<jupyter_start><jupyter_text>**Note for tomorrow** make a data frame where each row is a COUNTRY and each column is a different year. the entries are average food price or something? maybe just the price of one foodthen make a time series model for the countries.worth a shot<jupyter_code>maize = fao[fao.Item == 'Maize']
def fao_pivot(data, food):
    '''
    take the FAO data and the name of a food
    
    return the pivot table where the rows are the countries,
    the columns are the years, and the values are the values
    '''
    foods = data[data.Item == food]
    return foods.pivot(index='Area', columns='Year', values='Value')
maize_years = fao_pivot(fao, 'Maize')
maize_years.sample(5)
fig, ax = plt.subplots(figsize=(16,12))
for i in range(0, maize_years.shape[0], 20):
    data = maize_years.iloc[i]
    ax.plot(data.index, data.values, label=data.name)
ax.legend() 
ax.set_title('Prices of Maize Over Time in Select Countries')
plt.show()
print(maize_years.iloc[1].name)<jupyter_output>Algeria
{'fraction_non_alphanumeric': 0.10968379446640317, 'fraction_numerical': 0.009881422924901186, 'mean_word_length': 4.446236559139785, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '121952', 'license': 'MIT', 'n_tokens_mistral': 353, 'n_tokens_neox': 336, 'n_words': 117, 'path': 'exploratory/00_initial_explore.ipynb', 'repo_name': 'Jprebys/food_prices', 'size': '1012'}