How to remove rows where any columns are empty in csv?
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How to remove rows where any columns are empty in csv
Remove rows from a large file is not a very simple matter. For example, I have a csv file with millions of lines, storing access logs, some lines need to be removed because the specified columns are empty. I need to remove these lines, and then do data analysis. How can I do it?
Method A：Excel or Google Spreadsheet
Yes, you can use Excel to remove rows where specified columns are empty. Here's how:
- Open your CSV file in Excel.
- Select the columns that you want to check for empty cells.
- Click the "Data" tab in the ribbon.
- Click the "Filter" button in the "Sort & Filter" group.
- Click the dropdown arrow in the header of the selected column and uncheck the "Blanks" option.
- Press "Ctrl + -" to delete the visible rows.
- Save the file as a new CSV file.
Note: This method assumes that the empty cells in the specified columns are truly blank and not just spaces. You can use the "Find and Replace" feature to remove spaces before applying the filter.
To remove rows where specified columns are empty in a CSV file, you can use a programming language such as Python. Here's one way to do it:
import pandas as pd
# Read the CSV file
df = pd.read_csv('input.csv')
# Remove rows with empty values in the specified columns
df.dropna(subset=['column1', 'column2'], inplace=True)
# Write the cleaned dataframe to a new CSV file
Here's the code in Python:
Note: Replace 'input.csv' and 'output.csv' with the actual file names. Also, replace ['column1', 'column2'] with the actual column names you want to check for empty values.
The best way：Use QuickTran function
- Visit our website and find the online tool.
- Open your csv file by clicking the "Choose File" button and selecting the file you want to change.
- Once the file has been uploaded, you can select the specified columns you want to be processed , and in seconds, you'll remove rows where all columns are empty.
- You can then download the files and save it to your computer.