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dfransiscaf
/ correlation_median_price_quantity
Created
October 6, 2025 06:12
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| import datetime | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| dataset = pd.read_csv('https://storage.googleapis.com/dqlab-dataset/retail_raw_reduced.csv') | |
| dataset['order_month'] = dataset['order_date'].apply(lambda x: datetime.datetime.strptime(x, "%Y-%m-%d").strftime('%Y-%m')) | |
| dataset['gmv'] = dataset['item_price']*dataset['quantity'] | |
| top_brands = (dataset[dataset['order_month']=='2019-12'].groupby('brand')['quantity'] | |
| .sum() | |
| .reset_index() | |
| .sort_values(by='quantity',ascending=False) |
dfransiscaf
/ correlation_quantity_gmv
Created
October 6, 2025 06:11
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| import datetime | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| dataset = pd.read_csv('https://storage.googleapis.com/dqlab-dataset/retail_raw_reduced.csv') | |
| dataset['order_month'] = dataset['order_date'].apply(lambda x: datetime.datetime.strptime(x, "%Y-%m-%d").strftime('%Y-%m')) | |
| dataset['gmv'] = dataset['item_price']*dataset['quantity'] | |
| top_brands = (dataset[dataset['order_month']=='2019-12'].groupby('brand')['quantity'] | |
| .sum() | |
| .reset_index() | |
| .sort_values(by='quantity',ascending=False) |
dfransiscaf
/ sales_analysis_per_brand_stacked_chart
Created
October 6, 2025 06:08
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| import datetime | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| dataset = pd.read_csv('https://storage.googleapis.com/dqlab-dataset/retail_raw_reduced.csv') | |
| dataset['order_month'] = dataset['order_date'].apply(lambda x: datetime.datetime.strptime(x, "%Y-%m-%d").strftime('%Y-%m')) | |
| dataset['gmv'] = dataset['item_price']*dataset['quantity'] | |
| top_brands = (dataset[dataset['order_month']=='2019-12'].groupby('brand')['quantity'] | |
| .sum() | |
| .reset_index() | |
| .sort_values(by='quantity',ascending=False) |
dfransiscaf
/ sales_analysis_per_brand
Created
October 6, 2025 06:04
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| import datetime | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| dataset = pd.read_csv('https://storage.googleapis.com/dqlab-dataset/retail_raw_reduced.csv') | |
| dataset['order_month'] = dataset['order_date'].apply(lambda x: datetime.datetime.strptime(x, "%Y-%m-%d").strftime('%Y-%m')) | |
| dataset['gmv'] = dataset['item_price']*dataset['quantity'] | |
| top_brands = (dataset[dataset['order_month']=='2019-12'].groupby('brand')['quantity'] | |
| .sum() | |
| .reset_index() | |
| .sort_values(by='quantity',ascending=False) |