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One easy way would be to reassign the data frame with a list of the columns, rearranged as needed. Will do exactly what you want. You need to create a new list of your columns in the desired order, then use of = of[cols] to rearrange the columns in this new order. You can also use a more general approach.
1. Get the values of the last column in a variable, drop the last column, and insert it to the Database as the first column. 2. Get the column names of the Database in a list, rearrange the list of columns in your desired order, and use the rearranged list as an index for the Database.
1. Get the values of the last column in a variable, drop the last column, and insert it to the Database as the first column. 2. Get the column names of the Database in a list, rearrange the list of columns in your desired order, and use the rearranged list as an index for the Database.
DOB = DOB. Sort_values(by ='Name', ascending=False. Print(“Contents of Sorted Data frame based on a column 'Name' in Descending Order : print(DOB)
To delete rows and columns from Databases, Pandas uses the drop function. To delete a column, or multiple columns, use the name of the column(s), and specify the axis as 1. Alternatively, as in the example below, the 'columns' parameter has been added in Pandas which cuts out the need for 'axis'.
1:00 5:22 Suggested clip Reorder Columns of Data Frame in R (4 Examples) | Change YouTubeStart of suggested client of suggested clip Reorder Columns of Data Frame in R (4 Examples) | Change
One way to change the level order is to use factor() on the factor and specify the order directly. In this example, the function ordered() could be used instead of factor(). Another way to change the order is to use relevel() to make a particular level first in the list. (This will not work for ordered factors.)

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