exploratory data analysis
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Python's Applications in the Profession of Data Science
Abstract: Because of its ease of use, adaptability, and huge ecosystem of libraries, Python has become one of the most influential programming languages in the field of data science. Python is highly valued for its straightforward and versatile nature. This study delves into its various uses in data science, including tasks like data preprocessing, exploratory data analysis (EDA), statistical modeling, machine learning, and creating visualizations. Libraries like Pandas and NumPy make …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 23–30 Read article
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Analysis of World Population Growth Using Python
Abstract: In this research work, we studied data analysis using the Python programming language. The fundamental steps in data analysis, such as cleansing, converting, and modelling of data is briefly explained in this study. In order to come up with good results, data analysis is required. Python has been used by us for data analysis. This language is interactive, interpreted, and follows an object-oriented programming paradigm. It is open source and …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 15–20 Read article
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Optimizing Customer Care Centre Performance: A Data Analytics Approach
Abstract: Customer care centres are essential in today's competitive corporate environment for ensuring client loyalty and satisfaction. By utilizing data analytics approaches, one may gain important insights regarding performance overall, operational effectiveness, and customer interactions. Data analytics encompasses the analysing, interpretation, and extraction of valuable insights from data to aid decision-making and address intricate issues. Call centre analytics is the process of gathering and evaluating call data to assist companies in …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 34–49 Read article
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A Data-driven Approach to Sales Analysis
Abstract: Decisions made using data from digital sources are said to be data-driven when they are analysed and interpreted. Across many sectors, a data-driven approach is an effective technique for gaining insights, making wise choices, and guiding corporate strategy. This study covers the concept of data analytics in sales analysis of bakery and mess. It involves evaluating diverse types of information, including sales data, customer preferences, production costs, and supplier details. …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 1, 2024 · pp. 29–41 Read article