Customer dataset csv. csv') Distribution of Customer Ages.

Customer dataset csv flights-1m. csv │ ├── Customer_churn_raw. The second one, subset_tickets. csv: 14. Regards Data about customers. Start download View. customer_unique_id: unique identifier for each Classification dataset. README. Something went wrong and this page This dataset contains detailed information about various banking transactions and customer data. The code to bring the data into the notebook environment and create a Pandas DataFrame will be added to the cell. The mo Predict telecom customers likely to churn with 80% accuracy by analyzing 7000+ customers’ data; identified best model out of KNN, Naïve Bayes, Logistic, and SVM Contribute to pawarbi/datasets development by creating an account on GitHub. Full Screen. chiapudding Upload customer_support_tickets. This dataset CSV; Last Updated: 2021-04 You signed in with another tab or window. It has been compiled to aid in financial analysis, customer behavior studies, and predictive modeling. Datasets used in Plotly examples and documentation - plotly/datasets. u) on diverse product categories. csv to a local drive on your computer. Learn more about bidirectional Unicode characters. Dataset Description: The 'RetailCustomerSegmentation' dataset comprises customer profiles for a retail company, which have been clustered into different segments based on their demographics and shopping behavior. - suvchr105/Predict-Customer-Churn Skip to content Navigation Menu This analysis will help marketing team to target customers with some strategies. 95 MB. Each data table includes 1,000 rows of data that you can use to build Pivot Tables, Dashboards, Power Query automations, or practice your Excel formula skills. Let's create a histogram to visualize the age distribution of Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. kmeans_result. Perfect for validating your software's CSV handling making them suitable for small to medium-sized datasets. File too large to display, you can Download or view these example CSV datasets below. Tags generative-ai + 3. The data comes in two versions in this project: The first one, all_tickets. Customer acquistion value of the company by analysing previous performance datasets - Customer-acquistion/customer_acquisition_data. 7 KB: Papers Citing this Dataset Mall_Customers. Kaggle is a treasure trove of datasets that can be leveraged for customer segmentation, a crucial aspect of marketing and business strategy. customer_segmentation. The methodology involves: Pattern Recognition: Identifying and reproducing patterns seen in real-world customer data. CSV Content Preview: Dataset card Viewer Files Files and versions Community main kaggle-customer-service / customer_support_tickets. Write better code with AI Security. xlsx and . You can use techniques like ANOVA to conduct a multivariate analysis and implement modeling algorithms, such as the decision tree or random forest, to predict whether a customer will likely churn. Navigation Menu Customer Stories Partners Executive Insights Open Source CustomerLoyaltyProgram. Customer lifetime value (CLTV) Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Age and sex by ethnic group (grouped total responses), for census night population counts, 2006, This repository contains code for analyzing the "Mall_Customers" dataset, which includes information about customers in a mall. This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. The dataset includes order details, anonymized customer information, product specifics, and financial metrics. This project involves analyzing and visualizing an e-commerce dataset to gain insights into product trends, customer behavior, and sales strategies. Always test your software with a "worst-case scenario" amount of sample data, to get an accurate sense of its performance in the real world. You can get this dataset from In this project, we analyze a dataset of mall customers to understand their characteristics, preferences, and behaviors. Leveraging on Unsupervised Learning Techniques (K-Means and Hierarchical Clustering Implementation) to Perform Market Basket Analysis: Implementing Customer Segmentation Concepts to score a custom Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. You can download sample CSV files here for testing purposes. In this installment of MarTech 101, we look at the basics of customer data. Predict customer churn using machine learning models with the Telco Customer Churn dataset. The dataset is downloaded from UCI machine learning repository. csv: a. Exploring Market Basket Analysis in Istanbul Retail Data # Assuming the dataset is already cleaned and available # This example assumes the DataFrame is named 'customer_data' customer_data = pd. It includes the annual spending in monetary units(m. pptx: PowerPoint presentation summarizing the findings and insights. There is no programming or data science knowledge needed. The data set includes information about: Customers who left within the last month — the column is called Churn. Reload to refresh your session. csv. With records spanning a significant timeframe, this dataset provides a robust foundation for exploring sales trends, understanding consumer choices, and deriving Contribute to aishwaryamate/Datasets development by creating an account on GitHub. 0) license. rows. Croissant + 1. Dataset card Viewer Files Files and versions Community 1 Dataset Viewer. The results are visualized, and the dataset is saved for further exploration in Power BI. This project addresses the issue an e-commerce firm is facing- should the firm focus on its mobile app or website ? - customer-database/Ecommerce Customers. Uncover hidden patterns, This dataset contains 9 separated CSV files as follows: 1. This repository features a synthetic dataset for educational purposes, covering customer behavior and purchasing patterns on an e-commerce platform. It includes the Wholesale customers data. The mo Contribute to DennisKimt/datasets development by creating an account on GitHub. Click Insert to code and choose pandas DataFrame. Blame. This dataset is IBM Sample Data Sets that I founded at Kaggle. Pakistan faces floods and drought more often than anyone can believe in different parts of the country year after year, and the cycle seems to continue infinitely. Mosly using Python Faker package. Contribute to DennisKimt/datasets development by creating an account on GitHub. history contribute delete No virus 3. The dataset includes basic information such as invoice numbers, customer IDs, age, gender, payment methods, product categories, quantity, price, order dates, and mall locations. 13 lines (13 loc) · 663 Bytes. This dataset provides detailed data on online transactions made by customers from various countries. Something Brazilian E-Commerce Public Dataset by Olist. Journey into Consumer Insights and Retail Evolution with Synthetic Data I’ve built extensive spreadsheet sample data on a variety of real-world topics. Something went wrong and this page Exploratory data analysis on customer. An easy tool to edit CSV files online is our CSV Editor. In addition, it contains a notebook to set up a connection to a remote Microsoft SQL Server. Created by Gretel AI, it’s ideal for learning and research in data science and machine learning. Download the Customer Data file, and then extract CustomerData. Sign in Product Wholesale customers data. 000 samples and 13 unbalanced distinct tickets categories. Run the cell and you will see the first five rows of Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. Flexible Data Ingestion. Data Cleaning: Processes for handling null values, correcting data formats, and identifying outliers. Libraries: Datasets. Software Testing and Development: Utilized Synthetic Dataset of Customer Transactions. This is fake data — not actual customers or businesses. Show Gist options. 7c89014 8 months ago. Each row represents a unique transaction or customer insight. mtcars. Something went wrong and this page crashed! If the issue persists, it's likely a Complete customer churn dataset for telecom industry as made available by IBM. CSV is a generic flat file f The datasets are generated using random values. Auto If you encounter any difficulties or require further assistance, our dedicated customer support team is available during Contribute to Iznia/Restaurant-Customer-Satisfaction-Analysis development by creating an account on GitHub. 10. - haasitha/Customer_segmen Data Generation: Python scripts used to generate realistic e-commerce data. This dataset is licensed under a Creative Commons Attribution 4. 000 samples and 5 balanced distinct tickets categories. raw Copy download link. csv at master · rajtulluri/Olist-business-analysis olist_customers_dataset. Customer Sentiment Dataset: Opinions, Ratings, and Sources. csv │ └── churn_final. Datasets used in Plotly examples and documentation - datasets/telco-customer-churn-by-IBM. xlsx; The tables named Customer Analysis and Targets are joined on a combination of State and Vehicle Class. - sagarlakshmipathy/UK- Customer support ticket dataset. python data-science machine-learning ai random-forest classification churn-prediction customer-analytics customer-churn. Each data table includes 1,000 rows of data that you can Download free sample CSV files to test data import and export functionalities. Contribute to JeffryAugustinus/Dataset development by creating an account on GitHub. history contribute delete No virus 622 kB. Something went wrong and this page Analysis of company's ideal customers. A Machine Learning model to predict customer churn for a subscription- based service or business. We’re on a journey to advance and democratize artificial intelligence through open source and open science. Explore and run machine learning code with Kaggle Notebooks | Using data from E-Commerce Data Customer demographics and transactions data from an Indian Bank. Focused customer retention programs. 0. File too large to display, you can Dive into the realm of customer segmentation analysis with Python! This tutorial guides you through mall customer segmentation using clustering techniques in machine learning. This report analyzes various aspects of the dataset to extract meaningful insights. Code. customer_id: unique identifier for each customer. Explore Customer Shopping Habits, Churn, and Purchase Patterns 🛒 E-commerce Customer Data For Behavior Analysis | Kaggle Explore Customer Shopping Habits, Churn, and Purchase Patterns 💳🛒 Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. OK, Got it. rds: Saved K-means clustering results. Top. Navigation Menu Customer Stories Partners Executive Insights Open Source GitHub Sponsors. csv) into your preferred programming environment or Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. This is another telecom churn dataset, with columns detailing customer behavior, usage, and statistics. Donated on 3/30/2014. csv('Mall_Customers. Schema Design: Logical star schema with fact and dimension tables for in-depth analysis. 7 MB. Orange Telecom Customer Churn Dataset. The dataset has gender, customer id, age, annual income, and spending score Customer Segmentation is the process of division of customer base into several groups of individuals that share a similarity in different ways that are relevant to marketing such as gender, age, interests, and miscellaneous spending habits. Flights 1m. Customer segmentation is one of unsupervised learning’s most important applications. The dataset is provided in CSV format, containing 10,000 rows and 15 columns. Motor Trends Car Road Tests dataset. ,Elgin,OR,97827,USA,(503) 555-6874,(503) 555-2376 This notebook focuses on predicting customer churn using machine learning. We will start by understanding its definition and types. Explore topics Improve this page Add a description, image, and links to the customer-data topic page so that developers can more easily learn about it. Includes EDA, feature engineering, and Random Forest classification. Size: 10K - 100K. This blog post is here to help. Something went wrong and this page These free data sets are great public sources of information for those looking to learn how to analyze data and boost their data literacy skills. age: age of the customer. Skip to content. Develop your data analytics skillset with our free data sets using real-world data, from flight delays and movie ratings to shark attacks and UFO sightings Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. 17. Something went wrong and this page crashed! If the issue persists, it's likely a problem on Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. Unexpected token < Datasets used in Plotly examples and documentation - datasets/26k-consumer-complaints. csv ├── data_preprocessing │ ├── CustomerChurnPrediction. new_customer. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. Contribute to shanemcandrewai/olist development by creating an account on GitHub. Customer Analysis: Customer_analysis. Contribute to Apress/learn-pyspark development by creating an account on GitHub. Something went wrong and this page crashed! If the issue Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side. The dataset includes the following columns: ‍ data = read. Employing clustering algorithms to identify the numerous customer subgroups enables businesses to target specific consumer groupings. MT cars. I’ve built extensive spreadsheet sample data on a variety of real-world topics. csv at master · plotly/datasets Datasets used in Plotly examples and documentation - plotly/datasets Skip to content Upload customer_churn_dataset. To review, open the file in an editor that Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Customer conversion: Percentage of customers converted from acquisition efforts. fe6da79 verified about 10 hours ago. Task 2: Import the CSV file. b. Preview. In this study, we will explore four popular clustering algorithms: K-means, Hierarchical Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. Synthetic Data Generation: Creating data points for each feature based on recognized patterns. CSV Parquet TSV JSON. File metadata and controls. Each data set is available to download for free and comes in . You signed in with another tab or window. - FloZewi/E-commerce-Data-Analysis Skip to content Explore and run machine learning code with Kaggle Notebooks | Using data from Mall Customer Segmentation Data. Feel free to add more rows to suit your specific use case or dataset requirements. You signed out in another tab or window. Show hidden characters Customer ID Name Surname Gender A free test data generator and API mocking tool - Mockaroo lets you create custom CSV, JSON, SQL, and Excel datasets to test and demo your software. csv, has about 3. It covers data preprocessing, EDA, and building models like Logistic Regression, Decision Trees, and Random Forest. Iris plant species data set. Complete customer churn dataset for telecom industry as made available by IBM. Starbucks customer dataset. annual_income: annual income of Discover datasets around the world! Datasets; Contribute Donate New; Link External; About Us. Perfect for validating your software's CSV handling capabilities. Exploratory Data Analysis (EDA): Insights into sales trends, customer behavior, and product performance. Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side. This page gives you a dataset that stores information about fictional customers of an imaginary enterprise for the purposes of learning, practicing, or testing software. A dashboard is also created to provide interactive insights. The SuperStore dataset comprises a comprehensive sales record from a superstore, containing 9,994 entries across 19 distinct fields. All gists Back to GitHub Sign in Sign up GaneshSparkz / Mall_Customers. Learn more. The analysis is performed using Python with pandas, seaborn, and scikit-learn libraries. As the decisioning architect, import the CustomerData. Navigation Menu Toggle navigation. csv to the Customer Profile Designer in the Customer Decision Hub. csv, has about 50. csv at master · plotly/datasets. HUNGC,Hungry Coyote Import Store,Yoshi Latimer,Sales Representative,City Center Plaza 516 Main St. Below are some of the most notable datasets available on Kaggle that can help you A detialed analysis on the customers, products, orders and shipments of the Brazilian E-commerce giant Olist. For this round, we will analyze customer data for American cities. It includes demographics, browsing and purchase history, and product reviews. It is a classification problem. Sign in Product GitHub Copilot. csv. md: Project overview and instructions. The data set refers to clients of a wholesale distributor. Contribute to chrisayuni/dataset development by creating an account on GitHub. You can use this dataset to analyze customer behavior, product performance, sales trends, and more. gender: gender of the customer (male or female). csv: Dataset used for customer segmentation. Source Code for 'Learn PySpark' by Pramod Singh. to_csv('rfm_asia. The dataset consists of variables Fresh, Milk, Grocery, Frozen, Detergents_paper, Delicatessen, Channel, Region Segment 2: What is the Gender of Customers in Different Cities? Now, let us dive a bit deeper into our customer dataset and analyze how customers of different gender groups are divided between cities. About the dataset Imagine a telecommunications provider has segmented its customer base by service usage patterns, categorizing the customers into four groups. sentiment-analysis tensorflow eda gensim bert amazon-review-dataset text-embeddings. Customer Lifetime Value (CLTV): Average value of a customer throughout their lifetime. csv at main · Santhoshhariharan The wholesale customer dataset refers to clients of a wholesale distributor. Statistical area 1 dataset for 2018 Census – web page includes dataset in Excel and CSV format, footnotes, and other supporting information. The dataset was generated using machine learning algorithms that simulate typical customer interactions with an e-commerce platform. To learn more about the provided wholesale customer dataset; To reduce the number of dimensions our dataset has using PCA; Scale our dataset using both standard and minmax scaling; Apply the KMeans clustering technique to the dataset and see which set of modified features performs better Customer Success Use Cases. Churn Prediction and Prevention. Raw. The categories and intents have been selected from Bitext's collection of 20 vertical-specific datasets, covering the The Customer Support on Twitter dataset is a large, modern corpus of tweets and replies to aid innovation in natural language understanding and conversational models, and for study of modern customer support practices and impact. 9. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. By applying data analysis techniques and clustering algorithms, Load the dataset file (dataset. The survey questions assess satisfaction with overall customer service CSV; Last Updated: 2023-04-10; Rainfall in Pakistan. The sample data we’ve provided is designed to be a foundation for building your own healthcare insurance claim datasets. The dataset used in this project is mall-customers-data. It contains 200 rows and 5 columns: customer_id: unique ID assigned to the customer. The data will be in CSV, JSON, XLSX (Excel), and XML This project addresses the issue an e-commerce firm is facing- should the firm focus on its mobile app or website ? - araj2/customer-database Spend data for profile analysis. 0 International (CC BY 4. Who We Are; Citation Metadata; Contact Information; Login. This will allow them to target the The Olist Brazilian E-Commerce Dataset on Kaggle is a comprehensive collection of data from Olist, an online retail platform in Brazil. csv; Targets: Customer_analysis_targets. Size: 1K - 10K. License: cc-by-4. read_csv('cleaned_customer_data. The primary goal of this project is to analyze customer behavior and preferences based on the dataset to gain insights into the following: Spending Patterns: Understanding how various demographic factors like age and income influence average spending. - Olist-business-analysis/Original data/olist_customers_dataset. Spending Score is something you assign to the customer based on your defined parameters like customer behavior and purchasing data. A reference guide to the 11 segments and This notebook focuses on predicting customer churn using machine learning. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Updated Analysing Amazon customer reviews via Clustering, Visualization and Classification. Something went wrong and this page crashed! If the issue persists, Insights into Customer Behavior and Churn Prediction. csv This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. This project compares the four powerful deep learning models namely, RNN, LSTM, GRU, Bi LSTM and shows that by applying these models, how they achieves excellent result on the customer review dataset. olist_customers_dataset. Customer Satisfaction: Evaluating the correlation between ratings for service, food, and ambiance with overall Choose the Files tab. GitHub Gist: instantly share code, notes, and snippets. With the help of clustering techniques, B2C (Business to customers) companies can identify the several segments of customers that share a similarity in different ways that are relevant to marketing such as gender, age, interests, and miscellaneous spending habits. Full Screen Viewer. Explore trends, patterns, and key metrics to inform strate Skip to content. 1000000. Created February 20, 2022 12:28. Return on Investment (ROI): Percentage return on the investment made in customer acquisition efforts. So, we will head to the Filter option in the menu bar and apply the following Customer_Churn_Analysis/ ├── Model │ ├── images │ ├── Model_building_with_clean_data. Navigation Menu Customer Stories Partners Executive Insights Open Source Orders. This repository allows you to: Get the data Data Science ML. Copy path. The dataset contains 10 columns in Customer & Purchase Analytics using Segmentation, Targeting, Positioning, Marketing Mix, Price Elasticity - SooyeonWon/customer_analytics_fmcg Dataset to explore and use ML Algorithms to make wonderful predictions ! Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Datasets used in Plotly examples and documentation - datasets/diabetes. Download ZIP Sentiment Analysis on the Amazon Reviews Dataset using BERT-based transfer learning approach. Latest commit This analysis was created in Tableau desktop to perform analysis on a publicly available dataset for an UK Bank. File Information File Name: sales_and_customer_insights. The data is Microsoft support ticket dataset. csv file. Wholesale customers. Find and fix customers_dataset. Dataset card Viewer Files Files and versions Community 3 Dataset Viewer. A list of over 34,000 reviews of Amazon products like the Kindle, Fire TV, etc. CSV - 16; JSON - 13; RDF - 13; XML - 13; HTML - 5; ArcGIS GeoServices REST API - 2; GeoJSON - 2; Organization Types City Government - 10; State Government - 7; This dataset provides Customer Service Satisfaction results from the Annual Community Survey. Unsupervised Learning Online Retail Customer Segmentation. Iris. Data: Your data consist of columns like Customer ID, age, gender, annual income and spending score. python clustering sklearn tableau svm-classifier review-analysis amazon Analyze sales data from a supermarket dataset to uncover insights into customer behavior, product performance, and operational efficiency. Languages: English. Navigation Menu Customer Stories Partners Executive Insights Open Source Product Sales Data. This dataset contains information about people visiting the mall. Auto-converted to Parquet API Embed. . Here are some examples of how customer success teams are using the tool: Contribute to YBI-Foundation/Dataset development by creating an account on GitHub. filename. - GitHub - ahsan084/Banking Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side. - amruta33/Customer-Support-on csv. But these datasets for retailers can be hard to come by, since they include personal customer information and business competitive information, which is why not many retailers share this data. Squark’s no code predictive analytics tool puts the power of uncovering customer insights and opportunities in the customer success team’s hands. The 5 variables are CustomerID, Genre(Gender?), Age, Annual Income and Spending score of the customers in a Mall. Thank you for your comment! We provide sample datasets to help you get started, and you can easily extend or modify them as needed. Clustering algorithms are powerful tools in machine learning for grouping similar data points together. Files are provided as CSV. pandas. Contribute to aishwaryamate/Datasets development by creating an account on GitHub. csv We can't make this file beautiful and searchable because it's too large. Download free sample CSV files to test data import and export functionalities. csv') Distribution of Customer Ages. Fund open source developers The ReadME Find CSV files with the latest data from Infoshare and our information releases. This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given. Enhance lending decisions & risk management. Navigation Menu Customer Stories The customer-data topic hasn't been used on any public repositories, yet. csv') The dataset contains 200 rows and 5 columns. R: Script for data preprocessing and customer segmentation using K-means. md ├── data │ ├── Customer_churn_raw. md └── Simulated Dataset of Customer Purchase Behavior. Navigation Menu Explore and run machine learning code with Kaggle Notebooks | Using data from Online Retail II Data Set from ML Repository This repository contains a comprehensive analysis of customer churn in the telecom industry and machine learning models that I used to gain insights into customer behavior and churn patterns. mall_customers. Learn This project leverages KMeans Clustering to transform retail through data-driven customer segmentation, enabling targeted marketing and driving strategic decision-making. Import-ready CSV files, no weird characters, escaped characters, or anything else funky to screw things up. Subset (1) default · 7 Annual spending in monetary units of clients of a wholesale distributor. 1 Million flights including arrival and departure delays. Online Transactions Dataset: Analyze Customer Behavior and Product Performance. Three datasets are available: Customers, This repository contains sample Comma Separated Value (CSV) files. The Customer Analysis table contains a calculated column named Expiry Month that uses a case statement to assign a text string to each value of Month Key: CASE P6-UK-Bank-Customers. A brief explanation of this dataset: Each row represents a customer; each column contains the customer’s attributes described in the column Metadata. If demographic data can be used to predict group membership, the company can customize offers for individual prospective customers. The datasets can be used in any software application compatible with CSV files. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. License: cdla-sharing-1. Curate this topic Add this topic to your repo Loan dataset analysis project: Explore loan data, clean inconsistencies, perform statistical analysis, develop predictive models, identify loan performance factors. csv file from Kaggle using Google Spreadsheets. ipynb │ └── README. Sign in Product Mall_Customers. Mall Customers Dataset. Something went wrong and this page crashed! If the issue Customer Segmentation is one the most important applications of unsupervised learning. You switched accounts on another tab or window. Contribute to dsrscientist/DSData development by creating an account on GitHub. csv formats. Unexpected token < This dataset can be used to train Large Language Models such as GPT, Llama2 and Falcon, both for Fine Tuning and Domain Adaptation. rfm. Total revenue: Sum of revenue from all customers. - m-alqblawi/mall-customers-data-analysis Customer data is the behavioral, demographic and personal information about customers collected by businesses and marketing companies to understand, communicate and engage with customers. Let’s see from our dataset, which other variables we could use to maybe dive deeper to know the cause. csv at master · araj2/customer-database Dataset Description: Our meticulously curated dataset encompasses a wealth of e-commerce sales and order details, offering a panoramic view of transactions, products, and customer preferences. csv', encoding='utf-8', index=False, (An unedited dataset would also include customer names and contact details, which in this case have been omitted for privacy reasons). This dataset offers valuable insights into various aspects CLTV (Customer Lifetime Value) analysis is a method used by businesses to estimate the total value a customer will generate over the entire duration of their relationship with the company. csv File Format: CSV (Comma-Separated Values) Number of Rows: 10,000 Number of Columns: 15 Task 1: Download the CSV file. Select the Telco-Customer-Churn. Customer purchase and call center volume data for a subscription based product. In this machine learning project, K-means clustering, a critical method for clustering unlabeled datasets, will be applied. 32. tpsjd raxz kfgfxnx hical xqbh tjq quz arsttvec kzup xlrd