Choose columns release easily

Aug 6th, 2022
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How to choose columns release

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hey everyone its John here and in this video were going to take a look at how we can use the choose columns command in power query to make selecting columns and performing operations on those columns a little bit easier when we have a wide set of data so here Ive got data loaded into the power query editor and you can see that its pretty wide set of contact data and each record has five different contacts in it so for example here Ive got email one and if I scroll over then you can see that Ive got email two and lets say I wanted to combine those so merge those columns together what I might normally do is select the first one hold ctrl and scroll over to the next one and then try and find it and select Pat and repeat until Ive got them all selected and then I can come up to my transform tab and merge those columns now Im just gonna cancel that so an easier way to do that is to come up to the Home tab and theres an option here choose columns and if you click on that we have t

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To select columns, choose one of the following options: Type SELECT , followed by the names of the columns in the order that you want them to appear on the report. Use commas to separate the column names.
To select columns, choose one of the following options: Type SELECT , followed by the names of the columns in the order that you want them to appear on the report. Use commas to separate the column names.
You can also click anywhere in the table column, and then press CTRL+SPACEBAR, or you can click the first cell in the table column, and then press CTRL+SHIFT+DOWN ARROW. Note: Pressing CTRL+SPACEBAR once selects the table column data; pressing CTRL+SPACEBAR twice selects the entire table column.
Click the row or column heading. You can also select cells in a row or column by selecting the first cell and then pressing CTRL+SHIFT+ARROW key (RIGHT ARROW or LEFT ARROW for rows, UP ARROW or DOWN ARROW for columns).
Extract Columns from DataFrame using column indices with subset(). In this scenario, we can select single or multiple columns from the dataframe by specifying the column index inside the subset() function. It will take two parameters and return a dataframe with specified columns.
Position the cursor in the column header of the first column, and click and hold while you drag to select adjacent columns. Position the cursor in the row header of the first row, and click and hold while you drag to select adjacent rows.
You can create a new DataFrame of a specific column by using DataFrame.assign() method. The assign() method assign new columns to a DataFrame, returning a new object (a copy) with the new columns added to the original ones. Yields below output.
Android: Which Is Best For You?Select Non-Adjacent Cells with Keyboard and Mouse With your mouse, click the first cell you want to highlight. Press and hold the Ctrl key on the keyboard. Click the rest of the cells you want to highlight. Once the desired cells are highlighted, release the Ctrl key.
By using bracket notation on R DataFrame (data.name) we can select rows by column value, by index, by name, by condition e.t.c. You can also use the R base function subset() to get the same results. Besides these, R also provides another function dplyr::filter() to get the rows from the DataFrame.
To select a single column, use square brackets [] with the column name of the column of interest.

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