This is a collection of short videos explaining how to use each data processing function, primarily those introduced in the web seminar "Data Processing with JMP - Beyond Spreadsheets" held in February 2024.
If you're ever unsure how to perform data manipulation tasks in JMP, such as deleting unnecessary rows, hiding columns, or removing duplicate data, please make use of this video collection.
*This seminar uses the latest version of JMP, "JMP 18.0".
*Many of the videos explained in this seminar use the Hostel dataset available on the following page.
Japan Hostel Dataset (kaggle.com)
*Click the Full Screen icon in the bottom right corner of the video to enlarge it.
table of contents
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0. Introduction (5 minutes 59 seconds)
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Introduction to this video.
Main items
- Convert raw data into analytical data
- Things to do in JMP when loading data into JMP
- Advantages of using JMP for data processing
- Data processing techniques introduced in this video
- Data primarily used in this seminar
- An example of exploratory data analysis using JMP (demonstration)
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1. Check and change the column scale (2 minutes 54 seconds)
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Purpose : After importing a spreadsheet such as Excel into JMP, check if the column scale is set to the expected scale and change the scale if necessary.
Continuous scale: A numerical measurement, a quantitative variable (continuous) Nominal scale: A qualitative variable (categorical) consisting of numbers or letters where the order is not significant. Ordinal scale: A qualitative variable (categorical) consisting of numbers or letters where the order is meaningful. As a general rule, numerical sequences are converted to a continuous scale, and strings are converted to a nominal scale.
Operation : Click the icon to the left of the column name in the Columns panel (left center of the data table) to change the scale. |
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2. Check and change the display order of values (1(45 minutes)
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use : Changes the order of categories (levels) displayed in JMP reports (tables, graphs, etc.).  operate：
- Select the column whose category order you want to change in the data table, then select [Column] > [Column Info].
- From the [Column Properties] in the bottom left, select [Value Display Order].
- Change the order of the values in the custom order section.
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3. Setting column labels and row labels (2(48 minutes)
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`use` : Displays labels for plotted points on a graph. Setting column labels displays the values in that column as labels. Setting row labels displays labels on the graph for the plotted points in that row.
operate： Column Labels : Select the column you want to label, then select [Column] > [Labeled/Unlabeled]. Row labels : Select the relevant row, then select [Row] > [With/Without Labels]. Note : To remove the label, perform the same operation as above (no label). |
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4. Grouping columns (1(28 minutes)
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Use : In JMP data tables, grouping several columns allows you to specify all the variables within that group together when specifying columns in analysis and graphing platforms.
To operate : Select all the columns you want to group, then select [Columns] > [Group Columns] .
Supplement : To ungroup the columns, select the group and then select [Columns] > [Ungroup Columns] . |
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5. Excluding rows unnecessary for analysis (4(1 minute 11 seconds)
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`use` : In a JMP data table, exclude rows that are unnecessary for analysis, or subset data that meets certain conditions.
operate： Hide and exclude rows With the row you want to exclude selected, select Rows > Hide and Exclude. subset
- Select [Table] > [Subset]
- Select the [Filtered Rows] radio button and set the filter criteria.
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6. Excluding and not displaying columns (1(57 minutes)
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`use` : Hides specific columns in a JMP data table. Example: Hides columns unnecessary for analysis in data with many columns.
Do not display: Do not display that column in the data table. Exclude: Do not include that column in the analysis (it will be removed from the platform's list of potential columns).
operate： Do not display Select the relevant column, then select [Columns] > [Hide/Show]. exclude Select the relevant column, then select [Column] > [Exclude/Do not exclude]. |
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7. Recoding (5(53 minutes)
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`use` : Primarily used for categorical variables (nominal and ordinal scales) to modify or merge category values. It can also be used to extract specific characters (numbers) from a given string.
To operate : Select the relevant column, then select [Column] > [Recode] , and specify the new value (the value to recode) for the old value (the current value).
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8. Creating the calculation formula (6(24 minutes)
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`use` : Creates a calculation formula for a JMP data table.
operate： 1. How to select the appropriate formula from the right-click menu Select the column to be included in the formula, right-click the column name, and select "Create New Formula". 
2. How to create an equation using the formula editor Select the column where you want to create the formula, then select [Column] > [Formula]. ⇒ The formula editor will launch, so create your formula. |
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9. Creating a formula for categorization (2(23 minutes)
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use : For columns with a continuous scale, set cut points and create categorized variables. Example: Create categorical columns for a column containing ages, dividing them into age groups such as teens, twenties, etc.
operate：
- Select the column with a continuous scale, then select [Column] > [Utilities] > [Create Categorization Formula].
- Set the cut point and select [Create Calculated Column] .
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10. Copy and paste column properties (2(1 minute 13 seconds)
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Use : In JMP data tables, you can set properties (attributes) for columns, such as the display order of values and value labels. Properties set for one column can be copied and pasted into another column to apply the same properties to that column as well.
operate：
- Select the column, right-click the column name, and select "Copy Column Properties" .
- Select the column you want to copy, right-click the column name, and select "Paste Column Properties" .
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11. Copy and paste the row attributes (2(45 minutes)
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Use : You can copy row attributes (exclude, hide, label, etc.) to a column in the data table and paste them when needed. For example, if a single data table has multiple exclusion conditions, these exclusion conditions can be stored in the data table and applied when needed.
operate： Create the destination column. Change the data type to [Row Attributes].  Copy the attributes of the current row to the column. Click the column icon and select "Copy from row attributes" .  Apply the information in the row attribute column as row attributes in the data table. Click the column icon and select "Copy to row attributes" .  |
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12. Checking and processing missing data (5(22 minutes)
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Use : To check for missing data. In JMP, you can check for missing data in detail mainly using the [Check Missing Values] or [Display Missing Value Patterns] platform.
operate： To check for missing values : Select [Analyze] > [Screening] > [Check for Missing Values] , and then select the column for which you want to check for missing values. Displaying Missing Value Patterns : Select [Table] > [Display Missing Value Patterns] and then select the column for which you want to check for missing values. |
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13. Checking for and handling outliers (4(38 minutes)
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Use : To identify outliers. In JMP, there are two main methods: visually checking them using box plots and scatter plots, and using the [Outlier Detection] platform.
operate： To find outliers : Select [Analyze] > [Screening] > [Find Outliers] , and then select the column (continuous scale) for which you want to find outliers. |
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14. Deleting duplicate data (4(1 minute 14 seconds)
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use : Selects columns with duplicate values for the selected column.
To operate : Select the column you want to check, then select [Rows] > [Select Rows] > [Select Duplicate Rows] .
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