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    PYTHON FOR DATA ANALYSIS: A Practical Guide to Manipulating, Cleaning, and Analyzing Data Using Python (2023 Beginner Crash Course)
    PYTHON FOR DATA ANALYSIS: A Practical Guide to Manipulating, Cleaning, and Analyzing Data Using Python (2023 Beginner Crash Course)
    PYTHON FOR DATA ANALYSIS: A Practical Guide to Manipulating, Cleaning, and Analyzing Data Using Python (2023 Beginner Crash Course)
    Ebook78 pages1 hour

    PYTHON FOR DATA ANALYSIS: A Practical Guide to Manipulating, Cleaning, and Analyzing Data Using Python (2023 Beginner Crash Course)

    By Ike Beck

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    About this ebook

    Python is one of the most popular programming languages for data analysis due to its simplicity and flexibility.


    Python for Data Analysis is a comprehensive guide for individuals who want to learn how to use Python for data manipulation, cleanin

    LanguageEnglish
    PublisherIke Beck
    Release dateMar 27, 2023
    ISBN9783988312334
    PYTHON FOR DATA ANALYSIS: A Practical Guide to Manipulating, Cleaning, and Analyzing Data Using Python (2023 Beginner Crash Course)

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      Book preview

      PYTHON FOR DATA ANALYSIS - Ike Beck

      Introduction

      Today, data analysis is crucial in many aspects of life. You interact with data on various levels from the moment you wake up. It is the foundation for many important decisions. Companies require data to achieve their objectives. As the world's population continues to grow, so does its customer base. As a result, they must find ways to keep their customer's happy while also meeting their business objectives.

      Keeping customers happy in the business world is difficult given the nature of competition. Competitors continue to prey on each other's customers and those who succeed face a new challenge: how to keep customers from returning to former business partners. This is an area where Data Analysis can help.

      Companies rely on data to better understand their customers. Data is everywhere and comes in many forms. Data can be mined whenever there is customer interaction. Data can be useful in a variety of ways. Companies, for example, can better understand their customers' needs by grouping them according to their specific needs. With such segmentation, it will be possible to better meet the needs of customers and keep them satisfied for a longer period of time.

      Data Analytics, on the other hand, is about more than just customers and profits. It is also a matter of governance. Governments are the world's largest data consumers. They collect information about citizens, businesses, and any other entity with which they interact at any given time. This is important information because it is useful in many situations.

      Governments require accurate population data for planning purposes so that funds can be allocated appropriately. Proper resource allocation is impossible to achieve without proper data analysis. Aside from planning, there is also the issue of security. The government must maintain several databases for various reasons in order to protect the country. There are high-profile people who require special protection, so the most serious threats must be monitored at all times. To achieve the goal of security, the government must obtain and maintain accurate data on people of interest at all times.

      Data Analysis encompasses far more than corporate and government decisions. As a programmer, you are entering an industry that is both challenging and exciting. Data does not lie unless it is manipulated, in which case you must have insane Data Analysis and manipulation skills. As a data analyst, you will face numerous challenges and problems that can only be solved through data analysis. The way you interact with data can have a far-reaching impact, perhaps greater than you realize.

      You can analyze data using a variety of tools. Many people use Microsoft Excel, and it serves them well. However, there are some limitations to using Excel that Python can help you overcome. Learning Python is a good idea because it is one of the most simple and effective programming languages. Because its syntax is so similar to the normal language we use, it is classified as a high-level programming language. This facilitates your understanding of Python concepts.

      This book is the culmination of a lengthy series that introduced you to Data Analysis with Python. Some key ideas have been repeated since the beginning of the series to help you remember the basics. Knowing Python libraries is essential. You can become an expert Data Analyst with Python by understanding specific libraries.

      As we interact with data, it is critical to understand the significance of data cleaning to ensure that the results of our analysis are not flawed. We will learn how to do this so that our work is flawless. Another issue that many organizations face is maintaining data integrity. You should make every effort to keep your organization from using biased data. There are procedures you can implement to ensure that you always use clean data.

      We live in a world where data is at the heart of almost everything we do. Every day, large amounts of data are generated and stored by automated systems. Learning Data Analysis with Python will assist you in processing and extracting information from data and drawing meaningful conclusions from it. Forecasting is one application of these skills. Data analysis can be used to develop predictive models that will assist a company in meeting its objectives.

      A good predictive model is only as good as the data that is fed into it, the data modelling methods used, and, most importantly, the dataset used for the analysis. Aside from data handling and processing, visualization, or presentation, is an important aspect of data analysis. At the first point of contact, your data model should be good enough for an audience to read and understand it. In addition to the audience, we will learn how to plot data on various visualizations to help you get a rough idea of the nature of the data you are working with.

      Once you have mastered Data Analysis, you must create a data model that includes visual concepts so that you can predict results and responses before moving on to the testing phase. Data analysis is a study that is in high demand in a variety of fields right now. Knowing what to do, when to do it, and how to handle data is a critical skill

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