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Yash Tyagi, Neha Yadav
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- Research Scholar, Research Scholar, MCA, Thakur Institute of Management Studies, Career Development & Research (TIMSCDR), Mumbai, MCA, Thakur Institute of Management Studies, Career Development & Research (TIMSCDR), Mumbai, Maharashtra, Maharashtra, India, India
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Abstract
nIn this paper, 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 paper. 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 comes with a variety of libraries, including MAT plotlib, Seaborn, and Pandas. In this study, we focus primarily on the insights that might be discovered through exploratory data analysis of an existing dataset. The data from the dataset will be analysed graphically using various Python libraries and functions. The “World Population” dataset is used in this analysis to examine and extract different data in both numerical and visual form.
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Keywords: Data Analysis; Exploratory data analysis; Pandas; Seaborn; Matplotlib
n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Programming languages(rtpl)]
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References
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[5] Pokrovskii, Vladimir N. Econodynamics : The Theory of Social Production. Cham, Switzerland, Springer, 2018.
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[8] Arif Z. Building the Future with Supervised Learning: Unleashing the Potential of Labeled Data . Medium. Medium; 2023. Available from: https://medium.com/@mr-zeeshan-arif/building-the-future-with-supervised-learning-unleashing-the-potential-of-labeled-data-3f10624ca48f
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[10] Gerland P, Raftery AE, Ševčíková H, Li N, Gu D, Spoorenberg T, Alkema L, Fosdick BK, Chunn J, Lalic N, Bay G. World population stabilization unlikely this century. Science. 2014 Oct 10;346(6206):234-7.
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| Volume | 11 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 01 | |
| Received | February 29, 2024 | |
| Accepted | April 3, 2024 | |
| Published | April 4, 2024 |
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