316 lines
26 KiB
Python
316 lines
26 KiB
Python
from datetime import datetime
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from collections import defaultdict
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def add_value_growth(data):
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"""
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Adds a new key 'valueGrowth' to each entry in the data list.
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Parameters:
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- data (list): A list of dictionaries containing date and value lists.
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Returns:
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- list: A new list with the 'valueGrowth' key added to each dictionary.
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"""
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# Initialize a new list for the output data
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updated_data = []
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# Loop through the data from the latest to the oldest
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for i in range(len(data)):
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try:
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current_entry = data[i].copy() # Create a copy of the current entry
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current_values = current_entry['value']
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# Initialize the growth percentages list
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if i < len(data) - 1: # Only compute growth if there is a next entry
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next_values = data[i + 1]['value']
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growth_percentages = []
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for j in range(len(current_values)):
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# Convert values to integers if they are strings
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next_value = int(next_values[j]) if isinstance(next_values[j], (int, str)) else 0
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current_value = int(current_values[j]) if isinstance(current_values[j], (int, str)) else 0
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# Calculate growth percentage if next_value is not zero
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if next_value != 0:
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growth = round(((current_value - next_value) / next_value) * 100,2)
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else:
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growth = None # Cannot calculate growth if next value is zero
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growth_percentages.append(growth)
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current_entry['valueGrowth'] = growth_percentages # Add the growth percentages
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else:
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current_entry['valueGrowth'] = [None] * len(current_values) # No growth for the last entry
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updated_data.append(current_entry) # Append the updated entry to the output list
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except:
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pass
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return updated_data
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def sort_by_latest_date_and_highest_value(data):
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# Define a key function to convert the date string to a datetime object
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# and use the negative of the integer value for descending order
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def sort_key(item):
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date = datetime.strptime(item['date'], '%Y-%m-%d')
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value = -int(item['value']) # Negative for descending order
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return (date, value)
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# Sort the list
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sorted_data = sorted(data, key=sort_key, reverse=True)
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return sorted_data
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def aggregate_other_values(data):
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aggregated = defaultdict(int)
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result = []
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# First pass: aggregate 'Other' values and keep non-'Other' items
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for item in data:
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date = item['date']
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value = int(item['value'])
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if item['name'] == 'Other':
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aggregated[date] += value
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else:
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result.append(item)
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# Second pass: add aggregated 'Other' values
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for date, value in aggregated.items():
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result.append({'name': 'Other', 'value': int(value), 'date': date})
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return sorted(result, key=lambda x: (x['date'], x['name']))
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# Define quarter-end dates for a given year
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def closest_quarter_end(date_str):
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date = datetime.strptime(date_str, "%Y-%m-%d")
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year = date.year
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# Define quarter end dates for the current year
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q1 = datetime(year, 3, 31)
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q2 = datetime(year, 6, 30)
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q3 = datetime(year, 9, 30)
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q4 = datetime(year, 12, 31)
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# If the date is in January, return the last day of Q4 of the previous year
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if date.month == 1:
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closest = datetime(year - 1, 12, 31) # Last quarter of the previous year
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else:
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# Adjust to next year's Q4 if the date is in the last quarter of the current year
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if date >= q4:
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closest = q4.replace(year=year + 1) # Next year's last quarter
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else:
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# Find the closest quarter date
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closest = min([q1, q2, q3, q4], key=lambda d: abs(d - date))
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# Return the closest quarter date in 'YYYY-MM-DD' format
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return closest.strftime("%Y-%m-%d")
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def compute_q4_results(dataset):
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# Group data by year and name
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yearly_data = defaultdict(lambda: defaultdict(dict))
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for item in dataset:
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date = datetime.strptime(item['date'], '%Y-%m-%d')
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year = date.year
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quarter = (date.month - 1) // 3 + 1
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yearly_data[year][item['name']][quarter] = item['value']
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# Calculate Q4 results and update dataset
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for year in sorted(yearly_data.keys(), reverse=True):
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for name, quarters in yearly_data[year].items():
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if 4 in quarters: # This is the year-end total
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total = quarters[4]
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q1 = quarters.get(1, 0)
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q2 = quarters.get(2, 0)
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q3 = quarters.get(3, 0)
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q4_value = total - (q1 + q2 + q3)
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# Update the original dataset
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for item in dataset:
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if item['name'] == name and item['date'] == f'{year}-12-31':
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item['value'] = q4_value
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break
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return dataset
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revenue_sources = [{'name': 'Product', 'value': '17080000000', 'date': '2024-03-31'}, {'name': 'ServiceOther', 'value': '44778000000', 'date': '2024-03-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '24832000000', 'date': '2024-03-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '13911000000', 'date': '2024-03-31'}, {'name': 'Windows', 'value': '5929000000', 'date': '2024-03-31'}, {'name': 'Gaming', 'value': '5451000000', 'date': '2024-03-31'}, {'name': 'LinkedInCorporation', 'value': '4013000000', 'date': '2024-03-31'}, {'name': 'SearchAndNewsAdvertising', 'value': '3134000000', 'date': '2024-03-31'}, {'name': 'EnterpriseAndPartnerServices', 'value': '1861000000', 'date': '2024-03-31'}, {'name': 'DynamicsProductsAndCloudServices', 'value': '1646000000', 'date': '2024-03-31'}, {'name': 'Devices', 'value': '1067000000', 'date': '2024-03-31'}, {'name': 'OtherProductsAndServices', 'value': '14000000', 'date': '2024-03-31'}, {'name': 'Product', 'value': '18941000000', 'date': '2023-12-31'}, {'name': 'ServiceOther', 'value': '43079000000', 'date': '2023-12-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '23953000000', 'date': '2023-12-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '13477000000', 'date': '2023-12-31'}, {'name': 'Gaming', 'value': '7111000000', 'date': '2023-12-31'}, {'name': 'Windows', 'value': '5262000000', 'date': '2023-12-31'}, {'name': 'LinkedInCorporation', 'value': '4195000000', 'date': '2023-12-31'}, {'name': 'SearchAndNewsAdvertising', 'value': '3220000000', 'date': '2023-12-31'}, {'name': 'EnterpriseAndPartnerServices', 'value': '1917000000', 'date': '2023-12-31'}, {'name': 'DynamicsProductsAndCloudServices', 'value': '1576000000', 'date': '2023-12-31'}, {'name': 'Devices', 'value': '1298000000', 'date': '2023-12-31'}, {'name': 'OtherProductsAndServices', 'value': '11000000', 'date': '2023-12-31'}, {'name': 'Product', 'value': '15535000000', 'date': '2023-09-30'}, {'name': 'ServiceOther', 'value': '40982000000', 'date': '2023-09-30'}, {'name': 'ServerProductsAndCloudServices', 'value': '22308000000', 'date': '2023-09-30'}, {'name': 'OfficeProductsAndCloudServices', 'value': '13140000000', 'date': '2023-09-30'}, {'name': 'Windows', 'value': '5567000000', 'date': '2023-09-30'}, {'name': 'Gaming', 'value': '3919000000', 'date': '2023-09-30'}, {'name': 'LinkedInCorporation', 'value': '3913000000', 'date': '2023-09-30'}, {'name': 'SearchAndNewsAdvertising', 'value': '3053000000', 'date': '2023-09-30'}, {'name': 'EnterpriseAndPartnerServices', 'value': '1944000000', 'date': '2023-09-30'}, {'name': 'Dynamics', 'value': '1540000000', 'date': '2023-09-30'}, {'name': 'Devices', 'value': '1125000000', 'date': '2023-09-30'}, {'name': 'OtherProductsAndServices', 'value': '8000000', 'date': '2023-09-30'}, {'name': 'Product', 'value': '15588000000', 'date': '2023-03-31'}, {'name': 'ServiceOther', 'value': '37269000000', 'date': '2023-03-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '20025000000', 'date': '2023-03-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '12438000000', 'date': '2023-03-31'}, {'name': 'Windows', 'value': '5328000000', 'date': '2023-03-31'}, {'name': 'Gaming', 'value': '3607000000', 'date': '2023-03-31'}, {'name': 'LinkedInCorporation', 'value': '3697000000', 'date': '2023-03-31'}, {'name': 'SearchAndNewsAdvertising', 'value': '3045000000', 'date': '2023-03-31'}, {'name': 'EnterpriseServices', 'value': '2007000000', 'date': '2023-03-31'}, {'name': 'Devices', 'value': '1282000000', 'date': '2023-03-31'}, {'name': 'OtherProductsAndServices', 'value': '1428000000', 'date': '2023-03-31'}, {'name': 'Product', 'value': '16517000000', 'date': '2022-12-31'}, {'name': 'ServiceOther', 'value': '36230000000', 'date': '2022-12-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '19594000000', 'date': '2022-12-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '11837000000', 'date': '2022-12-31'}, {'name': 'Windows', 'value': '4808000000', 'date': '2022-12-31'}, {'name': 'Gaming', 'value': '4758000000', 'date': '2022-12-31'}, {'name': 'LinkedInCorporation', 'value': '3876000000', 'date': '2022-12-31'}, {'name': 'SearchAndNewsAdvertising', 'value': '3223000000', 'date': '2022-12-31'}, {'name': 'EnterpriseServices', 'value': '1862000000', 'date': '2022-12-31'}, {'name': 'Devices', 'value': '1430000000', 'date': '2022-12-31'}, {'name': 'OtherProductsAndServices', 'value': '1359000000', 'date': '2022-12-31'}, {'name': 'Product', 'value': '15741000000', 'date': '2022-09-30'}, {'name': 'ServiceOther', 'value': '34381000000', 'date': '2022-09-30'}, {'name': 'ServerProductsAndCloudServices', 'value': '18388000000', 'date': '2022-09-30'}, {'name': 'OfficeProductsAndCloudServices', 'value': '11548000000', 'date': '2022-09-30'}, {'name': 'Windows', 'value': '5313000000', 'date': '2022-09-30'}, {'name': 'LinkedInCorporation', 'value': '3663000000', 'date': '2022-09-30'}, {'name': 'Gaming', 'value': '3610000000', 'date': '2022-09-30'}, {'name': 'SearchAndNewsAdvertising', 'value': '2928000000', 'date': '2022-09-30'}, {'name': 'EnterpriseServices', 'value': '1876000000', 'date': '2022-09-30'}, {'name': 'Devices', 'value': '1448000000', 'date': '2022-09-30'}, {'name': 'OtherProductsAndServices', 'value': '1348000000', 'date': '2022-09-30'}, {'name': 'Product', 'value': '17366000000', 'date': '2022-03-31'}, {'name': 'ServiceOther', 'value': '31994000000', 'date': '2022-03-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '17038000000', 'date': '2022-03-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '11164000000', 'date': '2022-03-31'}, {'name': 'Windows', 'value': '6077000000', 'date': '2022-03-31'}, {'name': 'Gaming', 'value': '3740000000', 'date': '2022-03-31'}, {'name': 'LinkedInCorporation', 'value': '3437000000', 'date': '2022-03-31'}, {'name': 'SearchAndNewsAdvertising', 'value': '2945000000', 'date': '2022-03-31'}, {'name': 'EnterpriseServices', 'value': '1891000000', 'date': '2022-03-31'}, {'name': 'Devices', 'value': '1764000000', 'date': '2022-03-31'}, {'name': 'OtherProductsAndServices', 'value': '1304000000', 'date': '2022-03-31'}, {'name': 'Product', 'value': '20779000000', 'date': '2021-12-31'}, {'name': 'ServiceOther', 'value': '30949000000', 'date': '2021-12-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '16375000000', 'date': '2021-12-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '11251000000', 'date': '2021-12-31'}, {'name': 'Windows', 'value': '6600000000', 'date': '2021-12-31'}, {'name': 'Gaming', 'value': '5442000000', 'date': '2021-12-31'}, {'name': 'LinkedInCorporation', 'value': '3531000000', 'date': '2021-12-31'}, {'name': 'SearchAndNewsAdvertising', 'value': '3064000000', 'date': '2021-12-31'}, {'name': 'Devices', 'value': '2285000000', 'date': '2021-12-31'}, {'name': 'EnterpriseServices', 'value': '1823000000', 'date': '2021-12-31'}, {'name': 'OtherProductsAndServices', 'value': '1357000000', 'date': '2021-12-31'}, {'name': 'Product', 'value': '16631000000', 'date': '2021-09-30'}, {'name': 'ServiceOther', 'value': '28686000000', 'date': '2021-09-30'}, {'name': 'ServerProductsAndCloudServices', 'value': '15069000000', 'date': '2021-09-30'}, {'name': 'OfficeProductsAndCloudServices', 'value': '10808000000', 'date': '2021-09-30'}, {'name': 'Windows', 'value': '5676000000', 'date': '2021-09-30'}, {'name': 'Gaming', 'value': '3593000000', 'date': '2021-09-30'}, {'name': 'LinkedInCorporation', 'value': '3136000000', 'date': '2021-09-30'}, {'name': 'SearchAndNewsAdvertising', 'value': '2656000000', 'date': '2021-09-30'}, {'name': 'EnterpriseServices', 'value': '1791000000', 'date': '2021-09-30'}, {'name': 'Devices', 'value': '1361000000', 'date': '2021-09-30'}, {'name': 'OtherProductsAndServices', 'value': '1227000000', 'date': '2021-09-30'}, {'name': 'Product', 'value': '16873000000', 'date': '2021-03-31'}, {'name': 'ServiceOther', 'value': '24833000000', 'date': '2021-03-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '13204000000', 'date': '2021-03-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '10016000000', 'date': '2021-03-31'}, {'name': 'Windows', 'value': '5646000000', 'date': '2021-03-31'}, {'name': 'Gaming', 'value': '3533000000', 'date': '2021-03-31'}, {'name': 'LinkedInCorporation', 'value': '2562000000', 'date': '2021-03-31'}, {'name': 'SearchAdvertising', 'value': '2218000000', 'date': '2021-03-31'}, {'name': 'Devices', 'value': '1599000000', 'date': '2021-03-31'}, {'name': 'EnterpriseServices', 'value': '1803000000', 'date': '2021-03-31'}, {'name': 'OtherProductsAndServices', 'value': '1125000000', 'date': '2021-03-31'}, {'name': 'Product', 'value': '19460000000', 'date': '2020-12-31'}, {'name': 'ServiceOther', 'value': '23616000000', 'date': '2020-12-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '12729000000', 'date': '2020-12-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '9881000000', 'date': '2020-12-31'}, {'name': 'Windows', 'value': '5716000000', 'date': '2020-12-31'}, {'name': 'Gaming', 'value': '5031000000', 'date': '2020-12-31'}, {'name': 'LinkedInCorporation', 'value': '2577000000', 'date': '2020-12-31'}, {'name': 'SearchAdvertising', 'value': '2184000000', 'date': '2020-12-31'}, {'name': 'Devices', 'value': '2120000000', 'date': '2020-12-31'}, {'name': 'EnterpriseServices', 'value': '1695000000', 'date': '2020-12-31'}, {'name': 'OtherProductsAndServices', 'value': '1143000000', 'date': '2020-12-31'}, {'name': 'Product', 'value': '15803000000', 'date': '2020-09-30'}, {'name': 'ServiceOther', 'value': '21351000000', 'date': '2020-09-30'}, {'name': 'ServerProductsAndCloudServices', 'value': '11195000000', 'date': '2020-09-30'}, {'name': 'OfficeProductsAndCloudServices', 'value': '9278000000', 'date': '2020-09-30'}, {'name': 'Windows', 'value': '5305000000', 'date': '2020-09-30'}, {'name': 'Gaming', 'value': '3092000000', 'date': '2020-09-30'}, {'name': 'LinkedInCorporation', 'value': '2206000000', 'date': '2020-09-30'}, {'name': 'SearchAdvertising', 'value': '1789000000', 'date': '2020-09-30'}, {'name': 'EnterpriseServices', 'value': '1637000000', 'date': '2020-09-30'}, {'name': 'Devices', 'value': '1620000000', 'date': '2020-09-30'}, {'name': 'OtherProductsAndServices', 'value': '1032000000', 'date': '2020-09-30'}, {'name': 'Product', 'value': '15871000000', 'date': '2020-03-31'}, {'name': 'ServiceOther', 'value': '19150000000', 'date': '2020-03-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '10490000000', 'date': '2020-03-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '8920000000', 'date': '2020-03-31'}, {'name': 'Windows', 'value': '5220000000', 'date': '2020-03-31'}, {'name': 'Gaming', 'value': '2349000000', 'date': '2020-03-31'}, {'name': 'SearchAdvertising', 'value': '1986000000', 'date': '2020-03-31'}, {'name': 'LinkedInCorporation', 'value': '2050000000', 'date': '2020-03-31'}, {'name': 'EnterpriseServices', 'value': '1633000000', 'date': '2020-03-31'}, {'name': 'Devices', 'value': '1412000000', 'date': '2020-03-31'}, {'name': 'OtherProductsAndServices', 'value': '961000000', 'date': '2020-03-31'}, {'name': 'Product', 'value': '18255000000', 'date': '2019-12-31'}, {'name': 'ServiceOther', 'value': '18651000000', 'date': '2019-12-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '10119000000', 'date': '2019-12-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '8983000000', 'date': '2019-12-31'}, {'name': 'Windows', 'value': '5593000000', 'date': '2019-12-31'}, {'name': 'Gaming', 'value': '3327000000', 'date': '2019-12-31'}, {'name': 'SearchAdvertising', 'value': '2163000000', 'date': '2019-12-31'}, {'name': 'LinkedInCorporation', 'value': '2102000000', 'date': '2019-12-31'}, {'name': 'Devices', 'value': '2048000000', 'date': '2019-12-31'}, {'name': 'EnterpriseServices', 'value': '1612000000', 'date': '2019-12-31'}, {'name': 'OtherProductsAndServices', 'value': '959000000', 'date': '2019-12-31'}, {'name': 'Product', 'value': '15768000000', 'date': '2019-09-30'}, {'name': 'ServiceOther', 'value': '17287000000', 'date': '2019-09-30'}, {'name': 'ServerProductsAndCloudServices', 'value': '9192000000', 'date': '2019-09-30'}, {'name': 'OfficeProductsAndCloudServices', 'value': '8466000000', 'date': '2019-09-30'}, {'name': 'Windows', 'value': '5353000000', 'date': '2019-09-30'}, {'name': 'Gaming', 'value': '2542000000', 'date': '2019-09-30'}, {'name': 'SearchAdvertising', 'value': '1991000000', 'date': '2019-09-30'}, {'name': 'LinkedInCorporation', 'value': '1909000000', 'date': '2019-09-30'}, {'name': 'EnterpriseServices', 'value': '1545000000', 'date': '2019-09-30'}, {'name': 'Devices', 'value': '1202000000', 'date': '2019-09-30'}, {'name': 'OtherProductsAndServices', 'value': '855000000', 'date': '2019-09-30'}, {'name': 'Product', 'value': '15448000000', 'date': '2019-03-31'}, {'name': 'ServiceOther', 'value': '15123000000', 'date': '2019-03-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '7889000000', 'date': '2019-03-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '8053000000', 'date': '2019-03-31'}, {'name': 'Windows', 'value': '4944000000', 'date': '2019-03-31'}, {'name': 'Gaming', 'value': '2363000000', 'date': '2019-03-31'}, {'name': 'SearchAdvertising', 'value': '1911000000', 'date': '2019-03-31'}, {'name': 'LinkedInCorporation', 'value': '1696000000', 'date': '2019-03-31'}, {'name': 'Devices', 'value': '1423000000', 'date': '2019-03-31'}, {'name': 'EnterpriseServices', 'value': '1542000000', 'date': '2019-03-31'}, {'name': 'OtherProductsAndServices', 'value': '750000000', 'date': '2019-03-31'}, {'name': 'Product', 'value': '16219000000', 'date': '2018-12-31'}, {'name': 'ServiceOther', 'value': '16252000000', 'date': '2018-12-31'}, {'name': 'OfficeProductsAndCloudServices', 'value': '7747000000', 'date': '2018-12-31'}, {'name': 'ServerProductsAndCloudServices', 'value': '7791000000', 'date': '2018-12-31'}, {'name': 'Windows', 'value': '4758000000', 'date': '2018-12-31'}, {'name': 'Gaming', 'value': '4232000000', 'date': '2018-12-31'}, {'name': 'SearchAdvertising', 'value': '1976000000', 'date': '2018-12-31'}, {'name': 'LinkedInCorporation', 'value': '1693000000', 'date': '2018-12-31'}, {'name': 'Devices', 'value': '1948000000', 'date': '2018-12-31'}, {'name': 'EnterpriseServices', 'value': '1521000000', 'date': '2018-12-31'}, {'name': 'OtherProductsAndServices', 'value': '805000000', 'date': '2018-12-31'}]
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def generate_revenue_dataset(dataset):
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# Find all unique names and dates
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all_dates = sorted(set(item['date'] for item in dataset))
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all_names = sorted(set(item['name'] for item in dataset))
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# Check and fill missing combinations at the beginning
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name_date_map = defaultdict(lambda: defaultdict(lambda: None))
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for item in dataset:
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name_date_map[item['name']][item['date']] = item['value']
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# Ensure all names have entries for all dates
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for name in all_names:
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for date in all_dates:
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if date not in name_date_map[name]:
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dataset.append({'name': name, 'date': date, 'value': None})
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# Clean and process the dataset values
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processed_dataset = []
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for item in dataset:
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if item['value'] not in (None, '', 0):
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processed_dataset.append({
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'name': item['name'],
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'date': item['date'],
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'value': int(float(item['value']))
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})
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else:
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processed_dataset.append({
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'name': item['name'],
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'date': item['date'],
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'value': None
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})
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dataset = processed_dataset
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name_replacements = {
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"datacenter": "Data Center",
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"professionalvisualization": "Visualization",
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"oemandother": "OEM & Other",
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"automotive": "Automotive",
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"oemip": "OEM & Other",
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"gaming": "Gaming",
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"mac": "Mac",
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"iphone": "IPhone",
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"ipad": "IPad",
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"wearableshomeandaccessories": "Wearables",
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"hardwareandaccessories": "Hardware & Accessories",
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"software": "Software",
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"collectibles": "Collectibles",
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"automotivesales": "Auto",
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"energygenerationandstoragesegment": "Energy and Storage",
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"servicesandother": "Services & Other",
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"automotiveregulatorycredits": "Regulatory Credits",
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"intelligentcloud": "Intelligent Cloud",
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"productivityandbusinessprocesses": "Productivity & Business",
|
|
"searchandnewsadvertising": "Advertising",
|
|
"linkedincorporation": "LinkedIn",
|
|
"morepersonalcomputing": "More Personal Computing",
|
|
"serviceother": "Service Other",
|
|
}
|
|
|
|
# Filter out unwanted categories
|
|
excluded_names = {'automotiveleasing ','officeproductsandcloudservices','serverproductsandcloudservices','automotiverevenues','automotive','computeandnetworking','graphics','gpu','automotivesegment','energygenerationandstoragesales','energygenerationandstorage','automotivesaleswithoutresalevalueguarantee','salesandservices','compute', 'networking', 'cloudserviceagreements', 'digital', 'allother', 'preownedvideogameproducts'}
|
|
dataset = [revenue for revenue in dataset if revenue['name'].lower() not in excluded_names]
|
|
|
|
# Process and clean the dataset
|
|
for item in dataset:
|
|
try:
|
|
name = item.get('name').lower()
|
|
value = int(float(item.get('value')))
|
|
if name in name_replacements:
|
|
item['name'] = name_replacements[name]
|
|
item['value'] = value
|
|
except:
|
|
pass
|
|
|
|
# Group by name and calculate total value
|
|
name_totals = defaultdict(int)
|
|
for item in dataset:
|
|
name_totals[item['name']] += item['value'] if item['value'] != None else 0
|
|
|
|
# Sort names by total value and get top 5, ensuring excluded names are not considered
|
|
top_names = sorted(
|
|
[(name, total) for name, total in name_totals.items() if name.lower() not in excluded_names],
|
|
key=lambda x: x[1],
|
|
reverse=True
|
|
)[:5]
|
|
top_names = [name for name, _ in top_names]
|
|
|
|
# Filter dataset to include only top 5 names
|
|
dataset = [item for item in dataset if item['name'] in top_names]
|
|
|
|
# Sort the dataset
|
|
dataset.sort(key=lambda item: (datetime.strptime(item['date'], '%Y-%m-%d'), item['value'] if item['value'] != None else 0), reverse=True)
|
|
|
|
|
|
# Process the data into the required format
|
|
result = {}
|
|
for item in dataset:
|
|
date = item['date']
|
|
value = item['value']
|
|
if date not in result:
|
|
result[date] = {'date': date, 'value': []}
|
|
result[date]['value'].append(value)
|
|
|
|
# Convert the result dictionary to a list
|
|
res_list = list(result.values())
|
|
print(res_list)
|
|
# Add value growth (assuming add_value_growth function exists)
|
|
res_list = add_value_growth(res_list)
|
|
|
|
final_result = {'names': top_names, 'history': res_list}
|
|
return final_result
|
|
|
|
|
|
def generate_geography_dataset(dataset):
|
|
|
|
country_replacements = {
|
|
"country:us": "United States",
|
|
"country:cn": "China",
|
|
"chinaincludinghongkong": "China"
|
|
}
|
|
|
|
# Custom order for specific countries
|
|
custom_order = {
|
|
'United States': 2,
|
|
'China': 1,
|
|
'Other': 0
|
|
}
|
|
|
|
for item in dataset:
|
|
item['date'] = closest_quarter_end(item['date'])
|
|
name = item.get('name').lower()
|
|
value = int(float(item.get('value')))
|
|
if name in country_replacements:
|
|
item['name'] = country_replacements[name]
|
|
item['value'] = value
|
|
else:
|
|
item['name'] = 'Other'
|
|
item['value'] = value
|
|
|
|
dataset = aggregate_other_values(dataset)
|
|
dataset = sorted(
|
|
dataset,
|
|
key=lambda item: (datetime.strptime(item['date'], '%Y-%m-%d'), custom_order.get(item['name'], 3)),
|
|
reverse = True
|
|
)
|
|
|
|
dataset = compute_q4_results(dataset)
|
|
result = {}
|
|
|
|
# Iterate through the original data
|
|
for item in dataset:
|
|
# Get the date and value
|
|
date = item['date']
|
|
value = item['value']
|
|
|
|
# Initialize the dictionary for the date if not already done
|
|
if date not in result:
|
|
result[date] = {'date': date, 'value': []}
|
|
|
|
# Append the value to the list
|
|
result[date]['value'].append(value)
|
|
|
|
# Convert the result dictionary to a list
|
|
# Convert the result dictionary to a list
|
|
final_result = list(result.values())
|
|
|
|
# Print the final result
|
|
final_result = add_value_growth(final_result)
|
|
print(final_result)
|
|
|
|
|
|
#generate_revenue_dataset(revenue_sources)
|
|
generate_geography_dataset(geographic_sources)
|
|
|