As we want to split the data in column A into two parts, Insert a column between columns A & B to place the second portion of the text. To insert another column, select column B and right-click on it, and then click insert, or we can use the shortcut key ( Ctrl with +). To split a column by position: In the Split a column by position dialog box: In the Number of character textbox, enter the number of characters used to. In the Number of character textbox, enter the number of characters used to split the text column. Select a Split option. Expand Show advanced. Start by selecting the range of cells containing the text you want to split and then clicking Data Text to Columns. On the first page of the wizard, select the “Fixed Width” option and then click “Next.” On the next page, we need to specify the position(s) in the column to split the content.

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Posted November 29, 2013 by Vishwanath Dalvi in Microsoft Excel

With Excel, you can split one cell into multiple rows or a comma delimited cell into multiple rows. This tutorial explains how.

If your job requires you to manipulate or organize large amounts of data, you probably spend lots of time working with Microsoft Excel for a variety of purposes. Excel is the gold-standard spreadsheet for manipulating data data and generating graphs.

You also need to deal with formatting and splitting data within Excel using formulas and filters.

Video Tutorial

Step-by-step directions

The process of converting one delimited row into multiple rows is divided into two stages.

1. Convert a delimited row string into multiple columns.
2. Transpose multiple columns into multiple rows.

Let us assume that you have the following data in a cell as one row, which is separated by a comma (,). This means the comma is a delimiter in this string.

[email protected], [email protected], [email protected], [email protected], [email protected]

Stage 1 – Convert a Delimited Row String into Multiple Columns

1. Select the delimited row that you want to convert into multiple rows.
2. From the top ribbon on the Data tab in the Data tool group, click Text to Columns.

3. In Step 1 of the Convert Text to Columns Wizard, select Delimited, and then click Next.

4. In Step 2, select the Comma checkbox, and clear all other checkboxes. In the Data preview, you can see the email addresses separated into multiple columns. Then click Finish.

Now, you can see the delimited row is separated into six different columns from A to F. We have completed the first stage, converting a delimited string into multiple columns. Now, we will complete Stage 2: Transpose.

Stage 2 – Transpose Multiple Columns into Multiple Rows

1. Select the range of columns, in this case columns A to F.
2. Press CTRL + C, or click Copy on the Home tab.
3. Select the cell where you want your first row to be. Right on that cell, from Paste Options, select the fourth option which is Transpose.

The video tutorial will take you through the same steps.

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Very often you may have to manipulate a column of text in a data frame with R. You may want to separate a column in to multiple columns in a data frame or you may want to split a column of text and keep only a part of it.

tidyr’s separate function is the best option to separate a column or split a column of text the way you want. Let us see some simple examples of using tidyr’s separate function.

Let us first load the R packages needed to see the examples with separate function.

Let us create a small data frame with a column of text separated by underscore.

The data frame contains just single column of file names.

How to Split a Single Column into Multiple Columns with tidyr’ separate()?

Let us use separate function from tidyr to split the “file_name” column into multiple columns with specific column name. Here, we will specify the column names in a vector.

By default, separate uses regular expression that matches any sequence of non-alphanumeric values as delimiter to split.

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In this example, tidyr automatically found that the delimiters are underscore and dot and separted the single column to four columns with the names specified.

Often you want only part of text in a column. Let us see another example of a data frame with column containing text, but this time we specify only three columns for our output.

Note that we provide just three columns in separate function.

The output of separate() in this example contains only three column as we specified. And we also see a warning, since we left out the extra element present after separating the text.

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We can use argument extra=’drop’ to specify separate to drop anything extra without warning us.

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Similarly, if we want only the first element after splitting, we can just specify only one column for our output.

If you want an element that is in the middle after separating with separate, we can use dplyr’s select function select the column needed. For example, if we need the second element ‘Month’, we can combine tidyr’s separate with dplyr’s select.

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unite() to combine multiple columns to a single column

Sometimes you may want to do opposite ehat separate can do, i.e. combine multiple columns into a single column. You guessed it right, tidyr has a cool function to do that. tidyr’s unite() complements separate() and combine multiple columns into a single column.

Let us see an example of unite() combining two columns created by separate(). Here, we first separate a column into three columns and then use unite() to combine the first two columns into a single column.

The output is a dataframe with two columns, where the first column is the result of unite().