Split Text To Columns In Mac For Addresses

16-08-2021
 |  [RAND-100] - Comments

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.

Click the shape or text box to select it. In the Format sidebar, click the Text tab. Click the Layout button near the top of the sidebar, then click the arrows next to the Columns value field to add or remove columns. To see more formatting options, click the disclosure arrow next to Columns. Select the column with the addresses in it. In our example, column B has the addresses so we would select the entire column by clicking on the letter B at the top of the column. Select the text to columns function from the data menu. When the text to columns wizard opens, select Delimited and click Next.

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.

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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.

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.

Text

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.

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

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

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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.

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().

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Original Question:-

I am importing text file in Excel, but all data is importing in a column I want to split a column data into 3 different cells. How can I do it please suggest.

In this thread user wants to split a cell into 3 and more cells as per data requirement. To fulfill this requirement we use 'Text to Column' option.

Text to Columns: - This function is used to split a single column of text into multiple columns.

Let’s take an example and understand how we can use this function to split a single cell.

We have a list of addressesin column A which contains the entire address in a single cell. We needto split the address into separate columns.

There are 3 steps in the Text to Columns function:-

  • Select the column A.
  • Go to the “Data” tab, from the “Data Tools” group, click on “Text to Columns”.
  • “Convert Text to Columns Wizard – Step 1 of 3” dialog box will appear.
  • In the dialog box you will find 2 file types: - Delimited and Fixed Width.
    A. Delimited:-Character such as commas or tabs separate each field.
    B. Fixed Width: - Fields are aligned in columns with spaces between each field.
  • For this data we have to select the Delimited option, because there is no fixed width.
  • Click on the Next button.
  • The “Convert Text to Column Wizard – Step 2 of 3” dialog box will appear.
  • Click and put a tick on the “Space” check box because our data delimiter is “Space”. When you will click on it, then you can see the data being separated in the data

preview box. If your data has comma as the delimiter which is mostly the case, you can select the comma check box.

  • Click on the Next button.
  • The “Convert Text to Column Wizard – Step 3 of 3” dialog box will appear.

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  • Click on destination to choose the location where you want to split the text. The destination box will show $A$1 but if you do not want to over-write the existing data, then you can either select $B$1:$D$1 or just $B$1.
  • Click on the “Finish” button

Split Text To Columns In Mac For Addresses

You can see above that the text from one cell in column A has been split into the column B:F. This is very useful when you receive the data as in column A and need to split it into multiple columns for further analysis and reporting.

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Note:- If you merge data in Excel then will cell will not be split in other cells through Text to Column.