Just upload your CSV file in the form below, specify the columns to swap, and the tool will automatically change the positions of the specified columns in the output file. In the tool options, you can specify the column positions or names that you want to swap, as well as fix incomplete data and optionally remove empty records and records that have been commented out.
This tool reorganizes CSV data by swapping the positions of its columns. Swapping columns can enhance the readability of a CSV file by placing frequently used data together or in the front for easier data comparison and editing. For example, you can swap the first column with the last or swap the second column with the third. To swap columns based on their positions, select the
Fill incomplete CSV data with empty symbols or a custom symbol.
In this example, we use our CSV column swapping tool to bring the most important information to the first column. As we are planning to go on vacation soon, in the input of the tool, we load data about national parks that include their names and locations. To decide, which is the closest park to us, we need to see the parks location first, therefore, we swap the first and second data columns so that the "location" column is at the beginning of the CSV data.
park_name,location Yellowstone,Wyoming Yosemite,California Grand Canyon,Arizona Rocky Mountain,Colorado Zion Park,Utah
location,park_name Wyoming,Yellowstone California,Yosemite Arizona,Grand Canyon Colorado,Rocky Mountain Utah,Zion Park
Fill incomplete CSV data with empty symbols or a custom symbol.
In this example, a lab intern made a mistake and created a corrupted CSV file with mixed-up columns and missing data. To fix the file, we swap the columns based on the headers "Vitamin" and "Function" so that the "Vitamin" column becomes the first in the output data. We also fill the incomplete CSV data by adding a custom asterisk "*" symbol in place of missing values.
Function,Fat-Soluble,Vitamin,Sources Supports vision,Fat-Soluble,A,Carrots Immune function,Water-Soluble,C,Citrus fruits Bone health,Fat-Soluble,D,Fatty fish Antioxidant,Fat-Soluble,E,Nuts Blood clotting,Fat-Soluble,K,Leafy greens Energy production,Water-Soluble,B1 Energy production,Water-Soluble,B2 Energy production,Water-Soluble,B3,Meat Protein metabolism,Water-Soluble,B6,Poultry Nervous system,Water-Soluble,B12,Meat
Vitamin,Fat-Soluble,Function,Sources A,Fat-Soluble,Supports vision,Carrots C,Water-Soluble,Immune function,Citrus fruits D,Fat-Soluble,Bone health,Fatty fish E,Fat-Soluble,Antioxidant,Nuts K,Fat-Soluble,Blood clotting,Leafy greens B1,Water-Soluble,Energy production,* B2,Water-Soluble,Energy production,* B3,Water-Soluble,Energy production,Meat B6,Water-Soluble,Protein metabolism,Poultry B12,Water-Soluble,Nervous system,Meat
Header of the first column you want to swap.
Header of the second column you want to swap.
Fill incomplete CSV data with empty symbols or a custom symbol.
In this example, we change the order of columns in a CSV dataset to have the columns essential for analysis adjacent to each other. We match the "ScreenSize" column by its name and place it in the second-to-last position "-2". This groups the "ScreenSize" and "Price" columns together, allowing us to easily compare and choose the phone we want to buy. We also remove empty lines and specify that lines starting with the "#" symbol are comments and should be left as is.
Brand,Model,ScreenSize,OS,Price Apple,iPhone 15 Pro Max,6.7″,iOS,$1299 Samsung,Galaxy S23 Ultra,6.8″,Android,$1199 Google,Pixel 7 Pro,6.4″,Android,$899 #OnePlus,11 Pro,6.7″,Android,$949 Xiaomi,13 Ultra,6.6″,Android,$849
Brand,Model,OS,ScreenSize,Price Apple,iPhone 15 Pro Max,iOS,6.7″,$1299 Samsung,Galaxy S23 Ultra,Android,6.8″,$1199 Google,Pixel 7 Pro,Android,6.4″,$899 Xiaomi,13 Ultra,Android,6.6″,$849
Header of the first column you want to swap.
Fill incomplete CSV data with empty symbols or a custom symbol.
Convert CSV data to JSON format.
Convert CSV data to XML format.
Convert CSV rows to columns.
Convert CSV data to TSV format.
Quickly convert a CSV file to a YAML file.
Change CSV file delimiter
Quickly find rows and columns in CSV that are missing values.
Quickly transpose a CSV file.
Quickly insert one or more new columns anywhere in a CSV file.
Convert TSV to JSON format