You don't always need all the columns of data that have been imported. In this video Matt Francis explains how to simplify your data by removing unwanted columns and how to change the field names from the originally imported data.
- [Instructor] Often, to make it easier…to do our analysis, we want to rename the fields…to make them something more meaningful.…Luckily we don't have to stick with the default values…that come across from our data set.…You can rename any of the fields in Prep,…and these will persist to the rest of the analysis.…Now common use case for this is where you've used…an automatic split.…So for example, we have our customer ID here…that consists of two parts.…Now if I use the automatic split,…we're going to get two new columns.…Now by default, it calls them Customer ID Split One,…Customer ID Split Two.…
That doesn't really mean anything to anybody.…In actual fact, I know from this customer ID…that the first part are the customer initials.…So I'm going to rename that.…So to do that, I can either click on the drop down…and click on rename field,…and I can change to Customer Initials.…And it has now renamed that field,…and if we look at the bottom, in the data grid,…we can now see it's called Customer Initials.…Now the second half of that split, the customer ID,…
Author
Released
1/2/2019- The data prep cycle
- Connecting to data
- Examining data in the preview pane
- Cleaning data
- Combining data using joins and unions
- Reshaping and pivoting data
- Previewing and sharing data
- Data sampling to improve performance
Skill Level Intermediate
Duration
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Introduction
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Software setup1m 36s
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1. Introduction to Tableau Prep
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What is Tableau Prep?2m 34s
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Tableau anatomy4m 2s
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2. Connecting to Data
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Connecting to a data source2m 38s
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Using the data interpreter1m 53s
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Connecting to multiple files2m 38s
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3. Exploring Your Data
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Using the Profile pane2m 52s
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How to search and sort3m 22s
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4. Cleaning Your Data
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Removing and renaming fields2m 40s
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Filtering data3m 48s
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Grouping values3m 48s
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Replacing values3m 49s
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Keeping track of changes4m 23s
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Solution 3: Cleaning data2m 43s
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5. Combining Your Data
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Union data using wildcards3m 58s
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Correcting mismatched fields3m 40s
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Creating joins4m 8s
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Correcting join errors3m 38s
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Solution 4: Combining data3m 55s
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6. Reshaping Your Data
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Reshaping using pivots3m 8s
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Aggregating data3m 41s
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Solution 5: Aggregate data3m 43s
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7. Sampling Your Data
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Sampling your data2m 42s
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Sampling options3m 36s
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Solution 6: Data sampling3m 16s
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8. Previewing and Sharing Your Data
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Creating output files4m 1s
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9. Example Flows
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Flight delays4m 45s
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World indicators4m 25s
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Superstore4m 41s
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Minimum wage4m 9s
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Conclusion
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Next steps11s
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Video: Removing and renaming fields