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It does not require any prior experience with spreadsheets or coding. Getting started with Excel is made easy in this course. By the end of this course you will have worked with several data sets and spreadsheets and demonstrated the basics of cleaning and analyzing data all without having to learn any code. The final project enables you to show off your newly acquired data analysis skills. You will then convert your data to a pivot table and learn its features to make your data organized and readable. Clean and analyze your data faster by understanding functions in the formatting of data. With each lab, you will gain hands-on experience in manipulating data and begin to understand the important role of spreadsheets. There is a strong focus on practice and applied learning in this course. By performing these tasks throughout the course, it will give you an understanding of how spreadsheets can be used as a data analysis tool and understand its limitations. With this introduction you will then learn to perform some basic level data wrangling and cleansing tasks and continue to expand your knowledge of analyzing data through the use of filtering, sorting, and using pivot tables within the spreadsheet. This course starts with an introduction to spreadsheets like Microsoft Excel and Google Sheets and loading data from multiple formats. You will gain valuable experience in cleansing and wrangling data using functions and then analyze your data using techniques like filtering, sorting and creating pivot tables. This course is suitable for those aspiring to take up Data Analysis or Data Science as a profession, as well as those who just want to use Excel for data analysis in their own domains. It includes plenty of videos, demos, and examples for you to learn, followed by step-by-step instructions for you to apply and practice on a live spreadsheet.Įxcel is an essential tool for working with data - whether for business, marketing, data analytics, or research. It covers some of the first steps for working with spreadsheets and their usage in the process of analyzing data. Now, we just need to make a little more glamor by choosing proper style for our report and add the appropriate chart based on the results of the research.This course is designed to provide you with basic working knowledge for using Excel spreadsheets for Data Analysis. That is, instead of years of respondents, we see 6 groups with given range of years. In our case, we will choose to show the respondents from 18 to 69 years in groups of 10 personsĪfter we confirm the action you should notice that the number of rows in the pivot table has decreased. The last field ( By) indicates the size of the group (bin). The second field ( Ending at) serves to set the value to which the data ends. The first of them ( Starting at) denotes the value from which starts the data that will be displayed in the pivot table. How would we group years of respondents into bins? We do this by right-clicking over any item in the row, then choosing the Group option.Ī dialog box that contains three text boxes will open. If you pay attention to the pivot table you will see that it has lots of rows. And for more transparent look we should remove totals from pivot table report. Next, let’s drag AGE dimension into Rows. This action will create implicit measure Count of SMOKER. In the Columns field we should drag the dimension SMOKER, and we will repeat this by dragging it to the Value field. Let’s select the data range and then create a pivot table in the same worksheet. In the first column there are years of respondents, and in the second answer to the question whether respondent is a smoker or not (YES or NO). In one simple case, where we research the age of the respondents and the answer to the question whether they are smokers or not, you will see how the groups (bins) are made and how can we later use them to create beautiful charts. When we create a pivot table report, based on statistical data, it’s sometimes convenient to group them into bins so that we can analyze them more easily.