As a data scientist, you will often find yourself working with the command line interface (CLI) to manage and manipulate data, run scripts, and perform various tasks. Here are the top ten commands that can be useful for data scientists:
ls: For Windows, it is dir.This command lists the files and directories in a directory. You can use it to view the contents of your current working directory or to see the files and folders in a different directory.
cd: This command allows you to change the current working directory. You can use it to navigate to different directories on your machine or to switch between directories.
mkdir: This command creates a new directory. You can use it to create a new directory for your data or to organize your files and folders.
cp: This command copies files and directories. You can use it to make a copy of a file or directory, or to move files and directories to a different location.
mv: This command moves or renames files and directories. You can use it to rename a file or directory, or to move it to a different location.
rm: This command deletes files and directories. You can use it to delete a file or directory that you no longer need.
grep: This command searches for a specific pattern in a file or set of files. You can use it to search for specific data or to extract information from a large dataset.
find: This command searches for files and directories based on various criteria, such as name, size, and time modified. You can use it to locate specific files or directories on your machine.
wc: This command counts the number of lines, words, and characters in a file. You can use it to get a sense of the size and complexity of a dataset.
sort: This command sorts the lines in a file alphabetically or numerically. You can use it to organize data or to find patterns in a dataset.
These are just a few of the many commands that are available in the CLI. By mastering these and other commands, you can become more efficient and effective at working with data as a data scientist.
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