From the course: Python in Excel: Data Outputs in Custom Data Visualizations and Algorithms
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Leveraging Excel line charts
From the course: Python in Excel: Data Outputs in Custom Data Visualizations and Algorithms
Leveraging Excel line charts
- [Instructor] When we're working with Excel charts, there are a few key peculiarities to keep in mind to make these workflows easier. In line charts and scatterplots, for example, the x-axis is categorical and not numerical. It's helpful to sort the axes and the data table or pivot table beforehand, so these order labels flow into the chart itself. We can use legends in Excel charts, but a separate series rather than using the labels in a single field to apply color groups to the data points. Excel charts also interpret blank values as zeros, which means we want to put NAs, for example, in these empty cells. Let's first create a line chart for the temperature anomalies over the last several years. (inhales) We can reference the values and the data frame object that we expanded into a table in Excel formulas of their own. We'll add a column to this table that we'll call, Label. To display the anomalies on the chart at the point at which they occurred and the value they occurred at, we…
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Contents
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Visualizing data1m 35s
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(Locked)
Leveraging Excel line charts3m 58s
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(Locked)
Leveraging Excel scatter plots5m 21s
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(Locked)
Configuring Python in Excel with dynamic parameters4m 32s
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(Locked)
Creating Python visuals2m 13s
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(Locked)
Visualizing hierarchical clustering with dendrograms6m 43s
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(Locked)
Breaking down time series models into components5m 29s
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(Locked)
Challenge: Comparing time series components to anomalies50s
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(Locked)
Solution: Comparing time series components to anomalies4m 56s
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