Excel

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    Books
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    Excel 2021 for Dummies (Greg Harvey)

    A welcoming guide for beginners, this book clearly explains the essentials of Excel. You'll discover how to create spreadsheets, manage data, and apply formulas through hands-on examples, making it easy to master Excel skills.

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    Excel Formulas and Functions for Dummies (Ken Bluttman)

    This practical guide makes the complex world of formulas and functions accessible. Ken Bluttman expertly guides you through key techniques for calculations and data management, empowering you to tackle challenging tasks with confidence.

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    Excel VBA Programming For Dummies (Michael Alexander & John Walkenbach)

    Explore the powerful VBA programming language in Excel with this comprehensive guide. Suitable for all skill levels, it teaches you how to automate repetitive tasks and develop custom solutions, revolutionizing your Excel experience.

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    Excel 2019 Power Programming with VBA (Michael Alexander & Dick Kusleika)

    Unlock Excel's full potential with advanced VBA programming techniques. This book covers a range of topics, from automation to user forms, equipping you with the tools needed to boost productivity and streamline your workflows.

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    Excel Data Analysis For Dummies (Paul McFedries)

    Master data analysis in Excel with this straightforward guide by Paul McFedries. He covers essential tools and techniques, making it easy for anyone to extract meaningful insights from their data.

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    Microsoft Excel 2019 Step by Step (Curt Frye)

    This engaging resource is ideal for self-paced learners. With hands-on exercises and clear explanations, it guides you in building practical skills in Excel 2019, covering everything from basic functions to advanced features.

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    Excel Dashboards and Reports For Dummies (Michael Alexander)

    Discover how to create visually appealing dashboards and reports in Excel. This book offers practical tips for data visualization, enabling you to communicate insights effectively and make informed, data-driven decisions.

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    Excel 2019 in Easy Steps (Michael McGrath)

    Designed for quick learning, this book introduces Excel 2019’s essential features in a user-friendly format. With straightforward steps, it's perfect for anyone looking to improve their Excel skills without feeling overwhelmed.

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    Excel Pivot Table Data Crunching (Bill Jelen & Michael Alexander)

    Master pivot tables with this insightful guide by Bill Jelen and Michael Alexander. Filled with practical examples, it helps you analyze and summarize large data sets, making data management effortless.

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    Excel for Financial Analysis (Daniel E. Whitney)

    Essential for finance professionals, this book shows you how to utilize Excel for budgeting, forecasting, and financial modeling. With clear explanations and practical applications, it provides the tools you need for effective financial analysis.

    Reference Materials

    Excel Functions

    Function

    Description

    SUM(range)

    Adds all the numbers in a range of cells.

    AVERAGE(range)

    Calculates the average of a range of numbers.

    COUNT(range)

    Counts the number of cells with numeric entries in a range.

    IF(logical_test, value_if_true, value_if_false)

    Returns one value if a condition is true and another if false.

    VLOOKUP(lookup_value, table_array, col_index_num, [range_lookup])

    Searches for a value in the first column of a table and returns a value in the same row from a specified column.

    Excel Text Functions

    Function

    Description

    CONCATENATE(text1, text2, ...)

    Joins multiple text strings into one string.

    TRIM(text)

    Removes extra spaces from text, leaving only single spaces between words.

    LEFT(text, [num_chars])

    Returns the leftmost characters from a text string.

    RIGHT(text, [num_chars])

    Returns the rightmost characters from a text string.

    MID(text, start_num, num_chars)

    Returns a specific number of characters from a text string, starting at the position you specify.

    Excel Date and Time Functions

    Function

    Description

    NOW()

    Returns the current date and time.

    TODAY()

    Returns the current date.

    DATEDIF(start_date, end_date, unit)

    Calculates the difference between two dates.

    Excel Financial Functions

    Function

    Description

    PMT(rate, nper, pv, [fv], [type])

    Calculates the payment for a loan based on constant payments and a constant interest rate.

    FV(rate, nper, pmt, [pv], [type])

    Calculates the future value of an investment based on periodic, constant payments and a constant interest rate.

    Excel Logical Functions

    Function

    Description

    AND(logical1, [logical2], ...)

    Returns TRUE if all arguments are TRUE.

    OR(logical1, [logical2], ...)

    Returns TRUE if any argument is TRUE.

    NOT(logical)

    Reverses the value of its argument.

    Example Project
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    Excel Projects

    This repository showcases my work in Microsoft Excel, including two key projects: a dynamic heat map for accident analysis and a sales dashboard. The dynamic heat map visualizes accident trends in Cambridge by analyzing frequency based on time, type, and season. It helps identify the safest and riskiest travel times through interactive dropdowns and dynamically updating axes. The map integrates features like conditional formatting, Pivot Tables, and a Geo Heat Map using Power Map, making it easy to explore accident data.

    The sales dashboard provides an interactive analysis of sales by category and region. It incorporates tools such as Pivot Tables, Pivot Charts, Slicers, Sparklines, dynamic name tagging, and data refresh capabilities. The dashboard allows users to explore sales trends and regional insights effectively. Both projects demonstrate advanced Excel functionalities for data analysis and visualization.

    Source https://github.com/konchada2/Excel-Projects

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    Excel Portfolio Projects: A Journey through Advanced Excel and VBA

    This repository highlights my journey into advanced Excel and VBA through various portfolio projects. These projects were instrumental in enhancing my understanding of Excel’s capabilities and expanding its boundaries.

    Key learning resources played a significant role in this journey. Mastering Microsoft Excel keyboard shortcuts greatly improved my efficiency, with resources like the Microsoft support article serving as invaluable guides. The learning process followed a structured sequence, starting with foundational formulas and advancing to field-specific formulas. This progression laid the groundwork for mastering Pivot Tables, enabling efficient data analysis. Exploring ETL processes using Power Query and Power Pivot further strengthened my data manipulation skills. Finally, diving into VBA and Macros allowed me to automate repetitive tasks and optimize workflows.

    The repository offers a comprehensive look at my progress, showcasing diverse projects that demonstrate expertise in everything from basic formulas to advanced automation. It also reflects the logical learning sequence I employed to master Excel and VBA effectively.

    Source https://github.com/Balasubramanian-pg/Excel-Portfolio-Project

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    Sales Analysis Excel Project

    This repository showcases a Sales Analysis project using Excel. The dataset (Raw Data.xlsx) contains customer demographics and purchasing behavior data. Key steps include:

    • Data Cleaning: Ensuring data quality and consistency.
    • Pivot Tables & Charts: Creating visualizations to reveal trends and insights.
    • Interactive Dashboard: Building an Excel-based dashboard to explore key sales metrics and trends.

    Users can download the dataset, navigate the Excel sheets, and customize it for their analysis needs.

    Source https://github.com/imuhammadaasim/bike_sales_data_analysis

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    Microsoft Excel Data Analysis Projects Portfolio

    This repository showcases my data analysis projects, focusing on tasks such as data preprocessing, cleaning, and visualization.

    Projects Overview

    1. Housing Dashboard (Excel)
      • Analyzed California house prices (1990 dataset from Kaggle) to identify correlations with various factors.
      • Built a dashboard to present key insights and trends.
    2. Microsoft Financial Performance Dashboard (Excel)
      • Scraped financial data from Yahoo Finance using Power Query.
      • Created a minimalist dashboard showcasing Microsoft’s financial performance (2019–2022), highlighting metrics like total return and monthly average return.
    3. Source https://github.com/Mabrar92/Data-Analysis-Projects-Portfolio

    Expert Answers

    To create a drop-down list, select a cell, go to the "Data" tab, click on "Data Validation," and choose "List." Then, input your items in the source box.

    Relative references adjust when you copy a formula to a different cell (e.g., A1), whereas absolute references stay fixed (e.g., $A$1). You can toggle between them using the F4 key.

    Navigate to the "Home" tab, click on "Conditional Formatting," and select a rule type. This allows you to format cells based on criteria, like highlighting values that exceed a specific number.

    The VLOOKUP function looks for a value in the first column of a table and returns a corresponding value from a specified column in the same row. It's helpful for fetching related data efficiently.

    You can use the CONCATENATE function or the & operator to combine text. For example, `=CONCATENATE(A1, " ", B1)` or `=A1 & " " & B1` will join the contents of cells A1 and B1 with a space in between.

    The IF function enables conditional logic by returning one value if a condition is true and a different value if it's false. The syntax is `=IF(condition, value_if_true, value_if_false)`.

    Select your data, navigate to the "Insert" tab, and click on "PivotTable." Then, follow the prompts to choose the pivot table's location and select the fields you want to analyze.

    The #VALUE! error signifies a problem with the data type in a formula, often occurring when a calculation is attempted with text instead of numbers.

    Select the range of cells, go to the "Data" tab, and click on "Remove Duplicates." Choose the columns to check for duplicates, then click OK.

    COUNT only counts cells with numeric entries, whereas COUNTA counts all non-empty cells, including text and errors.