There are multiple SO questions addressing some form of this topic, but they all seem terribly inefficient for removing only a single row from a csv file (usually they involve copying the entire file). If I have a csv formatted like so:
fname,lname,age,sex John,Doe,28,m Sarah,Smith,27,f Xavier,Moore,19,m
What is the most efficient way to remove Sarah's row? If possible, I would like to avoid copying the entire file.
Method 3: Removing using Conditions Select required data. Find the row that specifies the specified condition. Use drop() method and pass the index of the fetched row as a parameter in the drop method.
This way, we can ignore the header row from the csv while reading the data. Line 1: We import the Pandas library as a pd. Line 2: We read the csv file using the pandas read_csv module, and in that, we mentioned the skiprows=[0], which means skip the first line while reading the csv file data.
When using a DataSet or DataTable in conjunction with a DataAdapter and a relational data source, use the Delete method of the DataRow to remove the row. The Delete method marks the row as Deleted in the DataSet or DataTable but does not remove it.
You have a fundamental problem here. No current filesystem (that I am aware of) provides a facility to remove a bunch of bytes from the middle of a file. You can overwrite existing bytes, or write a new file. So, your options are:
\0
). If you want to be completely generic though, this is not an option with CSV files, because there is no defined comment character.The last option obviously doesn't help much if you are trying to remove the first line (but it is handy if you want to remove a line near the end). It is also horribly vulnerable to crashing in the middle of the process.
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