High Low Chart In Excel
Building a chart in Excel in and of itself is not a terribly difficult thing to do. The hard part is getting your mind around which types of chart to use in which situation. Excel has 11 major chart types with variations on each type. For most business dashboards and reports, you will only need a handful of the chart types available in Excel, including the following:
Steps to create volume-open-high-low-close chart: Step 1: Initialize chart. Step 2: Assign data and specify the chart type. Step 3: Apply basic chart elements. Analyze your Excel information by creating high/low lines for your data charts, allowing you to easily view parameters of a given range. Mary Ann Richardson gives you the lowdown.
Open High Low Close Chart In Excel
Line Chart: The line chart is one of the most frequently used chart types, typically used to show trends over a period of time. If you need to chart changes over time, consider using a line chart.
Column Chart: Column charts are typically used to compare several items in a specific range of values. Column charts are ideal if you need to compare a single category of data between individual sub-items, such as, for example, when comparing revenue between regions.
Clustered Column Chart: A clustered column chart can be used if you need to compare multiple categories of data within individual sub-items as well as between sub-items. For instance, you can use a clustered column chart to compare revenue for each year within each region, as well as between regions.
Stacked Column Chart: A stacked column chart allows you to compare items in a specific range of values as well as show the relationship of the individual sub-items with the whole. For instance, a stacked column chart can show not only the overall revenue for each year, but also the proportion of the total revenue made up by each region.
Pie Chart: Another frequently used chart is the old pie chart. A pie chart represents the distribution or proportion of each data item over a total value (represented by the overall pie). A pie chart is most effective when plotting no more than three categories of data.
Bar Chart: Bar charts are typically used to compare several categories of data. Bar charts are ideal for visualizing the distribution or proportion of data items when there are more than three categories. For instance a bar chart could be used to compare the overall revenue distribution for a given set of products.
Area Chart: Area charts are ideal for clearly illustrating the magnitude of change between two or more data points. For example, you can give your audience a visual feel for the degree of variance between the high and low price for each month.
Combination Chart: A combination chart is a visualization that combines two or more chart types into a single chart. Combination charts are an ideal choice when you want to compare two categories of each individual sub-item. They are commonly used to create visualizations that show the difference between targets versus actual results.
XY Scatter Plot Chart: Scatter charts in Excel (also known as XY scatter plot charts) are excellent for showing correlations between two sets of values. For example an XY scatter plot can be used to illustrate the correlation between employee performance and competency, demonstrating that employee performance rises as competency improves. The x and y axes work together to represent data plots on the chart based on the intersection of x values and y values.
Bubble Chart: A bubble chart is a variation of an XY scatter plot. Just like the XY scatter plot, bubble charts show the correlation between two sets of data. The difference is the addition of a third dimension that is represented by the size of each bubble in the chart. This third dimension is typically used to show the relative impact of a quantitative data item. For instance, in addition to showing employee performance versus competency, you can have the size of each bubble represent years of service, allowing your audience to quickly get a sense of how years of service may affect the relationship between competency and performance.