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Refactor faculty scraping functionality and add new scrapers for various departments. Update main.py to comment out sum calculations and chart plotting. Introduce profile_to_vector_database notebook for faculty data processing. Remove simple.ipynb as it is no longer needed.

df2f2e8 over 1 year ago

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#%%
# Import libraries
import pandas as pd
import matplotlib.pyplot as plt
#%%
# Defining data for the dataframe
data = {
    'Basket': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P'],
    'Apples': [10, 20, 30, 56, 40, 40, 67, 47, 40, 4, 49, 52, 5, 56, 35, 45],
    'Bananas': [15, 6, 3, 45, 67, 44, 45, 11, 14, 18, 13, 12, 1, 34, 12, 12]
}

# Creating the dataframe
df = pd.DataFrame(data)

df
#%%
# # Calculate the sums
# sum_apples = df['Apples'].sum()
# sum_bananas = df['Bananas'].sum()

# # Create a bar chart
# plt.bar(['Apples', 'Bananas'], [sum_apples, sum_bananas], color=['red', 'blue'])

# # Set a title
# plt.title('Comparison of total Apples and Bananas')

# # Show the plot
# plt.show()

# See DataSpell help at https://www.jetbrains.com/help/dataspell/

# %%

	#%%
	# Import libraries
	import pandas as pd
	import matplotlib.pyplot as plt
	#%%
	# Defining data for the dataframe
	data = {
	'Basket': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P'],
	'Apples': [10, 20, 30, 56, 40, 40, 67, 47, 40, 4, 49, 52, 5, 56, 35, 45],
	'Bananas': [15, 6, 3, 45, 67, 44, 45, 11, 14, 18, 13, 12, 1, 34, 12, 12]
	}

	# Creating the dataframe
	df = pd.DataFrame(data)

	df
	#%%
	# # Calculate the sums
	# sum_apples = df['Apples'].sum()
	# sum_bananas = df['Bananas'].sum()

	# # Create a bar chart
	# plt.bar(['Apples', 'Bananas'], [sum_apples, sum_bananas], color=['red', 'blue'])

	# # Set a title
	# plt.title('Comparison of total Apples and Bananas')

	# # Show the plot
	# plt.show()

	# See DataSpell help at https://www.jetbrains.com/help/dataspell/

	# %%