2.3 KiB
If you need to resize a CSV file to be under 10 MB, you can do so using command line tools available on Linux. One effective approach is to utilize the csvkit tools, specifically csvcut to cut out unnecessary columns or csvgrep to filter out rows based on specific criteria. Here are a couple of ways you might approach this:
1. Install csvkit
If you don't already have csvkit installed, you can install it via pip (Python's package manager):
pip install csvkit
2. Check the Current File Size
First, ensure that the file workSQLtest.csv indeed exceeds 10 MB but is close to it, as you noted it's around 2.9 MB. If you have other files that need resizing, you can check their sizes using:
ls -lh <filename>
3. Analyze the CSV File
Before resizing, analyze the file to understand what data it contains, which will help you decide what to keep and what to cut:
csvstat workSQLtest.csv
4. Reduce File Size
Depending on the analysis, you can choose one of the following methods:
a. Remove Unnecessary Columns
If the file has columns that aren't needed, you can remove them using csvcut:
csvcut -C column_number_to_remove workSQLtest.csv > reduced_workSQLtest.csv
Replace column_number_to_remove with the actual numbers of the columns you want to omit.
b. Filter Rows
If there are specific rows that are not necessary (e.g., certain dates, entries), use csvgrep:
csvgrep -c column_name -m match_value workSQLtest.csv > filtered_workSQLtest.csv
Replace column_name and match_value with the appropriate column and the value you want to filter by.
c. Split the CSV
If the dataset is too large and all data is essential, consider splitting the CSV into smaller parts:
csvsplit -c column_name workSQLtest.csv
This splits the CSV file based on unique values in the specified column.
5. Check the New File Size
After modifying the file, check the new file size:
ls -lh reduced_workSQLtest.csv
or
ls -lh filtered_workSQLtest.csv
Use these commands to confirm the file is now under the desired size limit.
These tools offer a powerful way to manipulate CSV files directly from the command line, allowing for quick resizing and adjustment of data files to meet specific constraints.