├── LICENSE ├── README.md ├── Housing.csv └── retail_sales_dataset.csv /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 Deepak L 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Project 1 : Customer Segmentation Analysis 2 | 3 | ## Introduction 4 | 5 | This project is centered around customer segmentation, an essential strategy in modern marketing and business analytics. The goal is to analyze customer data to identify distinct segments within the customer base, enabling targeted marketing strategies, improved customer satisfaction, and optimized resource allocation. 6 | 7 | ### Objectives: 8 | - **Identify key customer segments** based on purchasing behavior and demographic information. 9 | - **Analyze the characteristics** of each segment to understand their preferences and needs. 10 | - **Provide actionable insights** for targeted marketing and business decisions. 11 | 12 | ## Data Insights 13 | 14 | ### Dataset Overview: 15 | The dataset contains various features related to customer demographics, purchase history, and response to marketing campaigns. Key columns include: 16 | - **Income**: The annual income of customers. 17 | - **Kidhome**: The number of children in the household. 18 | - **Teenhome**: The number of teenagers in the household. 19 | - **Recency**: Days since the last purchase. 20 | - **MntWines**: Amount spent on wine products. 21 | - **MntFruits**: Amount spent on fruit products. 22 | - **MntMeatProducts**: Amount spent on meat products. 23 | - **MntFishProducts**: Amount spent on fish products. 24 | - **MntSweetProducts**: Amount spent on sweet products. 25 | - **MntGoldProds**: Amount spent on gold products. 26 | - **AcceptedCmpOverall**: Number of accepted marketing campaigns. 27 | 28 | ### Analysis and Insights: 29 | - **Customer Segments**: The analysis likely includes clustering techniques to identify distinct customer segments. Each segment can be characterized by unique spending behaviors and demographic factors. 30 | - **Spending Patterns**: By analyzing the total spending (`MntTotal`) and spending on regular products (`MntRegularProds`), we can identify high-value customers who contribute significantly to revenue. 31 | - **Campaign Effectiveness**: The `AcceptedCmpOverall` feature allows for the evaluation of the effectiveness of past marketing campaigns, helping in the design of future strategies. 32 | 33 | ## Conclusion 34 | 35 | This project offers a comprehensive look at customer segmentation, providing valuable insights into customer behavior and preferences. These insights can drive targeted marketing efforts, enhance customer satisfaction, and ultimately lead to increased business success. 36 | 37 | 38 | ================================================================================================================================================================ 39 | 40 | 41 | # Project 2 : House Prices Analysis 42 | 43 | ## Project Overview 44 | This project analyzes a housing dataset to uncover factors that influence house prices. It involves data preprocessing, exploratory data analysis, and predictive modeling using linear regression. 45 | 46 | ## Dataset 47 | The dataset contains the following features related to houses: 48 | 49 | - **price**: The selling price of the house. 50 | - **area**: The size of the house in square feet. 51 | - **bedrooms**: The number of bedrooms. 52 | - **bathrooms**: The number of bathrooms. 53 | - **stories**: The number of stories in the house. 54 | - **mainroad**: Whether the house is located on the main road (`yes`/`no`). 55 | - **guestroom**: Presence of a guest room (`yes`/`no`). 56 | - **basement**: Presence of a basement (`yes`/`no`). 57 | - **hotwaterheating**: Whether the house has hot water heating (`yes`/`no`). 58 | - **airconditioning**: Whether the house has air conditioning (`yes`/`no`). 59 | - **parking**: The number of parking spaces. 60 | - **prefarea**: Whether the house is in a preferred area (`yes`/`no`). 61 | - **furnishingstatus**: The furnishing status of the house (`furnished`, `semi-furnished`, `unfurnished`). 62 | 63 | ## Dependencies 64 | The project requires the following Python libraries: 65 | - **Python 3.x** 66 | - **Pandas**: `pip install pandas` 67 | - **NumPy**: `pip install numpy` 68 | - **Matplotlib**: `pip install matplotlib` 69 | - **Scikit-learn**: `pip install scikit-learn` 70 | 71 | ## Data Insights 72 | Key insights obtained from the dataset include: 73 | - **Price Distribution**: Analysis of how house prices are distributed. 74 | - **Feature Relationships**: Investigation of correlations between house features and prices. 75 | - **Predictive Modeling**: A linear regression model to predict house prices based on various features, evaluated using metrics like mean squared error. 76 | 77 | 78 | =========================================================================================================================================================== 79 | 80 | 81 | # Project 3 :Retail Sales Data Analysis 82 | 83 | ## Project Overview 84 | 85 | This project involves the analysis of a retail sales dataset to uncover insights into customer spending behavior, product performance, and overall sales trends. The analysis was conducted using Python, utilizing libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualization. 86 | 87 | ### Objectives 88 | 89 | - **Understand the Data:** Explore the dataset to understand its structure and contents. 90 | - **Handle Missing Data:** Identify and manage any missing values in the dataset to ensure accurate analysis. 91 | - **Statistical Analysis:** Perform statistical analysis to derive key metrics like mean, median, mode, and standard deviation. 92 | - **Data Visualization:** Create visualizations to identify patterns and trends in the data. 93 | - **Correlation Analysis:** Explore relationships between different variables in the dataset. 94 | - **Product and Price Analysis:** Assess product performance and analyze the impact of pricing on sales. 95 | 96 | ## Data Insights 97 | 98 | ### 1. Customer Spending 99 | - The average spending per customer was calculated, providing insights into the purchasing behavior of the customer base. 100 | 101 | ### 2. Sales Statistics 102 | - Key statistics such as mean, median, mode, and standard deviation were derived for total sales amounts, helping to understand the central tendency and variability in the sales data. 103 | 104 | ### 3. Product Performance 105 | - **Total Sales by Product Category:** 106 | - A bar chart visualized total sales by product category, revealing the top-performing categories. 107 | - **Inventory Turnover:** 108 | - The analysis identified product categories with the lowest inventory turnover, highlighting areas for potential improvement in sales strategies. 109 | 110 | ### 4. Gender and Age Analysis 111 | - A line plot examined average purchases by gender, offering a demographic perspective on customer behavior. 112 | 113 | ### 5. Correlation Analysis 114 | - A correlation matrix was plotted to assess relationships between variables such as age, quantity purchased, and total amount spent. 115 | 116 | ### 6. Price Sensitivity 117 | - The relationship between price per unit and total sales was analyzed, providing insights into how pricing strategies might impact sales volumes. 118 | 119 | ## Tools and Technologies Used 120 | 121 | - **Python:** For data processing and analysis. 122 | - **Pandas:** For data manipulation and analysis. 123 | - **NumPy:** For numerical computations. 124 | - **Matplotlib & Seaborn:** For data visualization. 125 | 126 | 127 | ## Conclusion 128 | 129 | This analysis provided valuable insights into customer behavior, product performance, and pricing strategies. The visualizations and statistical analyses can serve as a basis for making data-driven decisions to enhance retail sales performance. 130 | -------------------------------------------------------------------------------- /Housing.csv: -------------------------------------------------------------------------------- 1 | price,area,bedrooms,bathrooms,stories,mainroad,guestroom,basement,hotwaterheating,airconditioning,parking,prefarea,furnishingstatus 2 | 13300000,7420,4,2,3,yes,no,no,no,yes,2,yes,furnished 3 | 12250000,8960,4,4,4,yes,no,no,no,yes,3,no,furnished 4 | 12250000,9960,3,2,2,yes,no,yes,no,no,2,yes,semi-furnished 5 | 12215000,7500,4,2,2,yes,no,yes,no,yes,3,yes,furnished 6 | 11410000,7420,4,1,2,yes,yes,yes,no,yes,2,no,furnished 7 | 10850000,7500,3,3,1,yes,no,yes,no,yes,2,yes,semi-furnished 8 | 10150000,8580,4,3,4,yes,no,no,no,yes,2,yes,semi-furnished 9 | 10150000,16200,5,3,2,yes,no,no,no,no,0,no,unfurnished 10 | 9870000,8100,4,1,2,yes,yes,yes,no,yes,2,yes,furnished 11 | 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| 3703000,3120,3,1,2,no,no,yes,yes,no,0,no,semi-furnished 367 | 3703000,5450,2,1,1,yes,no,no,no,no,0,no,furnished 368 | 3675000,3630,2,1,1,yes,no,yes,no,no,0,no,furnished 369 | 3675000,3630,2,1,1,yes,no,no,no,yes,0,no,unfurnished 370 | 3675000,5640,2,1,1,no,no,no,no,no,0,no,semi-furnished 371 | 3675000,3600,2,1,1,yes,no,no,no,no,0,no,furnished 372 | 3640000,4280,2,1,1,yes,no,no,no,yes,2,no,semi-furnished 373 | 3640000,3570,3,1,2,yes,no,yes,no,no,0,no,semi-furnished 374 | 3640000,3180,3,1,2,no,no,yes,no,no,0,no,semi-furnished 375 | 3640000,3000,2,1,2,yes,no,no,no,yes,0,no,furnished 376 | 3640000,3520,2,2,1,yes,no,yes,no,no,0,no,semi-furnished 377 | 3640000,5960,3,1,2,yes,yes,yes,no,no,0,no,unfurnished 378 | 3640000,4130,3,2,2,yes,no,no,no,no,2,no,semi-furnished 379 | 3640000,2850,3,2,2,no,no,yes,no,no,0,yes,unfurnished 380 | 3640000,2275,3,1,3,yes,no,no,yes,yes,0,yes,semi-furnished 381 | 3633000,3520,3,1,1,yes,no,no,no,no,2,yes,unfurnished 382 | 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| 3500000,5900,2,1,1,yes,no,no,no,no,1,no,furnished 400 | 3500000,3120,3,1,2,yes,no,no,no,no,1,no,unfurnished 401 | 3500000,7350,2,1,1,yes,no,no,no,no,1,no,semi-furnished 402 | 3500000,3512,2,1,1,yes,no,no,no,no,1,yes,unfurnished 403 | 3500000,9500,3,1,2,yes,no,no,no,no,3,yes,unfurnished 404 | 3500000,5880,2,1,1,yes,no,no,no,no,0,no,unfurnished 405 | 3500000,12944,3,1,1,yes,no,no,no,no,0,no,unfurnished 406 | 3493000,4900,3,1,2,no,no,no,no,no,0,no,unfurnished 407 | 3465000,3060,3,1,1,yes,no,no,no,no,0,no,unfurnished 408 | 3465000,5320,2,1,1,yes,no,no,no,no,1,yes,unfurnished 409 | 3465000,2145,3,1,3,yes,no,no,no,no,0,yes,furnished 410 | 3430000,4000,2,1,1,yes,no,no,no,no,0,no,unfurnished 411 | 3430000,3185,2,1,1,yes,no,no,no,no,2,no,unfurnished 412 | 3430000,3850,3,1,1,yes,no,no,no,no,0,no,unfurnished 413 | 3430000,2145,3,1,3,yes,no,no,no,no,0,yes,furnished 414 | 3430000,2610,3,1,2,yes,no,yes,no,no,0,yes,unfurnished 415 | 3430000,1950,3,2,2,yes,no,yes,no,no,0,yes,unfurnished 416 | 3423000,4040,2,1,1,yes,no,no,no,no,0,no,unfurnished 417 | 3395000,4785,3,1,2,yes,yes,yes,no,yes,1,no,furnished 418 | 3395000,3450,3,1,1,yes,no,yes,no,no,2,no,unfurnished 419 | 3395000,3640,2,1,1,yes,no,no,no,no,0,no,furnished 420 | 3360000,3500,4,1,2,yes,no,no,no,yes,2,no,unfurnished 421 | 3360000,4960,4,1,3,no,no,no,no,no,0,no,semi-furnished 422 | 3360000,4120,2,1,2,yes,no,no,no,no,0,no,unfurnished 423 | 3360000,4750,2,1,1,yes,no,no,no,no,0,no,unfurnished 424 | 3360000,3720,2,1,1,no,no,no,no,yes,0,no,unfurnished 425 | 3360000,3750,3,1,1,yes,no,no,no,no,0,no,unfurnished 426 | 3360000,3100,3,1,2,no,no,yes,no,no,0,no,semi-furnished 427 | 3360000,3185,2,1,1,yes,no,yes,no,no,2,no,furnished 428 | 3353000,2700,3,1,1,no,no,no,no,no,0,no,furnished 429 | 3332000,2145,3,1,2,yes,no,yes,no,no,0,yes,furnished 430 | 3325000,4040,2,1,1,yes,no,no,no,no,1,no,unfurnished 431 | 3325000,4775,4,1,2,yes,no,no,no,no,0,no,unfurnished 432 | 3290000,2500,2,1,1,no,no,no,no,yes,0,no,unfurnished 433 | 3290000,3180,4,1,2,yes,no,yes,no,yes,0,no,unfurnished 434 | 3290000,6060,3,1,1,yes,yes,yes,no,no,0,no,furnished 435 | 3290000,3480,4,1,2,no,no,no,no,no,1,no,semi-furnished 436 | 3290000,3792,4,1,2,yes,no,no,no,no,0,no,semi-furnished 437 | 3290000,4040,2,1,1,yes,no,no,no,no,0,no,unfurnished 438 | 3290000,2145,3,1,2,yes,no,yes,no,no,0,yes,furnished 439 | 3290000,5880,3,1,1,yes,no,no,no,no,1,no,unfurnished 440 | 3255000,4500,2,1,1,no,no,no,no,no,0,no,semi-furnished 441 | 3255000,3930,2,1,1,no,no,no,no,no,0,no,unfurnished 442 | 3234000,3640,4,1,2,yes,no,yes,no,no,0,no,unfurnished 443 | 3220000,4370,3,1,2,yes,no,no,no,no,0,no,unfurnished 444 | 3220000,2684,2,1,1,yes,no,no,no,yes,1,no,unfurnished 445 | 3220000,4320,3,1,1,no,no,no,no,no,1,no,unfurnished 446 | 3220000,3120,3,1,2,no,no,no,no,no,0,no,furnished 447 | 3150000,3450,1,1,1,yes,no,no,no,no,0,no,furnished 448 | 3150000,3986,2,2,1,no,yes,yes,no,no,1,no,unfurnished 449 | 3150000,3500,2,1,1,no,no,yes,no,no,0,no,semi-furnished 450 | 3150000,4095,2,1,1,yes,no,no,no,no,2,no,semi-furnished 451 | 3150000,1650,3,1,2,no,no,yes,no,no,0,no,unfurnished 452 | 3150000,3450,3,1,2,yes,no,yes,no,no,0,no,semi-furnished 453 | 3150000,6750,2,1,1,yes,no,no,no,no,0,no,semi-furnished 454 | 3150000,9000,3,1,2,yes,no,no,no,no,2,no,semi-furnished 455 | 3150000,3069,2,1,1,yes,no,no,no,no,1,no,unfurnished 456 | 3143000,4500,3,1,2,yes,no,no,no,yes,0,no,unfurnished 457 | 3129000,5495,3,1,1,yes,no,yes,no,no,0,no,unfurnished 458 | 3118850,2398,3,1,1,yes,no,no,no,no,0,yes,semi-furnished 459 | 3115000,3000,3,1,1,no,no,no,no,yes,0,no,unfurnished 460 | 3115000,3850,3,1,2,yes,no,no,no,no,0,no,unfurnished 461 | 3115000,3500,2,1,1,yes,no,no,no,no,0,no,unfurnished 462 | 3087000,8100,2,1,1,yes,no,no,no,no,1,no,unfurnished 463 | 3080000,4960,2,1,1,yes,no,yes,no,yes,0,no,unfurnished 464 | 3080000,2160,3,1,2,no,no,yes,no,no,0,no,semi-furnished 465 | 3080000,3090,2,1,1,yes,yes,yes,no,no,0,no,unfurnished 466 | 3080000,4500,2,1,2,yes,no,no,yes,no,1,no,semi-furnished 467 | 3045000,3800,2,1,1,yes,no,no,no,no,0,no,unfurnished 468 | 3010000,3090,3,1,2,no,no,no,no,no,0,no,semi-furnished 469 | 3010000,3240,3,1,2,yes,no,no,no,no,2,no,semi-furnished 470 | 3010000,2835,2,1,1,yes,no,no,no,no,0,no,semi-furnished 471 | 3010000,4600,2,1,1,yes,no,no,no,no,0,no,furnished 472 | 3010000,5076,3,1,1,no,no,no,no,no,0,no,unfurnished 473 | 3010000,3750,3,1,2,yes,no,no,no,no,0,no,unfurnished 474 | 3010000,3630,4,1,2,yes,no,no,no,no,3,no,semi-furnished 475 | 3003000,8050,2,1,1,yes,no,no,no,no,0,no,unfurnished 476 | 2975000,4352,4,1,2,no,no,no,no,no,1,no,unfurnished 477 | 2961000,3000,2,1,2,yes,no,no,no,no,0,no,semi-furnished 478 | 2940000,5850,3,1,2,yes,no,yes,no,no,1,no,unfurnished 479 | 2940000,4960,2,1,1,yes,no,no,no,no,0,no,unfurnished 480 | 2940000,3600,3,1,2,no,no,no,no,no,1,no,unfurnished 481 | 2940000,3660,4,1,2,no,no,no,no,no,0,no,unfurnished 482 | 2940000,3480,3,1,2,no,no,no,no,no,1,no,semi-furnished 483 | 2940000,2700,2,1,1,no,no,no,no,no,0,no,furnished 484 | 2940000,3150,3,1,2,no,no,no,no,no,0,no,unfurnished 485 | 2940000,6615,3,1,2,yes,no,no,no,no,0,no,semi-furnished 486 | 2870000,3040,2,1,1,no,no,no,no,no,0,no,unfurnished 487 | 2870000,3630,2,1,1,yes,no,no,no,no,0,no,unfurnished 488 | 2870000,6000,2,1,1,yes,no,no,no,no,0,no,semi-furnished 489 | 2870000,5400,4,1,2,yes,no,no,no,no,0,no,unfurnished 490 | 2852500,5200,4,1,3,yes,no,no,no,no,0,no,unfurnished 491 | 2835000,3300,3,1,2,no,no,no,no,no,1,no,semi-furnished 492 | 2835000,4350,3,1,2,no,no,no,yes,no,1,no,unfurnished 493 | 2835000,2640,2,1,1,no,no,no,no,no,1,no,furnished 494 | 2800000,2650,3,1,2,yes,no,yes,no,no,1,no,unfurnished 495 | 2800000,3960,3,1,1,yes,no,no,no,no,0,no,furnished 496 | 2730000,6800,2,1,1,yes,no,no,no,no,0,no,unfurnished 497 | 2730000,4000,3,1,2,yes,no,no,no,no,1,no,unfurnished 498 | 2695000,4000,2,1,1,yes,no,no,no,no,0,no,unfurnished 499 | 2660000,3934,2,1,1,yes,no,no,no,no,0,no,unfurnished 500 | 2660000,2000,2,1,2,yes,no,no,no,no,0,no,semi-furnished 501 | 2660000,3630,3,3,2,no,yes,no,no,no,0,no,unfurnished 502 | 2660000,2800,3,1,1,yes,no,no,no,no,0,no,unfurnished 503 | 2660000,2430,3,1,1,no,no,no,no,no,0,no,unfurnished 504 | 2660000,3480,2,1,1,yes,no,no,no,no,1,no,semi-furnished 505 | 2660000,4000,3,1,1,yes,no,no,no,no,0,no,semi-furnished 506 | 2653000,3185,2,1,1,yes,no,no,no,yes,0,no,unfurnished 507 | 2653000,4000,3,1,2,yes,no,no,no,yes,0,no,unfurnished 508 | 2604000,2910,2,1,1,no,no,no,no,no,0,no,unfurnished 509 | 2590000,3600,2,1,1,yes,no,no,no,no,0,no,unfurnished 510 | 2590000,4400,2,1,1,yes,no,no,no,no,0,no,unfurnished 511 | 2590000,3600,2,2,2,yes,no,yes,no,no,1,no,furnished 512 | 2520000,2880,3,1,1,no,no,no,no,no,0,no,unfurnished 513 | 2520000,3180,3,1,1,no,no,no,no,no,0,no,unfurnished 514 | 2520000,3000,2,1,2,yes,no,no,no,no,0,no,furnished 515 | 2485000,4400,3,1,2,yes,no,no,no,no,0,no,unfurnished 516 | 2485000,3000,3,1,2,no,no,no,no,no,0,no,semi-furnished 517 | 2450000,3210,3,1,2,yes,no,yes,no,no,0,no,unfurnished 518 | 2450000,3240,2,1,1,no,yes,no,no,no,1,no,unfurnished 519 | 2450000,3000,2,1,1,yes,no,no,no,no,1,no,unfurnished 520 | 2450000,3500,2,1,1,yes,yes,no,no,no,0,no,unfurnished 521 | 2450000,4840,2,1,2,yes,no,no,no,no,0,no,unfurnished 522 | 2450000,7700,2,1,1,yes,no,no,no,no,0,no,unfurnished 523 | 2408000,3635,2,1,1,no,no,no,no,no,0,no,unfurnished 524 | 2380000,2475,3,1,2,yes,no,no,no,no,0,no,furnished 525 | 2380000,2787,4,2,2,yes,no,no,no,no,0,no,furnished 526 | 2380000,3264,2,1,1,yes,no,no,no,no,0,no,unfurnished 527 | 2345000,3640,2,1,1,yes,no,no,no,no,0,no,unfurnished 528 | 2310000,3180,2,1,1,yes,no,no,no,no,0,no,unfurnished 529 | 2275000,1836,2,1,1,no,no,yes,no,no,0,no,semi-furnished 530 | 2275000,3970,1,1,1,no,no,no,no,no,0,no,unfurnished 531 | 2275000,3970,3,1,2,yes,no,yes,no,no,0,no,unfurnished 532 | 2240000,1950,3,1,1,no,no,no,yes,no,0,no,unfurnished 533 | 2233000,5300,3,1,1,no,no,no,no,yes,0,yes,unfurnished 534 | 2135000,3000,2,1,1,no,no,no,no,no,0,no,unfurnished 535 | 2100000,2400,3,1,2,yes,no,no,no,no,0,no,unfurnished 536 | 2100000,3000,4,1,2,yes,no,no,no,no,0,no,unfurnished 537 | 2100000,3360,2,1,1,yes,no,no,no,no,1,no,unfurnished 538 | 1960000,3420,5,1,2,no,no,no,no,no,0,no,unfurnished 539 | 1890000,1700,3,1,2,yes,no,no,no,no,0,no,unfurnished 540 | 1890000,3649,2,1,1,yes,no,no,no,no,0,no,unfurnished 541 | 1855000,2990,2,1,1,no,no,no,no,no,1,no,unfurnished 542 | 1820000,3000,2,1,1,yes,no,yes,no,no,2,no,unfurnished 543 | 1767150,2400,3,1,1,no,no,no,no,no,0,no,semi-furnished 544 | 1750000,3620,2,1,1,yes,no,no,no,no,0,no,unfurnished 545 | 1750000,2910,3,1,1,no,no,no,no,no,0,no,furnished 546 | 1750000,3850,3,1,2,yes,no,no,no,no,0,no,unfurnished 547 | -------------------------------------------------------------------------------- /retail_sales_dataset.csv: -------------------------------------------------------------------------------- 1 | Transaction ID,Date,Customer ID,Gender,Age,Product Category,Quantity,Price per Unit,Total Amount 2 | 1,2023-11-24,CUST001,Male,34,Beauty,3,50,150 3 | 2,2023-02-27,CUST002,Female,26,Clothing,2,500,1000 4 | 3,2023-01-13,CUST003,Male,50,Electronics,1,30,30 5 | 4,2023-05-21,CUST004,Male,37,Clothing,1,500,500 6 | 5,2023-05-06,CUST005,Male,30,Beauty,2,50,100 7 | 6,2023-04-25,CUST006,Female,45,Beauty,1,30,30 8 | 7,2023-03-13,CUST007,Male,46,Clothing,2,25,50 9 | 8,2023-02-22,CUST008,Male,30,Electronics,4,25,100 10 | 9,2023-12-13,CUST009,Male,63,Electronics,2,300,600 11 | 10,2023-10-07,CUST010,Female,52,Clothing,4,50,200 12 | 11,2023-02-14,CUST011,Male,23,Clothing,2,50,100 13 | 12,2023-10-30,CUST012,Male,35,Beauty,3,25,75 14 | 13,2023-08-05,CUST013,Male,22,Electronics,3,500,1500 15 | 14,2023-01-17,CUST014,Male,64,Clothing,4,30,120 16 | 15,2023-01-16,CUST015,Female,42,Electronics,4,500,2000 17 | 16,2023-02-17,CUST016,Male,19,Clothing,3,500,1500 18 | 17,2023-04-22,CUST017,Female,27,Clothing,4,25,100 19 | 18,2023-04-30,CUST018,Female,47,Electronics,2,25,50 20 | 19,2023-09-16,CUST019,Female,62,Clothing,2,25,50 21 | 20,2023-11-05,CUST020,Male,22,Clothing,3,300,900 22 | 21,2023-01-14,CUST021,Female,50,Beauty,1,500,500 23 | 22,2023-10-15,CUST022,Male,18,Clothing,2,50,100 24 | 23,2023-04-12,CUST023,Female,35,Clothing,4,30,120 25 | 24,2023-11-29,CUST024,Female,49,Clothing,1,300,300 26 | 25,2023-12-26,CUST025,Female,64,Beauty,1,50,50 27 | 26,2023-10-07,CUST026,Female,28,Electronics,2,500,1000 28 | 27,2023-08-03,CUST027,Female,38,Beauty,2,25,50 29 | 28,2023-04-23,CUST028,Female,43,Beauty,1,500,500 30 | 29,2023-08-18,CUST029,Female,42,Electronics,1,30,30 31 | 30,2023-10-29,CUST030,Female,39,Beauty,3,300,900 32 | 31,2023-05-23,CUST031,Male,44,Electronics,4,300,1200 33 | 32,2023-01-04,CUST032,Male,30,Beauty,3,30,90 34 | 33,2023-03-23,CUST033,Female,50,Electronics,2,50,100 35 | 34,2023-12-24,CUST034,Female,51,Clothing,3,50,150 36 | 35,2023-08-05,CUST035,Female,58,Beauty,3,300,900 37 | 36,2023-06-24,CUST036,Male,52,Beauty,3,300,900 38 | 37,2023-05-23,CUST037,Female,18,Beauty,3,25,75 39 | 38,2023-03-21,CUST038,Male,38,Beauty,4,50,200 40 | 39,2023-04-21,CUST039,Male,23,Clothing,4,30,120 41 | 40,2023-06-22,CUST040,Male,45,Beauty,1,50,50 42 | 41,2023-02-22,CUST041,Male,34,Clothing,2,25,50 43 | 42,2023-02-17,CUST042,Male,22,Clothing,3,300,900 44 | 43,2023-07-14,CUST043,Female,48,Clothing,1,300,300 45 | 44,2023-02-19,CUST044,Female,22,Clothing,1,25,25 46 | 45,2023-07-03,CUST045,Female,55,Electronics,1,30,30 47 | 46,2023-06-26,CUST046,Female,20,Electronics,4,300,1200 48 | 47,2023-11-06,CUST047,Female,40,Beauty,3,500,1500 49 | 48,2023-05-16,CUST048,Male,54,Electronics,3,300,900 50 | 49,2023-01-23,CUST049,Female,54,Electronics,2,500,1000 51 | 50,2023-08-24,CUST050,Female,27,Beauty,3,25,75 52 | 51,2023-10-02,CUST051,Male,27,Beauty,3,25,75 53 | 52,2023-03-05,CUST052,Female,36,Beauty,1,300,300 54 | 53,2023-07-13,CUST053,Male,34,Electronics,2,50,100 55 | 54,2023-02-10,CUST054,Female,38,Electronics,3,500,1500 56 | 55,2023-10-10,CUST055,Male,31,Beauty,4,30,120 57 | 56,2023-05-31,CUST056,Female,26,Clothing,3,300,900 58 | 57,2023-11-18,CUST057,Female,63,Beauty,1,30,30 59 | 58,2023-11-13,CUST058,Male,18,Clothing,4,300,1200 60 | 59,2023-07-05,CUST059,Male,62,Clothing,1,50,50 61 | 60,2023-10-23,CUST060,Male,30,Beauty,3,50,150 62 | 61,2023-04-09,CUST061,Male,21,Beauty,4,50,200 63 | 62,2023-12-27,CUST062,Male,18,Beauty,2,50,100 64 | 63,2023-02-05,CUST063,Male,57,Electronics,2,25,50 65 | 64,2023-01-24,CUST064,Male,49,Clothing,4,25,100 66 | 65,2023-12-05,CUST065,Male,51,Electronics,4,500,2000 67 | 66,2023-04-27,CUST066,Female,45,Electronics,1,30,30 68 | 67,2023-05-29,CUST067,Female,48,Beauty,4,300,1200 69 | 68,2023-02-10,CUST068,Male,25,Electronics,1,300,300 70 | 69,2023-04-30,CUST069,Female,56,Beauty,3,25,75 71 | 70,2023-02-21,CUST070,Female,43,Clothing,1,300,300 72 | 71,2023-07-14,CUST071,Female,51,Beauty,4,25,100 73 | 72,2023-05-23,CUST072,Female,20,Electronics,4,500,2000 74 | 73,2023-08-21,CUST073,Male,29,Electronics,3,30,90 75 | 74,2023-11-22,CUST074,Female,18,Beauty,4,500,2000 76 | 75,2023-07-06,CUST075,Male,61,Beauty,4,50,200 77 | 76,2023-03-25,CUST076,Female,22,Electronics,2,50,100 78 | 77,2023-07-09,CUST077,Female,47,Clothing,2,50,100 79 | 78,2023-07-01,CUST078,Female,47,Clothing,3,500,1500 80 | 79,2023-04-18,CUST079,Male,34,Beauty,1,300,300 81 | 80,2023-12-10,CUST080,Female,64,Clothing,2,30,60 82 | 81,2023-05-17,CUST081,Male,40,Electronics,1,50,50 83 | 82,2023-12-26,CUST082,Female,32,Beauty,4,50,200 84 | 83,2023-12-16,CUST083,Male,54,Electronics,2,50,100 85 | 84,2023-11-28,CUST084,Female,38,Electronics,3,30,90 86 | 85,2023-02-06,CUST085,Male,31,Clothing,3,50,150 87 | 86,2023-11-08,CUST086,Male,19,Beauty,3,30,90 88 | 87,2023-11-22,CUST087,Female,28,Beauty,2,50,100 89 | 88,2023-03-29,CUST088,Male,56,Clothing,1,500,500 90 | 89,2023-10-01,CUST089,Female,55,Electronics,4,500,2000 91 | 90,2023-05-06,CUST090,Female,51,Electronics,1,30,30 92 | 91,2023-03-25,CUST091,Female,55,Electronics,1,500,500 93 | 92,2023-08-25,CUST092,Female,51,Electronics,4,30,120 94 | 93,2023-07-14,CUST093,Female,35,Beauty,4,500,2000 95 | 94,2023-05-19,CUST094,Female,47,Beauty,2,500,1000 96 | 95,2023-11-24,CUST095,Female,32,Clothing,2,30,60 97 | 96,2023-12-19,CUST096,Female,44,Clothing,2,300,600 98 | 97,2023-10-13,CUST097,Female,51,Beauty,2,500,1000 99 | 98,2023-04-23,CUST098,Female,55,Beauty,2,50,100 100 | 99,2023-12-17,CUST099,Female,50,Electronics,4,300,1200 101 | 100,2023-06-16,CUST100,Male,41,Electronics,1,30,30 102 | 101,2023-01-29,CUST101,Male,32,Clothing,2,300,600 103 | 102,2023-04-28,CUST102,Female,47,Beauty,2,25,50 104 | 103,2023-01-17,CUST103,Female,59,Clothing,1,25,25 105 | 104,2023-06-11,CUST104,Female,34,Beauty,2,500,1000 106 | 105,2023-07-25,CUST105,Female,22,Electronics,1,500,500 107 | 106,2023-05-18,CUST106,Female,46,Clothing,1,50,50 108 | 107,2023-02-03,CUST107,Female,21,Clothing,4,300,1200 109 | 108,2023-04-19,CUST108,Female,27,Beauty,3,25,75 110 | 109,2023-10-18,CUST109,Female,34,Electronics,4,500,2000 111 | 110,2023-06-11,CUST110,Male,27,Clothing,3,300,900 112 | 111,2023-04-19,CUST111,Female,34,Electronics,3,500,1500 113 | 112,2023-12-02,CUST112,Male,37,Clothing,3,500,1500 114 | 113,2023-09-13,CUST113,Female,41,Electronics,2,25,50 115 | 114,2023-07-22,CUST114,Female,22,Beauty,4,25,100 116 | 115,2023-11-26,CUST115,Male,51,Clothing,3,500,1500 117 | 116,2023-08-23,CUST116,Female,23,Clothing,1,30,30 118 | 117,2023-03-15,CUST117,Male,19,Electronics,2,500,1000 119 | 118,2023-05-16,CUST118,Female,30,Electronics,4,500,2000 120 | 119,2023-03-13,CUST119,Female,60,Clothing,3,50,150 121 | 120,2023-05-07,CUST120,Male,60,Beauty,1,50,50 122 | 121,2023-10-15,CUST121,Female,28,Electronics,4,50,200 123 | 122,2023-10-03,CUST122,Male,64,Electronics,4,30,120 124 | 123,2023-05-15,CUST123,Female,40,Electronics,2,30,60 125 | 124,2023-10-27,CUST124,Male,33,Clothing,4,500,2000 126 | 125,2023-08-08,CUST125,Male,48,Clothing,2,50,100 127 | 126,2023-10-26,CUST126,Female,28,Clothing,3,30,90 128 | 127,2023-07-24,CUST127,Female,33,Clothing,2,25,50 129 | 128,2023-07-05,CUST128,Male,25,Beauty,1,500,500 130 | 129,2023-04-23,CUST129,Female,21,Beauty,2,300,600 131 | 130,2023-03-12,CUST130,Female,57,Clothing,1,500,500 132 | 131,2023-09-18,CUST131,Female,21,Beauty,2,300,600 133 | 132,2023-09-10,CUST132,Male,42,Electronics,4,50,200 134 | 133,2023-02-16,CUST133,Male,20,Electronics,3,300,900 135 | 134,2023-01-25,CUST134,Male,49,Electronics,1,50,50 136 | 135,2023-02-26,CUST135,Male,20,Clothing,2,25,50 137 | 136,2023-03-20,CUST136,Male,44,Electronics,2,300,600 138 | 137,2023-11-18,CUST137,Male,46,Beauty,2,500,1000 139 | 138,2023-03-23,CUST138,Male,49,Clothing,4,50,200 140 | 139,2023-12-15,CUST139,Male,36,Beauty,4,500,2000 141 | 140,2023-08-05,CUST140,Male,38,Electronics,1,30,30 142 | 141,2023-11-02,CUST141,Female,22,Electronics,1,50,50 143 | 142,2023-02-02,CUST142,Male,35,Electronics,4,300,1200 144 | 143,2023-07-17,CUST143,Female,45,Clothing,1,50,50 145 | 144,2023-07-15,CUST144,Female,59,Beauty,3,500,1500 146 | 145,2023-11-02,CUST145,Female,39,Clothing,3,25,75 147 | 146,2023-08-28,CUST146,Male,38,Clothing,4,50,200 148 | 147,2023-09-28,CUST147,Male,23,Electronics,1,300,300 149 | 148,2023-05-09,CUST148,Male,18,Clothing,2,30,60 150 | 149,2023-10-11,CUST149,Male,22,Clothing,3,25,75 151 | 150,2023-01-06,CUST150,Female,58,Electronics,4,30,120 152 | 151,2023-12-15,CUST151,Male,29,Clothing,1,50,50 153 | 152,2023-02-28,CUST152,Male,43,Electronics,4,500,2000 154 | 153,2023-12-16,CUST153,Male,63,Electronics,2,500,1000 155 | 154,2023-10-02,CUST154,Male,51,Electronics,3,300,900 156 | 155,2023-05-17,CUST155,Male,31,Electronics,4,500,2000 157 | 156,2023-11-25,CUST156,Female,43,Clothing,4,25,100 158 | 157,2023-06-24,CUST157,Male,62,Electronics,4,500,2000 159 | 158,2023-02-27,CUST158,Female,44,Electronics,2,300,600 160 | 159,2023-05-31,CUST159,Male,26,Clothing,4,50,200 161 | 160,2023-08-11,CUST160,Female,43,Clothing,2,50,100 162 | 161,2023-03-22,CUST161,Male,64,Beauty,2,500,1000 163 | 162,2023-08-21,CUST162,Male,39,Clothing,2,30,60 164 | 163,2023-01-02,CUST163,Female,64,Clothing,3,50,150 165 | 164,2023-05-15,CUST164,Female,47,Beauty,3,500,1500 166 | 165,2023-09-14,CUST165,Female,60,Clothing,4,300,1200 167 | 166,2023-04-02,CUST166,Male,34,Clothing,4,500,2000 168 | 167,2023-09-17,CUST167,Female,43,Clothing,3,50,150 169 | 168,2023-02-24,CUST168,Male,53,Clothing,1,300,300 170 | 169,2023-11-17,CUST169,Male,18,Beauty,3,500,1500 171 | 170,2023-06-02,CUST170,Female,25,Clothing,2,25,50 172 | 171,2023-11-24,CUST171,Female,52,Clothing,3,300,900 173 | 172,2023-09-17,CUST172,Male,32,Beauty,2,25,50 174 | 173,2023-11-08,CUST173,Male,64,Electronics,4,30,120 175 | 174,2023-04-12,CUST174,Female,39,Beauty,1,300,300 176 | 175,2023-03-20,CUST175,Female,31,Electronics,4,25,100 177 | 176,2023-07-11,CUST176,Female,43,Beauty,2,50,100 178 | 177,2023-03-24,CUST177,Male,45,Beauty,2,50,100 179 | 178,2023-10-04,CUST178,Male,40,Clothing,2,30,60 180 | 179,2023-09-29,CUST179,Male,31,Electronics,1,300,300 181 | 180,2023-01-01,CUST180,Male,41,Clothing,3,300,900 182 | 181,2023-11-03,CUST181,Male,19,Electronics,4,300,1200 183 | 182,2023-06-15,CUST182,Male,62,Beauty,4,30,120 184 | 183,2023-09-08,CUST183,Female,43,Beauty,3,300,900 185 | 184,2023-01-10,CUST184,Male,31,Electronics,4,50,200 186 | 185,2023-02-27,CUST185,Male,24,Clothing,1,25,25 187 | 186,2023-07-05,CUST186,Male,20,Clothing,4,50,200 188 | 187,2023-06-07,CUST187,Female,64,Clothing,2,50,100 189 | 188,2023-05-03,CUST188,Male,40,Clothing,3,25,75 190 | 189,2023-01-30,CUST189,Male,63,Beauty,1,50,50 191 | 190,2023-05-04,CUST190,Female,60,Beauty,3,30,90 192 | 191,2023-10-18,CUST191,Male,64,Beauty,1,25,25 193 | 192,2023-02-10,CUST192,Male,62,Beauty,2,50,100 194 | 193,2023-02-13,CUST193,Male,35,Beauty,3,500,1500 195 | 194,2023-09-06,CUST194,Male,55,Clothing,4,50,200 196 | 195,2023-02-05,CUST195,Male,52,Clothing,1,30,30 197 | 196,2023-09-30,CUST196,Female,32,Clothing,3,300,900 198 | 197,2023-03-06,CUST197,Female,42,Clothing,4,50,200 199 | 198,2023-03-07,CUST198,Female,54,Beauty,3,300,900 200 | 199,2023-12-04,CUST199,Male,45,Beauty,3,500,1500 201 | 200,2023-09-01,CUST200,Male,27,Beauty,3,50,150 202 | 201,2023-10-09,CUST201,Male,56,Electronics,1,25,25 203 | 202,2023-03-26,CUST202,Female,34,Clothing,4,300,1200 204 | 203,2023-05-16,CUST203,Male,56,Clothing,2,500,1000 205 | 204,2023-09-28,CUST204,Male,39,Beauty,1,25,25 206 | 205,2023-11-07,CUST205,Female,43,Clothing,1,25,25 207 | 206,2023-08-05,CUST206,Male,61,Clothing,1,25,25 208 | 207,2023-04-19,CUST207,Female,42,Beauty,2,25,50 209 | 208,2023-10-04,CUST208,Female,34,Electronics,4,50,200 210 | 209,2023-12-20,CUST209,Female,30,Electronics,4,50,200 211 | 210,2023-04-13,CUST210,Male,37,Electronics,4,50,200 212 | 211,2024-01-01,CUST211,Male,42,Beauty,3,500,1500 213 | 212,2023-06-09,CUST212,Male,21,Clothing,3,500,1500 214 | 213,2023-07-24,CUST213,Male,27,Beauty,3,500,1500 215 | 214,2023-12-10,CUST214,Male,20,Beauty,2,30,60 216 | 215,2023-11-29,CUST215,Male,58,Clothing,3,500,1500 217 | 216,2023-07-11,CUST216,Male,62,Electronics,2,50,100 218 | 217,2023-08-13,CUST217,Female,35,Electronics,4,50,200 219 | 218,2023-09-22,CUST218,Male,64,Beauty,3,30,90 220 | 219,2023-08-20,CUST219,Female,53,Electronics,3,30,90 221 | 220,2023-03-03,CUST220,Male,64,Beauty,1,500,500 222 | 221,2023-05-07,CUST221,Male,39,Beauty,2,300,600 223 | 222,2023-04-26,CUST222,Male,51,Clothing,4,30,120 224 | 223,2023-02-02,CUST223,Female,64,Clothing,1,25,25 225 | 224,2023-06-23,CUST224,Female,25,Clothing,1,50,50 226 | 225,2023-01-11,CUST225,Female,57,Beauty,4,25,100 227 | 226,2023-10-29,CUST226,Female,61,Clothing,1,50,50 228 | 227,2023-10-11,CUST227,Male,36,Electronics,2,50,100 229 | 228,2023-04-28,CUST228,Female,59,Electronics,2,30,60 230 | 229,2023-10-29,CUST229,Male,58,Beauty,3,30,90 231 | 230,2023-04-23,CUST230,Male,54,Beauty,1,25,25 232 | 231,2023-01-04,CUST231,Female,23,Clothing,3,50,150 233 | 232,2023-02-06,CUST232,Female,43,Beauty,1,25,25 234 | 233,2023-12-29,CUST233,Female,51,Beauty,2,300,600 235 | 234,2023-11-20,CUST234,Female,62,Electronics,2,25,50 236 | 235,2023-01-31,CUST235,Female,23,Electronics,2,500,1000 237 | 236,2023-04-28,CUST236,Female,54,Clothing,1,25,25 238 | 237,2023-02-04,CUST237,Female,50,Beauty,2,500,1000 239 | 238,2023-01-17,CUST238,Female,39,Beauty,1,500,500 240 | 239,2023-06-19,CUST239,Male,38,Electronics,3,500,1500 241 | 240,2023-02-06,CUST240,Female,23,Beauty,1,300,300 242 | 241,2023-09-21,CUST241,Female,23,Electronics,3,25,75 243 | 242,2023-05-02,CUST242,Male,21,Clothing,1,25,25 244 | 243,2023-05-23,CUST243,Female,47,Electronics,3,300,900 245 | 244,2023-12-09,CUST244,Male,28,Beauty,2,50,100 246 | 245,2023-09-06,CUST245,Male,47,Clothing,3,30,90 247 | 246,2023-04-20,CUST246,Female,48,Electronics,2,25,50 248 | 247,2023-10-04,CUST247,Male,41,Electronics,2,30,60 249 | 248,2023-03-09,CUST248,Male,26,Clothing,3,300,900 250 | 249,2023-10-20,CUST249,Male,20,Clothing,1,50,50 251 | 250,2023-10-23,CUST250,Male,48,Electronics,1,50,50 252 | 251,2023-08-31,CUST251,Female,57,Beauty,4,50,200 253 | 252,2023-05-05,CUST252,Male,54,Electronics,1,300,300 254 | 253,2023-08-31,CUST253,Female,53,Clothing,4,500,2000 255 | 254,2023-07-28,CUST254,Male,41,Electronics,1,500,500 256 | 255,2023-04-08,CUST255,Male,48,Clothing,1,30,30 257 | 256,2023-02-18,CUST256,Male,23,Clothing,2,500,1000 258 | 257,2023-02-19,CUST257,Male,19,Beauty,4,500,2000 259 | 258,2023-12-04,CUST258,Female,37,Clothing,1,50,50 260 | 259,2023-08-09,CUST259,Female,45,Clothing,4,50,200 261 | 260,2023-07-01,CUST260,Male,28,Beauty,2,30,60 262 | 261,2023-08-05,CUST261,Male,21,Clothing,2,25,50 263 | 262,2023-07-30,CUST262,Female,32,Beauty,4,30,120 264 | 263,2023-08-28,CUST263,Male,23,Beauty,2,30,60 265 | 264,2023-01-28,CUST264,Male,47,Clothing,3,300,900 266 | 265,2023-12-11,CUST265,Male,55,Clothing,3,300,900 267 | 266,2023-12-01,CUST266,Female,19,Electronics,2,30,60 268 | 267,2023-11-27,CUST267,Female,32,Beauty,3,30,90 269 | 268,2023-02-20,CUST268,Female,28,Electronics,1,30,30 270 | 269,2023-02-01,CUST269,Male,25,Clothing,4,500,2000 271 | 270,2023-07-26,CUST270,Male,43,Electronics,1,300,300 272 | 271,2023-06-23,CUST271,Female,62,Beauty,4,30,120 273 | 272,2023-02-25,CUST272,Female,61,Electronics,2,50,100 274 | 273,2023-05-08,CUST273,Female,22,Beauty,1,50,50 275 | 274,2023-04-09,CUST274,Female,23,Clothing,2,500,1000 276 | 275,2023-04-08,CUST275,Male,43,Clothing,2,500,1000 277 | 276,2023-10-02,CUST276,Female,21,Beauty,4,25,100 278 | 277,2023-08-18,CUST277,Male,36,Clothing,4,25,100 279 | 278,2023-03-13,CUST278,Female,37,Clothing,4,25,100 280 | 279,2023-08-05,CUST279,Male,50,Clothing,1,500,500 281 | 280,2023-04-04,CUST280,Female,37,Clothing,3,500,1500 282 | 281,2023-05-23,CUST281,Female,29,Beauty,4,500,2000 283 | 282,2023-08-25,CUST282,Female,64,Electronics,4,50,200 284 | 283,2023-05-08,CUST283,Female,18,Electronics,1,500,500 285 | 284,2023-02-08,CUST284,Male,43,Clothing,4,50,200 286 | 285,2023-08-15,CUST285,Female,31,Electronics,1,25,25 287 | 286,2023-10-09,CUST286,Male,55,Electronics,2,25,50 288 | 287,2023-02-20,CUST287,Male,54,Clothing,4,25,100 289 | 288,2023-01-26,CUST288,Male,28,Clothing,4,30,120 290 | 289,2023-11-30,CUST289,Male,53,Electronics,2,30,60 291 | 290,2023-10-04,CUST290,Female,30,Beauty,2,300,600 292 | 291,2023-01-08,CUST291,Male,60,Clothing,2,300,600 293 | 292,2023-02-17,CUST292,Male,20,Beauty,4,300,1200 294 | 293,2023-05-02,CUST293,Male,50,Electronics,3,30,90 295 | 294,2023-03-27,CUST294,Female,23,Clothing,3,30,90 296 | 295,2023-07-28,CUST295,Female,27,Beauty,3,300,900 297 | 296,2023-09-06,CUST296,Female,22,Clothing,4,300,1200 298 | 297,2023-09-04,CUST297,Female,40,Electronics,2,500,1000 299 | 298,2023-04-20,CUST298,Male,27,Beauty,4,300,1200 300 | 299,2023-07-25,CUST299,Male,61,Electronics,2,500,1000 301 | 300,2023-01-31,CUST300,Female,19,Electronics,4,50,200 302 | 301,2023-03-26,CUST301,Male,30,Clothing,4,30,120 303 | 302,2023-07-14,CUST302,Male,57,Beauty,2,300,600 304 | 303,2023-01-02,CUST303,Male,19,Electronics,3,30,90 305 | 304,2023-07-19,CUST304,Female,37,Electronics,2,30,60 306 | 305,2023-05-16,CUST305,Female,18,Beauty,1,30,30 307 | 306,2023-08-21,CUST306,Male,54,Electronics,1,50,50 308 | 307,2023-05-27,CUST307,Female,26,Electronics,2,25,50 309 | 308,2023-08-05,CUST308,Female,34,Beauty,4,300,1200 310 | 309,2023-12-23,CUST309,Female,26,Beauty,1,25,25 311 | 310,2023-10-12,CUST310,Female,28,Beauty,1,25,25 312 | 311,2023-12-05,CUST311,Female,32,Beauty,4,25,100 313 | 312,2023-09-07,CUST312,Male,41,Clothing,4,30,120 314 | 313,2023-03-21,CUST313,Female,55,Beauty,3,500,1500 315 | 314,2023-04-08,CUST314,Male,52,Clothing,4,30,120 316 | 315,2023-06-01,CUST315,Male,47,Clothing,2,30,60 317 | 316,2023-04-22,CUST316,Female,48,Clothing,2,25,50 318 | 317,2023-01-30,CUST317,Male,22,Electronics,3,30,90 319 | 318,2023-10-24,CUST318,Male,61,Clothing,1,25,25 320 | 319,2023-10-05,CUST319,Male,31,Clothing,1,500,500 321 | 320,2023-02-01,CUST320,Female,28,Electronics,4,300,1200 322 | 321,2023-06-10,CUST321,Female,26,Electronics,2,25,50 323 | 322,2023-01-30,CUST322,Male,51,Electronics,1,500,500 324 | 323,2023-01-26,CUST323,Female,29,Beauty,3,300,900 325 | 324,2023-10-27,CUST324,Female,52,Electronics,3,50,150 326 | 325,2023-09-02,CUST325,Female,52,Electronics,2,25,50 327 | 326,2023-09-15,CUST326,Female,18,Clothing,3,25,75 328 | 327,2023-09-29,CUST327,Male,57,Electronics,3,50,150 329 | 328,2023-03-22,CUST328,Male,39,Beauty,2,50,100 330 | 329,2023-01-30,CUST329,Female,46,Electronics,4,25,100 331 | 330,2023-09-18,CUST330,Female,25,Beauty,4,50,200 332 | 331,2023-02-11,CUST331,Male,28,Electronics,3,30,90 333 | 332,2023-04-06,CUST332,Male,58,Electronics,4,300,1200 334 | 333,2023-02-05,CUST333,Female,54,Electronics,4,300,1200 335 | 334,2023-11-01,CUST334,Male,31,Electronics,3,300,900 336 | 335,2023-02-04,CUST335,Female,47,Beauty,4,30,120 337 | 336,2023-12-12,CUST336,Female,52,Beauty,3,50,150 338 | 337,2023-05-01,CUST337,Male,38,Clothing,1,500,500 339 | 338,2023-07-26,CUST338,Male,54,Beauty,2,50,100 340 | 339,2023-03-03,CUST339,Female,22,Electronics,2,25,50 341 | 340,2023-10-19,CUST340,Female,36,Clothing,4,300,1200 342 | 341,2023-05-07,CUST341,Male,31,Clothing,4,50,200 343 | 342,2023-10-24,CUST342,Female,43,Clothing,4,500,2000 344 | 343,2023-11-01,CUST343,Male,21,Electronics,2,25,50 345 | 344,2023-01-21,CUST344,Female,42,Beauty,1,30,30 346 | 345,2023-11-14,CUST345,Male,62,Electronics,1,30,30 347 | 346,2023-02-11,CUST346,Male,59,Clothing,2,500,1000 348 | 347,2023-08-03,CUST347,Male,42,Electronics,1,25,25 349 | 348,2023-12-03,CUST348,Female,35,Electronics,2,300,600 350 | 349,2023-10-26,CUST349,Female,57,Beauty,1,50,50 351 | 350,2023-10-17,CUST350,Male,25,Beauty,3,25,75 352 | 351,2023-09-25,CUST351,Female,56,Clothing,3,30,90 353 | 352,2023-06-11,CUST352,Male,57,Electronics,2,500,1000 354 | 353,2023-05-14,CUST353,Male,31,Electronics,1,500,500 355 | 354,2023-04-15,CUST354,Female,49,Beauty,4,50,200 356 | 355,2023-12-09,CUST355,Female,55,Electronics,1,500,500 357 | 356,2023-06-10,CUST356,Male,50,Electronics,3,500,1500 358 | 357,2023-05-03,CUST357,Female,40,Electronics,3,25,75 359 | 358,2023-05-16,CUST358,Female,32,Beauty,1,300,300 360 | 359,2023-07-22,CUST359,Male,50,Clothing,1,50,50 361 | 360,2023-03-09,CUST360,Male,42,Clothing,4,25,100 362 | 361,2023-12-10,CUST361,Female,34,Electronics,4,300,1200 363 | 362,2023-11-27,CUST362,Male,50,Clothing,1,25,25 364 | 363,2023-06-03,CUST363,Male,64,Beauty,1,25,25 365 | 364,2023-08-23,CUST364,Female,19,Beauty,1,500,500 366 | 365,2023-06-11,CUST365,Male,31,Clothing,1,300,300 367 | 366,2023-02-07,CUST366,Male,57,Clothing,2,50,100 368 | 367,2023-01-05,CUST367,Female,57,Electronics,1,50,50 369 | 368,2023-08-23,CUST368,Female,56,Clothing,4,300,1200 370 | 369,2023-11-15,CUST369,Male,23,Electronics,3,500,1500 371 | 370,2023-10-16,CUST370,Male,23,Electronics,2,30,60 372 | 371,2023-02-21,CUST371,Female,20,Beauty,1,25,25 373 | 372,2023-02-07,CUST372,Female,24,Beauty,3,500,1500 374 | 373,2023-10-03,CUST373,Female,25,Beauty,2,300,600 375 | 374,2023-04-20,CUST374,Female,59,Beauty,3,25,75 376 | 375,2023-09-17,CUST375,Male,32,Clothing,1,50,50 377 | 376,2023-05-16,CUST376,Female,64,Beauty,1,30,30 378 | 377,2023-03-09,CUST377,Female,46,Clothing,4,50,200 379 | 378,2023-06-28,CUST378,Male,50,Beauty,1,300,300 380 | 379,2023-02-05,CUST379,Female,47,Clothing,1,25,25 381 | 380,2023-05-06,CUST380,Male,56,Electronics,2,300,600 382 | 381,2023-07-09,CUST381,Female,44,Clothing,4,25,100 383 | 382,2023-05-26,CUST382,Female,53,Clothing,2,500,1000 384 | 383,2023-03-22,CUST383,Female,46,Beauty,3,30,90 385 | 384,2023-08-13,CUST384,Male,55,Clothing,1,500,500 386 | 385,2023-10-06,CUST385,Male,50,Electronics,3,500,1500 387 | 386,2023-12-27,CUST386,Female,54,Electronics,2,300,600 388 | 387,2023-06-04,CUST387,Male,44,Beauty,1,30,30 389 | 388,2023-11-10,CUST388,Male,50,Electronics,1,25,25 390 | 389,2023-12-01,CUST389,Male,21,Clothing,2,25,50 391 | 390,2023-09-28,CUST390,Male,39,Electronics,2,50,100 392 | 391,2023-01-05,CUST391,Male,19,Beauty,2,25,50 393 | 392,2023-12-08,CUST392,Male,27,Clothing,2,300,600 394 | 393,2023-10-11,CUST393,Female,22,Beauty,2,500,1000 395 | 394,2023-06-03,CUST394,Female,27,Clothing,1,500,500 396 | 395,2023-12-06,CUST395,Male,50,Electronics,2,500,1000 397 | 396,2023-02-23,CUST396,Female,55,Beauty,1,30,30 398 | 397,2023-03-10,CUST397,Female,30,Beauty,1,25,25 399 | 398,2023-05-16,CUST398,Female,48,Clothing,2,300,600 400 | 399,2023-03-01,CUST399,Female,64,Beauty,2,30,60 401 | 400,2023-02-24,CUST400,Male,53,Clothing,4,50,200 402 | 401,2023-10-11,CUST401,Female,62,Clothing,1,300,300 403 | 402,2023-03-21,CUST402,Female,41,Clothing,2,300,600 404 | 403,2023-05-20,CUST403,Male,32,Clothing,2,300,600 405 | 404,2023-05-25,CUST404,Male,46,Electronics,2,500,1000 406 | 405,2023-11-06,CUST405,Female,25,Clothing,4,300,1200 407 | 406,2023-04-18,CUST406,Female,22,Beauty,4,25,100 408 | 407,2023-06-25,CUST407,Female,46,Electronics,3,300,900 409 | 408,2023-04-15,CUST408,Female,64,Beauty,1,500,500 410 | 409,2023-12-18,CUST409,Female,21,Electronics,3,300,900 411 | 410,2023-11-21,CUST410,Female,29,Clothing,2,50,100 412 | 411,2023-05-16,CUST411,Male,62,Electronics,4,50,200 413 | 412,2023-09-16,CUST412,Female,19,Electronics,4,500,2000 414 | 413,2023-09-08,CUST413,Female,44,Beauty,3,25,75 415 | 414,2023-05-09,CUST414,Male,48,Beauty,4,25,100 416 | 415,2023-01-27,CUST415,Male,53,Clothing,2,30,60 417 | 416,2023-02-17,CUST416,Male,53,Electronics,4,500,2000 418 | 417,2023-11-21,CUST417,Male,43,Electronics,3,300,900 419 | 418,2023-08-05,CUST418,Female,60,Electronics,2,500,1000 420 | 419,2023-05-22,CUST419,Female,44,Clothing,3,30,90 421 | 420,2023-01-23,CUST420,Female,22,Clothing,4,500,2000 422 | 421,2023-01-02,CUST421,Female,37,Clothing,3,500,1500 423 | 422,2023-06-20,CUST422,Female,28,Clothing,3,30,90 424 | 423,2023-03-08,CUST423,Female,27,Clothing,1,25,25 425 | 424,2023-11-23,CUST424,Male,57,Beauty,4,300,1200 426 | 425,2023-05-15,CUST425,Female,55,Electronics,4,30,120 427 | 426,2023-03-24,CUST426,Male,23,Electronics,3,50,150 428 | 427,2023-08-15,CUST427,Male,25,Electronics,1,25,25 429 | 428,2023-10-10,CUST428,Female,40,Electronics,4,50,200 430 | 429,2023-12-28,CUST429,Male,64,Electronics,2,25,50 431 | 430,2023-08-07,CUST430,Female,43,Electronics,3,300,900 432 | 431,2023-10-15,CUST431,Male,63,Electronics,4,300,1200 433 | 432,2023-01-05,CUST432,Female,60,Electronics,2,500,1000 434 | 433,2023-02-27,CUST433,Male,29,Beauty,4,50,200 435 | 434,2023-02-08,CUST434,Female,43,Electronics,2,25,50 436 | 435,2023-12-20,CUST435,Female,30,Beauty,3,300,900 437 | 436,2023-03-18,CUST436,Female,57,Clothing,4,30,120 438 | 437,2023-10-07,CUST437,Female,35,Electronics,4,300,1200 439 | 438,2023-01-19,CUST438,Female,42,Clothing,1,30,30 440 | 439,2023-07-09,CUST439,Male,50,Clothing,3,25,75 441 | 440,2023-10-26,CUST440,Male,64,Clothing,2,300,600 442 | 441,2023-10-10,CUST441,Male,57,Beauty,4,300,1200 443 | 442,2023-03-17,CUST442,Female,60,Clothing,4,25,100 444 | 443,2023-08-09,CUST443,Male,29,Clothing,2,300,600 445 | 444,2023-03-07,CUST444,Female,61,Clothing,3,30,90 446 | 445,2023-01-22,CUST445,Female,53,Electronics,1,300,300 447 | 446,2023-06-07,CUST446,Male,21,Electronics,1,50,50 448 | 447,2023-07-06,CUST447,Male,22,Beauty,4,500,2000 449 | 448,2023-01-21,CUST448,Female,54,Beauty,2,30,60 450 | 449,2023-07-03,CUST449,Male,25,Electronics,4,50,200 451 | 450,2023-04-18,CUST450,Female,59,Beauty,2,25,50 452 | 451,2023-12-16,CUST451,Female,45,Electronics,1,30,30 453 | 452,2023-05-08,CUST452,Female,48,Clothing,3,500,1500 454 | 453,2023-12-08,CUST453,Female,26,Clothing,2,500,1000 455 | 454,2023-02-22,CUST454,Female,46,Beauty,1,25,25 456 | 455,2023-07-01,CUST455,Male,31,Electronics,4,25,100 457 | 456,2023-10-14,CUST456,Male,57,Electronics,2,30,60 458 | 457,2023-07-28,CUST457,Female,58,Beauty,3,300,900 459 | 458,2023-11-14,CUST458,Female,39,Electronics,4,25,100 460 | 459,2023-03-21,CUST459,Male,28,Clothing,4,300,1200 461 | 460,2023-05-02,CUST460,Male,40,Beauty,1,50,50 462 | 461,2023-03-25,CUST461,Female,18,Beauty,2,500,1000 463 | 462,2023-04-01,CUST462,Male,63,Electronics,4,300,1200 464 | 463,2023-07-31,CUST463,Female,54,Beauty,3,500,1500 465 | 464,2023-01-13,CUST464,Male,38,Electronics,2,300,600 466 | 465,2023-04-02,CUST465,Female,43,Electronics,3,50,150 467 | 466,2023-06-20,CUST466,Male,63,Electronics,4,25,100 468 | 467,2023-07-30,CUST467,Female,53,Electronics,3,50,150 469 | 468,2023-12-09,CUST468,Male,40,Electronics,1,25,25 470 | 469,2023-05-08,CUST469,Male,18,Beauty,3,25,75 471 | 470,2023-05-17,CUST470,Female,57,Clothing,2,500,1000 472 | 471,2023-03-23,CUST471,Male,32,Clothing,3,50,150 473 | 472,2023-12-26,CUST472,Female,38,Beauty,3,300,900 474 | 473,2023-02-25,CUST473,Male,64,Beauty,1,50,50 475 | 474,2023-07-15,CUST474,Female,26,Clothing,3,500,1500 476 | 475,2023-01-20,CUST475,Male,26,Clothing,3,25,75 477 | 476,2023-08-29,CUST476,Female,27,Clothing,4,500,2000 478 | 477,2023-04-24,CUST477,Male,43,Clothing,4,30,120 479 | 478,2023-04-13,CUST478,Female,58,Clothing,2,30,60 480 | 479,2023-08-24,CUST479,Male,52,Electronics,4,300,1200 481 | 480,2023-06-29,CUST480,Female,42,Beauty,4,500,2000 482 | 481,2023-06-06,CUST481,Female,43,Electronics,4,300,1200 483 | 482,2023-04-27,CUST482,Female,28,Clothing,4,300,1200 484 | 483,2023-04-25,CUST483,Male,55,Clothing,1,30,30 485 | 484,2023-01-13,CUST484,Female,19,Clothing,4,300,1200 486 | 485,2023-12-04,CUST485,Male,24,Electronics,1,30,30 487 | 486,2023-04-09,CUST486,Female,35,Electronics,1,25,25 488 | 487,2023-07-24,CUST487,Male,44,Clothing,4,500,2000 489 | 488,2023-06-18,CUST488,Female,51,Electronics,3,300,900 490 | 489,2023-05-23,CUST489,Male,44,Electronics,1,30,30 491 | 490,2023-02-05,CUST490,Male,34,Clothing,3,50,150 492 | 491,2023-05-23,CUST491,Female,60,Electronics,3,300,900 493 | 492,2023-06-29,CUST492,Male,61,Beauty,4,25,100 494 | 493,2023-11-25,CUST493,Male,41,Beauty,2,25,50 495 | 494,2023-09-18,CUST494,Female,42,Beauty,4,50,200 496 | 495,2023-07-24,CUST495,Male,24,Beauty,2,30,60 497 | 496,2023-12-14,CUST496,Male,23,Clothing,2,300,600 498 | 497,2023-10-02,CUST497,Male,41,Clothing,4,30,120 499 | 498,2023-06-19,CUST498,Female,50,Clothing,4,25,100 500 | 499,2023-01-15,CUST499,Male,46,Beauty,2,30,60 501 | 500,2023-03-01,CUST500,Female,60,Beauty,4,25,100 502 | 501,2023-05-14,CUST501,Male,39,Electronics,2,30,60 503 | 502,2023-04-02,CUST502,Male,43,Electronics,3,50,150 504 | 503,2023-10-25,CUST503,Male,45,Beauty,4,500,2000 505 | 504,2023-05-16,CUST504,Female,38,Beauty,3,50,150 506 | 505,2023-01-20,CUST505,Male,24,Beauty,1,50,50 507 | 506,2023-02-25,CUST506,Male,34,Beauty,3,500,1500 508 | 507,2023-11-02,CUST507,Female,37,Electronics,3,500,1500 509 | 508,2023-08-11,CUST508,Male,58,Beauty,2,300,600 510 | 509,2023-06-26,CUST509,Female,37,Electronics,3,300,900 511 | 510,2023-06-10,CUST510,Female,39,Beauty,4,50,200 512 | 511,2023-08-12,CUST511,Male,45,Beauty,2,50,100 513 | 512,2023-11-07,CUST512,Female,57,Beauty,1,25,25 514 | 513,2023-09-19,CUST513,Male,24,Electronics,4,25,100 515 | 514,2023-03-01,CUST514,Female,18,Electronics,1,300,300 516 | 515,2023-07-17,CUST515,Female,49,Clothing,3,300,900 517 | 516,2023-10-23,CUST516,Male,30,Beauty,4,25,100 518 | 517,2023-04-08,CUST517,Female,47,Clothing,4,25,100 519 | 518,2023-05-11,CUST518,Female,40,Clothing,1,30,30 520 | 519,2023-01-23,CUST519,Female,36,Electronics,4,30,120 521 | 520,2023-12-29,CUST520,Female,49,Electronics,4,25,100 522 | 521,2023-08-12,CUST521,Female,47,Clothing,4,30,120 523 | 522,2023-01-01,CUST522,Male,46,Beauty,3,500,1500 524 | 523,2023-09-24,CUST523,Female,62,Electronics,1,300,300 525 | 524,2023-10-03,CUST524,Male,46,Beauty,4,300,1200 526 | 525,2023-12-18,CUST525,Female,47,Beauty,2,25,50 527 | 526,2023-12-10,CUST526,Male,33,Clothing,2,50,100 528 | 527,2023-04-11,CUST527,Male,57,Clothing,2,25,50 529 | 528,2023-07-06,CUST528,Female,36,Clothing,2,30,60 530 | 529,2023-08-09,CUST529,Female,35,Clothing,3,50,150 531 | 530,2023-02-05,CUST530,Female,18,Electronics,4,30,120 532 | 531,2023-12-07,CUST531,Male,31,Electronics,1,500,500 533 | 532,2023-06-19,CUST532,Female,64,Clothing,4,30,120 534 | 533,2023-11-16,CUST533,Male,19,Electronics,3,500,1500 535 | 534,2023-06-10,CUST534,Male,45,Clothing,2,500,1000 536 | 535,2023-12-06,CUST535,Male,47,Beauty,3,30,90 537 | 536,2023-03-05,CUST536,Female,55,Beauty,4,30,120 538 | 537,2023-06-03,CUST537,Female,21,Beauty,1,500,500 539 | 538,2023-09-17,CUST538,Male,18,Clothing,3,50,150 540 | 539,2023-06-08,CUST539,Male,25,Beauty,1,500,500 541 | 540,2023-12-08,CUST540,Female,46,Electronics,3,300,900 542 | 541,2023-07-29,CUST541,Male,56,Beauty,1,500,500 543 | 542,2023-06-17,CUST542,Female,20,Beauty,1,50,50 544 | 543,2023-07-26,CUST543,Male,49,Beauty,2,300,600 545 | 544,2023-12-23,CUST544,Female,27,Electronics,1,25,25 546 | 545,2023-06-01,CUST545,Male,27,Clothing,2,25,50 547 | 546,2023-10-11,CUST546,Female,36,Electronics,4,50,200 548 | 547,2023-03-07,CUST547,Male,63,Clothing,4,500,2000 549 | 548,2023-04-09,CUST548,Female,51,Clothing,2,30,60 550 | 549,2023-08-04,CUST549,Female,50,Beauty,2,50,100 551 | 550,2023-12-07,CUST550,Male,40,Clothing,3,300,900 552 | 551,2023-07-14,CUST551,Male,45,Electronics,3,300,900 553 | 552,2023-12-13,CUST552,Female,49,Electronics,3,25,75 554 | 553,2023-03-31,CUST553,Male,24,Clothing,4,300,1200 555 | 554,2023-11-12,CUST554,Female,46,Beauty,3,50,150 556 | 555,2023-10-19,CUST555,Male,25,Beauty,1,300,300 557 | 556,2023-06-04,CUST556,Female,18,Electronics,1,50,50 558 | 557,2023-07-27,CUST557,Female,20,Beauty,3,30,90 559 | 558,2023-10-08,CUST558,Female,41,Clothing,1,25,25 560 | 559,2023-01-01,CUST559,Female,40,Clothing,4,300,1200 561 | 560,2023-06-05,CUST560,Female,25,Electronics,1,50,50 562 | 561,2023-05-27,CUST561,Female,64,Clothing,4,500,2000 563 | 562,2023-04-18,CUST562,Male,54,Electronics,2,25,50 564 | 563,2023-08-09,CUST563,Male,20,Clothing,2,30,60 565 | 564,2023-10-24,CUST564,Male,50,Electronics,2,50,100 566 | 565,2023-11-07,CUST565,Female,45,Beauty,2,30,60 567 | 566,2023-12-02,CUST566,Female,64,Clothing,1,30,30 568 | 567,2023-06-14,CUST567,Female,25,Clothing,3,300,900 569 | 568,2023-08-27,CUST568,Female,51,Electronics,1,300,300 570 | 569,2023-08-15,CUST569,Male,52,Electronics,4,50,200 571 | 570,2023-08-15,CUST570,Male,49,Clothing,1,500,500 572 | 571,2023-12-12,CUST571,Female,41,Electronics,1,50,50 573 | 572,2023-04-20,CUST572,Male,31,Clothing,4,500,2000 574 | 573,2023-09-19,CUST573,Male,49,Beauty,2,30,60 575 | 574,2023-08-31,CUST574,Female,63,Electronics,2,25,50 576 | 575,2023-03-28,CUST575,Male,60,Clothing,2,50,100 577 | 576,2023-12-04,CUST576,Female,33,Beauty,3,50,150 578 | 577,2023-02-13,CUST577,Male,21,Beauty,4,500,2000 579 | 578,2023-05-26,CUST578,Female,54,Clothing,4,30,120 580 | 579,2023-09-21,CUST579,Female,38,Electronics,1,30,30 581 | 580,2023-12-06,CUST580,Female,31,Clothing,3,500,1500 582 | 581,2023-11-21,CUST581,Female,48,Beauty,2,30,60 583 | 582,2023-11-14,CUST582,Male,35,Clothing,3,300,900 584 | 583,2023-06-21,CUST583,Female,24,Electronics,4,25,100 585 | 584,2023-02-17,CUST584,Female,27,Beauty,4,50,200 586 | 585,2023-05-01,CUST585,Female,24,Clothing,1,25,25 587 | 586,2023-12-11,CUST586,Male,50,Electronics,1,50,50 588 | 587,2023-06-08,CUST587,Female,40,Beauty,4,300,1200 589 | 588,2023-04-26,CUST588,Male,38,Electronics,2,30,60 590 | 589,2023-04-12,CUST589,Female,36,Beauty,2,500,1000 591 | 590,2023-03-17,CUST590,Male,36,Clothing,3,300,900 592 | 591,2023-01-13,CUST591,Male,53,Electronics,4,25,100 593 | 592,2023-01-24,CUST592,Female,46,Beauty,4,500,2000 594 | 593,2023-05-06,CUST593,Male,35,Electronics,2,30,60 595 | 594,2023-09-01,CUST594,Female,19,Electronics,2,300,600 596 | 595,2023-11-09,CUST595,Female,18,Clothing,4,500,2000 597 | 596,2023-02-07,CUST596,Female,64,Electronics,1,300,300 598 | 597,2023-08-22,CUST597,Male,22,Beauty,4,300,1200 599 | 598,2023-08-01,CUST598,Male,37,Beauty,4,30,120 600 | 599,2023-11-19,CUST599,Female,28,Beauty,2,50,100 601 | 600,2023-10-22,CUST600,Female,59,Beauty,2,500,1000 602 | 601,2023-04-10,CUST601,Male,19,Clothing,1,30,30 603 | 602,2023-12-23,CUST602,Female,20,Electronics,1,300,300 604 | 603,2023-07-16,CUST603,Female,40,Clothing,3,30,90 605 | 604,2023-09-11,CUST604,Female,29,Electronics,4,50,200 606 | 605,2023-07-24,CUST605,Male,37,Electronics,2,500,1000 607 | 606,2023-05-05,CUST606,Male,22,Electronics,1,50,50 608 | 607,2023-03-17,CUST607,Male,54,Clothing,3,25,75 609 | 608,2023-12-02,CUST608,Female,55,Electronics,3,500,1500 610 | 609,2023-12-19,CUST609,Female,47,Clothing,2,50,100 611 | 610,2023-01-03,CUST610,Female,26,Beauty,2,300,600 612 | 611,2023-02-24,CUST611,Male,51,Beauty,3,500,1500 613 | 612,2023-08-06,CUST612,Female,61,Electronics,1,500,500 614 | 613,2023-04-23,CUST613,Female,52,Clothing,3,30,90 615 | 614,2023-04-01,CUST614,Female,39,Beauty,4,300,1200 616 | 615,2023-12-23,CUST615,Female,61,Clothing,4,25,100 617 | 616,2023-09-23,CUST616,Male,41,Clothing,2,50,100 618 | 617,2023-08-26,CUST617,Male,34,Electronics,1,30,30 619 | 618,2023-01-26,CUST618,Female,27,Beauty,1,50,50 620 | 619,2023-10-13,CUST619,Male,47,Electronics,4,25,100 621 | 620,2023-05-08,CUST620,Male,63,Electronics,3,25,75 622 | 621,2023-03-04,CUST621,Female,40,Beauty,2,500,1000 623 | 622,2023-08-22,CUST622,Female,49,Beauty,3,25,75 624 | 623,2023-03-10,CUST623,Male,34,Clothing,3,50,150 625 | 624,2023-08-26,CUST624,Female,34,Beauty,3,300,900 626 | 625,2023-12-08,CUST625,Male,31,Clothing,1,300,300 627 | 626,2023-09-29,CUST626,Female,26,Clothing,4,500,2000 628 | 627,2023-10-14,CUST627,Male,57,Clothing,1,50,50 629 | 628,2023-11-01,CUST628,Female,19,Beauty,4,50,200 630 | 629,2023-06-12,CUST629,Male,62,Electronics,2,25,50 631 | 630,2023-08-15,CUST630,Male,42,Clothing,2,50,100 632 | 631,2023-11-10,CUST631,Male,56,Electronics,3,30,90 633 | 632,2023-09-16,CUST632,Female,26,Electronics,4,25,100 634 | 633,2023-08-07,CUST633,Male,39,Beauty,4,30,120 635 | 634,2023-10-08,CUST634,Male,60,Electronics,4,500,2000 636 | 635,2023-08-17,CUST635,Female,63,Electronics,3,300,900 637 | 636,2023-03-23,CUST636,Female,21,Beauty,3,500,1500 638 | 637,2023-09-01,CUST637,Male,43,Clothing,2,300,600 639 | 638,2023-08-19,CUST638,Male,46,Electronics,1,500,500 640 | 639,2023-05-13,CUST639,Female,62,Beauty,4,50,200 641 | 640,2023-05-07,CUST640,Female,51,Electronics,4,30,120 642 | 641,2023-11-23,CUST641,Female,40,Electronics,1,300,300 643 | 642,2023-05-22,CUST642,Female,54,Clothing,4,25,100 644 | 643,2023-09-24,CUST643,Female,28,Electronics,3,30,90 645 | 644,2023-09-06,CUST644,Male,23,Beauty,3,25,75 646 | 645,2023-11-17,CUST645,Female,35,Electronics,4,30,120 647 | 646,2023-05-03,CUST646,Male,38,Clothing,3,30,90 648 | 647,2023-05-21,CUST647,Male,59,Clothing,3,500,1500 649 | 648,2023-08-14,CUST648,Male,53,Beauty,4,300,1200 650 | 649,2023-02-09,CUST649,Female,58,Clothing,2,300,600 651 | 650,2024-01-01,CUST650,Male,55,Electronics,1,30,30 652 | 651,2023-05-27,CUST651,Male,51,Clothing,3,50,150 653 | 652,2023-05-01,CUST652,Female,34,Beauty,2,50,100 654 | 653,2023-05-20,CUST653,Male,54,Clothing,3,25,75 655 | 654,2023-06-21,CUST654,Male,42,Clothing,3,25,75 656 | 655,2023-06-13,CUST655,Female,55,Clothing,1,500,500 657 | 656,2023-10-04,CUST656,Male,29,Beauty,3,30,90 658 | 657,2023-02-11,CUST657,Male,40,Clothing,1,25,25 659 | 658,2023-03-12,CUST658,Male,59,Clothing,1,25,25 660 | 659,2023-03-19,CUST659,Female,39,Electronics,1,30,30 661 | 660,2023-04-29,CUST660,Female,38,Beauty,2,500,1000 662 | 661,2023-07-16,CUST661,Female,44,Clothing,4,25,100 663 | 662,2023-12-22,CUST662,Male,48,Beauty,2,500,1000 664 | 663,2023-03-20,CUST663,Male,23,Clothing,4,300,1200 665 | 664,2023-12-28,CUST664,Female,44,Clothing,4,500,2000 666 | 665,2023-04-20,CUST665,Male,57,Clothing,1,50,50 667 | 666,2023-02-02,CUST666,Male,51,Electronics,3,50,150 668 | 667,2023-08-01,CUST667,Female,29,Electronics,1,500,500 669 | 668,2023-07-28,CUST668,Female,62,Electronics,3,50,150 670 | 669,2023-06-19,CUST669,Male,24,Beauty,4,300,1200 671 | 670,2023-10-05,CUST670,Male,27,Beauty,1,30,30 672 | 671,2023-08-27,CUST671,Male,62,Electronics,3,50,150 673 | 672,2023-08-01,CUST672,Female,34,Beauty,2,50,100 674 | 673,2023-02-01,CUST673,Female,43,Clothing,3,500,1500 675 | 674,2023-04-16,CUST674,Female,38,Clothing,1,300,300 676 | 675,2023-08-04,CUST675,Female,45,Clothing,2,30,60 677 | 676,2023-07-19,CUST676,Male,63,Electronics,3,500,1500 678 | 677,2023-10-27,CUST677,Female,19,Beauty,3,500,1500 679 | 678,2023-12-23,CUST678,Female,60,Electronics,3,300,900 680 | 679,2023-01-11,CUST679,Female,18,Beauty,3,30,90 681 | 680,2023-10-22,CUST680,Female,53,Clothing,3,300,900 682 | 681,2023-07-14,CUST681,Female,43,Electronics,2,30,60 683 | 682,2023-09-02,CUST682,Male,46,Beauty,4,300,1200 684 | 683,2023-01-04,CUST683,Male,38,Beauty,2,500,1000 685 | 684,2023-06-30,CUST684,Female,28,Clothing,2,500,1000 686 | 685,2023-06-02,CUST685,Male,57,Electronics,2,25,50 687 | 686,2023-07-19,CUST686,Female,28,Electronics,4,50,200 688 | 687,2023-08-03,CUST687,Female,53,Electronics,1,300,300 689 | 688,2023-10-03,CUST688,Male,56,Clothing,4,25,100 690 | 689,2023-10-07,CUST689,Male,57,Electronics,2,50,100 691 | 690,2023-11-05,CUST690,Female,52,Clothing,3,300,900 692 | 691,2023-04-23,CUST691,Female,51,Clothing,3,30,90 693 | 692,2023-09-07,CUST692,Female,64,Clothing,2,50,100 694 | 693,2023-04-23,CUST693,Male,41,Beauty,3,500,1500 695 | 694,2023-05-20,CUST694,Female,39,Electronics,2,25,50 696 | 695,2023-08-12,CUST695,Female,22,Electronics,3,50,150 697 | 696,2023-09-06,CUST696,Female,50,Clothing,4,50,200 698 | 697,2023-01-15,CUST697,Male,53,Clothing,1,500,500 699 | 698,2023-07-19,CUST698,Female,64,Electronics,1,300,300 700 | 699,2023-06-22,CUST699,Female,37,Clothing,4,30,120 701 | 700,2023-12-09,CUST700,Male,36,Electronics,4,500,2000 702 | 701,2023-12-14,CUST701,Female,52,Beauty,2,30,60 703 | 702,2023-07-27,CUST702,Female,60,Clothing,2,300,600 704 | 703,2023-03-26,CUST703,Male,34,Electronics,2,50,100 705 | 704,2023-08-28,CUST704,Female,62,Clothing,3,30,90 706 | 705,2023-03-07,CUST705,Male,60,Electronics,2,25,50 707 | 706,2023-11-15,CUST706,Male,51,Electronics,4,25,100 708 | 707,2023-10-01,CUST707,Female,26,Clothing,1,500,500 709 | 708,2023-01-14,CUST708,Female,43,Beauty,3,300,900 710 | 709,2023-07-21,CUST709,Female,19,Electronics,2,500,1000 711 | 710,2023-10-31,CUST710,Female,26,Electronics,3,500,1500 712 | 711,2023-10-16,CUST711,Male,26,Electronics,3,500,1500 713 | 712,2023-12-06,CUST712,Female,57,Beauty,2,25,50 714 | 713,2023-01-14,CUST713,Male,34,Beauty,3,25,75 715 | 714,2023-02-12,CUST714,Female,18,Clothing,1,500,500 716 | 715,2023-11-26,CUST715,Female,42,Beauty,4,25,100 717 | 716,2023-08-08,CUST716,Female,60,Clothing,4,300,1200 718 | 717,2023-03-11,CUST717,Male,57,Clothing,1,500,500 719 | 718,2023-08-25,CUST718,Female,59,Beauty,3,25,75 720 | 719,2023-04-04,CUST719,Female,42,Clothing,2,30,60 721 | 720,2023-01-26,CUST720,Female,56,Beauty,3,500,1500 722 | 721,2023-05-14,CUST721,Female,52,Clothing,1,500,500 723 | 722,2023-07-14,CUST722,Male,20,Beauty,3,300,900 724 | 723,2023-06-17,CUST723,Female,54,Beauty,4,50,200 725 | 724,2023-04-19,CUST724,Male,61,Clothing,3,50,150 726 | 725,2023-08-21,CUST725,Male,61,Electronics,1,300,300 727 | 726,2023-06-17,CUST726,Male,47,Clothing,4,300,1200 728 | 727,2023-06-22,CUST727,Male,55,Beauty,3,300,900 729 | 728,2023-07-14,CUST728,Male,51,Electronics,3,50,150 730 | 729,2023-05-23,CUST729,Male,29,Clothing,4,300,1200 731 | 730,2023-08-04,CUST730,Female,36,Clothing,2,25,50 732 | 731,2023-05-10,CUST731,Male,54,Clothing,4,500,2000 733 | 732,2023-02-11,CUST732,Male,61,Electronics,2,500,1000 734 | 733,2023-08-29,CUST733,Male,34,Beauty,1,30,30 735 | 734,2023-01-10,CUST734,Female,27,Clothing,1,30,30 736 | 735,2023-10-04,CUST735,Female,64,Clothing,4,500,2000 737 | 736,2023-01-27,CUST736,Male,29,Clothing,4,25,100 738 | 737,2023-06-29,CUST737,Female,33,Clothing,1,50,50 739 | 738,2023-04-25,CUST738,Male,41,Clothing,2,50,100 740 | 739,2023-11-29,CUST739,Male,36,Beauty,1,25,25 741 | 740,2023-02-05,CUST740,Female,25,Beauty,4,50,200 742 | 741,2023-11-30,CUST741,Male,48,Clothing,1,300,300 743 | 742,2023-01-21,CUST742,Female,38,Electronics,4,500,2000 744 | 743,2023-01-16,CUST743,Female,34,Beauty,4,500,2000 745 | 744,2023-05-07,CUST744,Male,40,Electronics,1,25,25 746 | 745,2023-04-13,CUST745,Male,54,Beauty,2,50,100 747 | 746,2023-01-11,CUST746,Female,33,Clothing,3,30,90 748 | 747,2023-11-15,CUST747,Male,23,Beauty,1,30,30 749 | 748,2023-03-20,CUST748,Male,25,Clothing,3,50,150 750 | 749,2023-05-03,CUST749,Male,42,Beauty,1,30,30 751 | 750,2023-03-06,CUST750,Female,35,Clothing,3,25,75 752 | 751,2023-08-31,CUST751,Female,42,Clothing,2,25,50 753 | 752,2023-12-09,CUST752,Male,29,Clothing,2,50,100 754 | 753,2023-02-28,CUST753,Female,32,Clothing,1,30,30 755 | 754,2023-10-16,CUST754,Female,43,Electronics,4,25,100 756 | 755,2023-04-22,CUST755,Female,58,Clothing,3,25,75 757 | 756,2023-08-27,CUST756,Female,62,Electronics,4,300,1200 758 | 757,2023-12-25,CUST757,Female,43,Electronics,4,300,1200 759 | 758,2023-05-12,CUST758,Male,64,Clothing,4,25,100 760 | 759,2023-07-08,CUST759,Male,49,Electronics,2,50,100 761 | 760,2023-03-27,CUST760,Male,27,Beauty,1,500,500 762 | 761,2023-11-07,CUST761,Female,33,Clothing,1,500,500 763 | 762,2023-11-07,CUST762,Female,24,Electronics,2,25,50 764 | 763,2023-02-28,CUST763,Male,34,Clothing,2,25,50 765 | 764,2023-03-25,CUST764,Female,40,Clothing,1,25,25 766 | 765,2023-06-09,CUST765,Male,43,Clothing,4,50,200 767 | 766,2023-02-25,CUST766,Male,38,Electronics,3,300,900 768 | 767,2023-10-24,CUST767,Male,39,Beauty,3,25,75 769 | 768,2023-01-14,CUST768,Female,24,Beauty,3,25,75 770 | 769,2023-06-09,CUST769,Female,31,Electronics,4,30,120 771 | 770,2023-10-22,CUST770,Male,32,Clothing,1,50,50 772 | 771,2023-12-13,CUST771,Male,24,Electronics,2,25,50 773 | 772,2023-07-12,CUST772,Male,26,Electronics,1,30,30 774 | 773,2023-07-23,CUST773,Male,25,Electronics,4,500,2000 775 | 774,2023-04-12,CUST774,Female,40,Clothing,2,25,50 776 | 775,2023-02-08,CUST775,Female,46,Electronics,4,25,100 777 | 776,2023-10-31,CUST776,Male,35,Clothing,3,30,90 778 | 777,2023-12-20,CUST777,Male,48,Electronics,3,50,150 779 | 778,2023-11-18,CUST778,Female,47,Beauty,4,25,100 780 | 779,2023-05-05,CUST779,Female,56,Electronics,2,500,1000 781 | 780,2023-02-22,CUST780,Male,52,Electronics,2,25,50 782 | 781,2023-12-23,CUST781,Male,35,Beauty,1,500,500 783 | 782,2023-06-04,CUST782,Male,59,Clothing,3,300,900 784 | 783,2023-12-17,CUST783,Female,56,Clothing,1,300,300 785 | 784,2023-11-04,CUST784,Female,34,Electronics,1,500,500 786 | 785,2023-03-03,CUST785,Female,31,Beauty,4,50,200 787 | 786,2023-10-17,CUST786,Male,48,Clothing,4,25,100 788 | 787,2023-01-22,CUST787,Male,41,Electronics,1,25,25 789 | 788,2023-06-27,CUST788,Female,52,Beauty,3,300,900 790 | 789,2023-09-30,CUST789,Female,61,Clothing,4,500,2000 791 | 790,2023-08-08,CUST790,Male,62,Clothing,1,25,25 792 | 791,2023-12-05,CUST791,Female,51,Beauty,1,25,25 793 | 792,2023-07-09,CUST792,Female,20,Beauty,1,50,50 794 | 793,2023-02-05,CUST793,Male,54,Beauty,1,30,30 795 | 794,2023-09-17,CUST794,Female,60,Beauty,1,300,300 796 | 795,2023-11-28,CUST795,Male,57,Electronics,1,300,300 797 | 796,2023-06-24,CUST796,Male,43,Beauty,4,30,120 798 | 797,2023-01-07,CUST797,Male,40,Clothing,3,25,75 799 | 798,2023-08-04,CUST798,Male,61,Clothing,1,50,50 800 | 799,2023-09-08,CUST799,Male,56,Electronics,2,50,100 801 | 800,2023-02-24,CUST800,Male,32,Clothing,4,300,1200 802 | 801,2023-08-10,CUST801,Male,21,Clothing,4,50,200 803 | 802,2023-07-05,CUST802,Female,46,Beauty,1,30,30 804 | 803,2023-11-22,CUST803,Male,39,Clothing,4,25,100 805 | 804,2023-08-24,CUST804,Male,42,Electronics,1,30,30 806 | 805,2023-12-29,CUST805,Female,30,Beauty,3,500,1500 807 | 806,2023-03-20,CUST806,Female,35,Beauty,3,300,900 808 | 807,2023-08-11,CUST807,Female,50,Electronics,4,50,200 809 | 808,2023-04-01,CUST808,Male,33,Beauty,4,500,2000 810 | 809,2023-09-25,CUST809,Female,62,Beauty,2,50,100 811 | 810,2023-11-30,CUST810,Male,59,Electronics,4,25,100 812 | 811,2023-05-19,CUST811,Male,61,Beauty,2,25,50 813 | 812,2023-11-12,CUST812,Male,19,Electronics,3,25,75 814 | 813,2023-10-03,CUST813,Male,52,Electronics,3,50,150 815 | 814,2023-09-05,CUST814,Female,59,Clothing,1,500,500 816 | 815,2023-08-27,CUST815,Female,51,Clothing,3,25,75 817 | 816,2023-08-12,CUST816,Male,47,Beauty,2,500,1000 818 | 817,2023-10-31,CUST817,Male,30,Beauty,4,50,200 819 | 818,2023-05-18,CUST818,Male,30,Electronics,1,500,500 820 | 819,2023-06-15,CUST819,Female,35,Beauty,2,50,100 821 | 820,2023-05-06,CUST820,Male,49,Electronics,4,50,200 822 | 821,2023-02-14,CUST821,Male,49,Electronics,1,300,300 823 | 822,2023-05-23,CUST822,Female,52,Beauty,3,50,150 824 | 823,2023-08-19,CUST823,Female,56,Electronics,2,50,100 825 | 824,2023-05-05,CUST824,Male,63,Clothing,4,30,120 826 | 825,2023-08-26,CUST825,Female,46,Beauty,1,25,25 827 | 826,2023-10-19,CUST826,Female,46,Clothing,1,300,300 828 | 827,2023-11-09,CUST827,Male,61,Beauty,3,300,900 829 | 828,2023-12-09,CUST828,Female,33,Electronics,4,300,1200 830 | 829,2023-07-14,CUST829,Male,61,Beauty,3,30,90 831 | 830,2023-06-22,CUST830,Female,64,Clothing,3,50,150 832 | 831,2023-01-15,CUST831,Male,27,Electronics,4,25,100 833 | 832,2023-09-11,CUST832,Male,47,Beauty,4,500,2000 834 | 833,2023-06-16,CUST833,Male,42,Beauty,4,50,200 835 | 834,2023-04-04,CUST834,Female,56,Beauty,2,30,60 836 | 835,2023-09-07,CUST835,Male,37,Clothing,4,50,200 837 | 836,2023-04-19,CUST836,Female,22,Clothing,1,50,50 838 | 837,2023-07-01,CUST837,Male,18,Beauty,3,30,90 839 | 838,2023-05-13,CUST838,Male,47,Electronics,2,300,600 840 | 839,2023-06-24,CUST839,Female,20,Electronics,4,300,1200 841 | 840,2023-05-24,CUST840,Male,62,Clothing,2,25,50 842 | 841,2023-11-02,CUST841,Male,31,Electronics,4,25,100 843 | 842,2023-12-26,CUST842,Female,47,Clothing,2,300,600 844 | 843,2023-05-22,CUST843,Male,21,Beauty,3,500,1500 845 | 844,2023-10-12,CUST844,Male,35,Clothing,3,50,150 846 | 845,2023-01-06,CUST845,Male,54,Clothing,1,500,500 847 | 846,2023-09-22,CUST846,Male,42,Beauty,1,50,50 848 | 847,2023-04-08,CUST847,Female,18,Electronics,4,300,1200 849 | 848,2023-02-13,CUST848,Female,63,Clothing,3,25,75 850 | 849,2023-05-04,CUST849,Male,32,Clothing,2,25,50 851 | 850,2023-07-28,CUST850,Female,26,Beauty,2,500,1000 852 | 851,2023-09-08,CUST851,Male,32,Electronics,2,25,50 853 | 852,2023-10-12,CUST852,Female,41,Clothing,1,300,300 854 | 853,2023-05-04,CUST853,Male,21,Beauty,2,500,1000 855 | 854,2023-12-20,CUST854,Male,29,Clothing,1,50,50 856 | 855,2023-09-01,CUST855,Male,54,Beauty,1,25,25 857 | 856,2023-11-27,CUST856,Male,54,Electronics,4,30,120 858 | 857,2023-12-31,CUST857,Male,60,Electronics,2,25,50 859 | 858,2023-09-09,CUST858,Male,23,Electronics,2,50,100 860 | 859,2023-08-18,CUST859,Female,56,Electronics,3,500,1500 861 | 860,2023-01-09,CUST860,Male,63,Clothing,4,50,200 862 | 861,2023-02-17,CUST861,Female,41,Clothing,3,30,90 863 | 862,2023-05-31,CUST862,Male,28,Electronics,4,300,1200 864 | 863,2023-04-24,CUST863,Female,30,Electronics,2,25,50 865 | 864,2023-07-27,CUST864,Female,51,Electronics,1,500,500 866 | 865,2023-12-21,CUST865,Female,42,Clothing,1,300,300 867 | 866,2023-05-05,CUST866,Male,24,Electronics,1,50,50 868 | 867,2023-06-06,CUST867,Male,21,Electronics,1,500,500 869 | 868,2023-12-06,CUST868,Female,25,Electronics,1,300,300 870 | 869,2023-10-25,CUST869,Male,37,Beauty,3,500,1500 871 | 870,2023-07-08,CUST870,Female,46,Electronics,4,30,120 872 | 871,2023-08-31,CUST871,Male,62,Beauty,2,30,60 873 | 872,2023-10-11,CUST872,Female,63,Beauty,3,25,75 874 | 873,2023-09-29,CUST873,Female,27,Electronics,4,25,100 875 | 874,2023-06-26,CUST874,Male,60,Beauty,1,30,30 876 | 875,2023-08-06,CUST875,Female,51,Electronics,4,500,2000 877 | 876,2023-10-09,CUST876,Male,43,Clothing,4,30,120 878 | 877,2023-06-19,CUST877,Female,58,Clothing,1,25,25 879 | 878,2023-06-30,CUST878,Female,20,Clothing,1,30,30 880 | 879,2023-12-26,CUST879,Male,23,Clothing,1,30,30 881 | 880,2023-08-21,CUST880,Male,22,Beauty,2,500,1000 882 | 881,2023-05-19,CUST881,Male,22,Electronics,1,300,300 883 | 882,2023-06-06,CUST882,Female,64,Electronics,2,25,50 884 | 883,2023-05-09,CUST883,Male,40,Electronics,1,500,500 885 | 884,2023-04-29,CUST884,Female,26,Clothing,2,30,60 886 | 885,2023-03-03,CUST885,Female,52,Clothing,4,30,120 887 | 886,2023-04-09,CUST886,Male,37,Electronics,3,300,900 888 | 887,2023-06-11,CUST887,Male,59,Clothing,4,25,100 889 | 888,2023-03-03,CUST888,Female,52,Electronics,4,25,100 890 | 889,2023-10-02,CUST889,Female,35,Electronics,1,50,50 891 | 890,2023-12-20,CUST890,Male,34,Electronics,2,25,50 892 | 891,2023-04-05,CUST891,Male,41,Electronics,3,300,900 893 | 892,2023-04-09,CUST892,Male,20,Electronics,1,50,50 894 | 893,2023-04-21,CUST893,Male,49,Electronics,1,50,50 895 | 894,2023-09-05,CUST894,Male,52,Electronics,1,30,30 896 | 895,2023-05-22,CUST895,Female,55,Clothing,4,30,120 897 | 896,2023-10-29,CUST896,Female,30,Electronics,2,25,50 898 | 897,2023-09-26,CUST897,Female,64,Electronics,2,50,100 899 | 898,2023-11-02,CUST898,Female,42,Clothing,3,30,90 900 | 899,2023-05-25,CUST899,Male,26,Clothing,2,300,600 901 | 900,2023-02-21,CUST900,Male,21,Clothing,2,30,60 902 | 901,2023-04-10,CUST901,Male,31,Electronics,1,30,30 903 | 902,2023-06-01,CUST902,Female,54,Beauty,1,50,50 904 | 903,2023-04-27,CUST903,Female,51,Beauty,4,50,200 905 | 904,2023-07-04,CUST904,Male,28,Clothing,1,500,500 906 | 905,2023-04-02,CUST905,Male,58,Beauty,1,300,300 907 | 906,2023-06-04,CUST906,Female,20,Clothing,1,50,50 908 | 907,2023-01-08,CUST907,Female,45,Electronics,1,25,25 909 | 908,2023-12-29,CUST908,Male,46,Beauty,4,300,1200 910 | 909,2023-10-01,CUST909,Male,26,Electronics,1,300,300 911 | 910,2023-03-06,CUST910,Female,20,Beauty,3,50,150 912 | 911,2023-05-21,CUST911,Male,42,Electronics,3,300,900 913 | 912,2023-01-24,CUST912,Male,51,Beauty,3,50,150 914 | 913,2023-01-28,CUST913,Male,29,Electronics,3,30,90 915 | 914,2023-10-11,CUST914,Female,59,Electronics,1,500,500 916 | 915,2023-05-30,CUST915,Female,26,Beauty,3,30,90 917 | 916,2023-12-24,CUST916,Female,32,Electronics,1,50,50 918 | 917,2023-03-06,CUST917,Female,57,Electronics,4,50,200 919 | 918,2023-11-23,CUST918,Female,42,Electronics,3,30,90 920 | 919,2023-09-09,CUST919,Female,22,Beauty,2,25,50 921 | 920,2023-02-22,CUST920,Female,28,Beauty,3,25,75 922 | 921,2023-01-07,CUST921,Male,51,Electronics,3,25,75 923 | 922,2023-10-21,CUST922,Male,41,Electronics,1,50,50 924 | 923,2023-05-26,CUST923,Male,32,Beauty,3,300,900 925 | 924,2023-08-29,CUST924,Male,55,Beauty,2,50,100 926 | 925,2023-09-03,CUST925,Male,25,Electronics,1,300,300 927 | 926,2023-08-14,CUST926,Male,22,Electronics,1,30,30 928 | 927,2023-06-24,CUST927,Male,43,Electronics,4,500,2000 929 | 928,2023-04-05,CUST928,Female,35,Clothing,4,300,1200 930 | 929,2023-01-27,CUST929,Female,23,Beauty,3,25,75 931 | 930,2023-05-10,CUST930,Male,54,Clothing,4,50,200 932 | 931,2023-09-02,CUST931,Male,30,Beauty,4,30,120 933 | 932,2023-02-28,CUST932,Female,45,Beauty,4,25,100 934 | 933,2023-02-03,CUST933,Male,22,Beauty,1,30,30 935 | 934,2023-07-25,CUST934,Male,30,Beauty,1,500,500 936 | 935,2023-09-09,CUST935,Female,34,Beauty,1,50,50 937 | 936,2023-02-07,CUST936,Male,57,Beauty,4,50,200 938 | 937,2023-10-23,CUST937,Female,62,Beauty,1,500,500 939 | 938,2023-11-19,CUST938,Male,49,Clothing,4,50,200 940 | 939,2023-12-18,CUST939,Female,46,Electronics,1,300,300 941 | 940,2023-01-28,CUST940,Female,20,Electronics,1,30,30 942 | 941,2023-03-19,CUST941,Female,57,Clothing,2,25,50 943 | 942,2023-03-18,CUST942,Male,51,Clothing,3,500,1500 944 | 943,2023-10-16,CUST943,Female,57,Clothing,4,300,1200 945 | 944,2023-06-05,CUST944,Male,44,Clothing,2,25,50 946 | 945,2023-02-13,CUST945,Male,30,Beauty,1,25,25 947 | 946,2023-05-08,CUST946,Male,62,Electronics,4,500,2000 948 | 947,2023-03-02,CUST947,Male,50,Beauty,1,300,300 949 | 948,2023-10-13,CUST948,Female,23,Electronics,3,25,75 950 | 949,2023-08-02,CUST949,Female,41,Electronics,2,25,50 951 | 950,2023-11-07,CUST950,Male,36,Clothing,3,300,900 952 | 951,2023-11-02,CUST951,Male,33,Beauty,2,50,100 953 | 952,2023-11-13,CUST952,Female,57,Clothing,1,25,25 954 | 953,2023-04-26,CUST953,Male,45,Beauty,3,30,90 955 | 954,2023-09-25,CUST954,Female,50,Electronics,3,300,900 956 | 955,2023-07-14,CUST955,Male,58,Clothing,1,25,25 957 | 956,2023-08-19,CUST956,Male,30,Clothing,3,500,1500 958 | 957,2023-08-15,CUST957,Female,60,Electronics,4,30,120 959 | 958,2023-06-02,CUST958,Male,62,Electronics,2,25,50 960 | 959,2023-10-29,CUST959,Female,42,Electronics,2,30,60 961 | 960,2023-08-08,CUST960,Male,59,Clothing,2,30,60 962 | 961,2023-06-06,CUST961,Male,53,Beauty,4,50,200 963 | 962,2023-10-19,CUST962,Male,44,Clothing,2,30,60 964 | 963,2023-11-14,CUST963,Female,55,Beauty,1,50,50 965 | 964,2023-01-31,CUST964,Male,24,Clothing,3,300,900 966 | 965,2023-11-09,CUST965,Male,22,Clothing,4,50,200 967 | 966,2023-02-20,CUST966,Male,60,Electronics,2,500,1000 968 | 967,2023-04-17,CUST967,Male,62,Beauty,1,25,25 969 | 968,2023-11-17,CUST968,Female,48,Clothing,3,300,900 970 | 969,2023-04-19,CUST969,Female,40,Clothing,3,300,900 971 | 970,2023-05-16,CUST970,Male,59,Electronics,4,500,2000 972 | 971,2023-12-05,CUST971,Female,27,Electronics,4,50,200 973 | 972,2023-02-11,CUST972,Male,49,Beauty,4,25,100 974 | 973,2023-03-22,CUST973,Male,60,Clothing,1,50,50 975 | 974,2023-05-03,CUST974,Male,47,Beauty,1,30,30 976 | 975,2023-03-30,CUST975,Female,56,Clothing,4,50,200 977 | 976,2023-10-10,CUST976,Female,48,Beauty,2,300,600 978 | 977,2023-02-08,CUST977,Female,35,Electronics,3,25,75 979 | 978,2023-03-22,CUST978,Female,53,Clothing,3,50,150 980 | 979,2023-01-02,CUST979,Female,19,Beauty,1,25,25 981 | 980,2023-07-29,CUST980,Female,31,Electronics,3,25,75 982 | 981,2023-08-19,CUST981,Female,30,Electronics,2,30,60 983 | 982,2023-12-19,CUST982,Female,46,Beauty,3,30,90 984 | 983,2023-11-01,CUST983,Female,29,Clothing,1,300,300 985 | 984,2023-08-29,CUST984,Male,56,Clothing,1,500,500 986 | 985,2023-05-30,CUST985,Female,19,Electronics,2,25,50 987 | 986,2023-01-17,CUST986,Female,49,Clothing,2,500,1000 988 | 987,2023-04-29,CUST987,Female,30,Clothing,3,300,900 989 | 988,2023-05-28,CUST988,Female,63,Clothing,3,25,75 990 | 989,2023-12-28,CUST989,Female,44,Electronics,1,25,25 991 | 990,2023-05-25,CUST990,Female,58,Beauty,2,500,1000 992 | 991,2023-12-26,CUST991,Female,34,Clothing,2,50,100 993 | 992,2023-08-21,CUST992,Female,57,Electronics,2,30,60 994 | 993,2023-02-06,CUST993,Female,48,Electronics,3,50,150 995 | 994,2023-12-18,CUST994,Female,51,Beauty,2,500,1000 996 | 995,2023-04-30,CUST995,Female,41,Clothing,1,30,30 997 | 996,2023-05-16,CUST996,Male,62,Clothing,1,50,50 998 | 997,2023-11-17,CUST997,Male,52,Beauty,3,30,90 999 | 998,2023-10-29,CUST998,Female,23,Beauty,4,25,100 1000 | 999,2023-12-05,CUST999,Female,36,Electronics,3,50,150 1001 | 1000,2023-04-12,CUST1000,Male,47,Electronics,4,30,120 1002 | --------------------------------------------------------------------------------