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How to quickly delete duplicate rows in CSV, Excel, Markdown tables?

If you're working with CSV, Excel, or Markdown tables, you may run into issues with duplicate rows. This could be because you entered duplicate data manually, or because you imported duplicate data from another source. Whatever the reason, removing duplicate rows is an important data cleansing task. This article will show you how to quickly remove duplicate rows in CSV, Excel, and Markdown tables using a few different methods.

1. Online form tool [recommended]

You can use an online tool called "Table Convert" to remove duplicate rows. This tool helps you easily check and remove duplicate rows in CSV, Excel, Markdown tables. Just open in the browser, then paste or upload the content to be deduplicated in the data source, and click the "Deduplicate" button of Table Editor to complete the deduplication easily and quickly Heavy, as shown in the figure:

Delete duplicate rows in CSV, Excel, Markdown tables

2. Delete duplicate rows in Excel

Deleting duplicate rows in Excel is a very simple matter. First, open your Excel file and select the column you want to check for duplicate rows. Next, click the "Data" menu and select "Remove Duplicates." Excel will pop up a dialog box for you to select the columns you want to delete duplicate rows from. Click OK and Excel will delete all duplicate rows.

3. Delete CSV Duplicate Lines with Python

If your data is stored in CSV files, you can use Python to remove duplicate rows. First, you need to install the pandas library. Then, use the following code to read the CSV file and remove duplicate rows:

import pandas as pd

data = pd.read_csv("your_file.csv")
data = data. drop_duplicates()
data.to_csv("your_file.csv", index=False)
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This code reads the CSV file, removes duplicate rows, and writes the cleaned data back to the original file.

Summary: Removing duplicate rows in CSV, Excel, and Markdown tables is an important data cleaning task. By using the above methods, you can easily check and remove duplicate lines in these files and make sure your data is accurate and useful.

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