert 'observation_date' to datetime objects
  eggs['observation_date'] = pd.to_datetime(eggs['observation_date'])
  # eggs['12M_MA'] = eggs['APU0000708111'].rolling(window=12).mean()
  # plt.plot(eggs['observation_date'], eggs['12M_MA'], label="12-Month Moving Avg", linestyle="dashed", color="red")
  annotate_date = pd.to_datetime("2022-06-01")

  # Create the line plot
  plt.figure(figsize=(10, 6))  # Adjust figure size as needed
  plt.plot(eggs['observation_date'], eggs['APU0000708111'])
  plt.xlabel('Year')
  plt.ylabel('Price in Dollars')
  plt.title('Egg Price Over Time')

  # Add Annotation
  plt.annotate(
    'Bird Flu Outbreak',
    xy=(annotate_date, 2.50),   # Arrow still points to the actual event
    xytext=(pd.to_datetime("2010-01-01"), 4.00),  # Move text to x=2010, y=4
    arrowprops=dict(facecolor='black', shrink=0.05),
    fontsize=12,
    bbox=dict(boxstyle="round,pad=0.3", edgecolor="black", facecolor="white")
  )

  plt.grid(True)  # Add gridlines for better readability
  plt.xticks(rotation=45)  # Rotate x-axis labels for better visibility if needed
  plt.tight_layout()  # Adjust layout to prevent labels from overlapping
    # Save the plot as a PNG file


  plt.savefig('egg_price_plot.png')
  plt.show()

except FileNotFoundError:
  print("Error: eggs.csv not found in the current directory.")
except pd.errors.ParserError:
  print("Error: Could not parse eggs.csv. Please check file format.")
except KeyError as e:
    print(f"Error: Column '{e}' not found in the DataFrame. Check your column name.")
except Exception as e:
  print(f"An unexpected error occurred: {e}")

mayeggs.py

try:
  eggs = pd.read_csv('eggs.csv')
  eggs['observation_date'] = pd.to_datetime(eggs['observation_date'])
  annotate_date = pd.to_datetime("2022-06-01")

  plt.style.use('seaborn-v0_8-whitegrid')
  plt.figure(figsize=(10, 6))

  # Plot main monthly price line with label
  plt.plot(eggs['observation_date'], eggs['APU0000708111'], label="Monthly Price", color='steelblue')

  # 12-month moving average
  eggs['12M_MA'] = eggs['APU0000708111'].rolling(window=12).mean()
  plt.plot(eggs['observation_date'], eggs['12M_MA'], label="12-Month Moving Avg", linestyle="--", color="red")

  # Extended bird flu period
  plt.axvspan(pd.to_datetime("2022-01-01"), pd.to_datetime("2025-05-01"),
              color='orange', alpha=0.2, label="Bird Flu Outbreak")
# 2014–2015 H5N2 outbreak
  plt.axvspan(pd.to_datetime("2014-11-01"), pd.to_datetime("2015-06-01"),
            color='orange', alpha=0.15)
  
  # Annotation , label="2015 Bird Flu"
   #plt.annotate('Bird Flu Outbreak',
    #            xy=(annotate_date, 2.50),
    #           xytext=(pd.to_datetime("2010-01-01"), 4.00),
     #           arrowprops=dict(arrowstyle='->', color='black', lw=0.5),
     #           fontsize=12,
      #          bbox=dict(boxstyle="round,pad=0.3", edgecolor="black", facecolor="white"))

  # Labels and title
  plt.xlabel('Year')
  plt.ylabel('Price (USD per Dozen)')
  plt.title('US Egg Prices Over Time', fontsize=20, weight='bold')

  # Source and legend
  plt.figtext(0.99, 0.01, 'data: FRED, APU0000708111 by @iamreddave', 
              ha='right', fontsize=9, style='italic')

  plt.ylim(bottom=0)
  plt.legend(loc='upper left')
  plt.grid(True)
  plt.xticks(rotation=45)
  plt.tight_layout()
  plt.savefig('egg_price_plotMay.png')
  plt.show()

except FileNotFoundError:
  print("Error: eggs.csv not found in the current directory.")
except pd.errors.ParserError:
  print("Error: Could not parse eggs.csv. Please check file format.")
except KeyError as e:
  print(f"Error: Column '{e}' not found in the DataFrame. Check your column name.")
except Exception as e:
  print(f"An unexpected error occurred: {e}")