Data Storytelling — Basic Data Visualization in Excel

Siva
2 min readOct 6, 2020

Graph in Excel

Many people are working with large volumes of data in excel and there is a need to learn how to create a graph in excel. Data visualization has been a very important thing for any job and this is because anytime the visualization of data is an effective method for communicating your findings with the readers. With these graphs and charts, we can identify patterns and many more insights from our data which helps us to make better decisions.

Format graphs

As we know that graphs and charts play an important role in any job, it is just not enough we can leave the default settings of the graph. Tune the graph according to your data requirements and always remember to keep it simple. One important is to choose the right chart for your data, this can be done by understanding the functionality of the charts and find the advantages, disadvantages of the charts. The next step is to choose the right colors to represent the data, this can help the readers to spot the differences quickly and identify the pattern and message. The final step is to label your data in an appropriate manner and make sure that you don't excessively label the data.

Create graph worthy data

Before jumping into graphing, you need to make sure that your data is graph worthy. Check that if your data don't have any null values, is it well organized, and verify if the columns are containing a single group of data, do your data gives you any insights from graphs. If you pass all the checkpoints, you can go ahead and create a graph.

V lookups and Pivot Tables to summarize data

V lookups and Pivot tables are the most used functions in excel. Vlookups helps you to check the data in a column in one table and check it with the other table if the data matches according to your mentioned requirement it will give the desired output. This is like joins in SQL. On the other hand, pivot tables are used to summarize the data of a more extensive table. Some examples are finding the sum, average, and other statistics on the data, grouping columns according to the categories, you can also apply filters.

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