String Methods in Pandas

Pandas is a powerful library in Python for data manipulation and analysis. It provides a number of string methods that allow you to manipulate and work with string data in DataFrame and Series objects. Some of the most commonly used string methods in Pandas are:

1. str.lower(): This method is used to convert all characters in a string to lowercase. For example, if the string is “HELLO WORLD”, calling str.lower() on it will return “hello world”.
2. str.upper(): This method is used to convert all characters in a string to uppercase. For example, if the string is “hello world”, calling str.upper() on it will return “HELLO WORLD”.
3. str.len(): This method is used to return the length of a string. For example, if the string is “hello world”, calling str.len() on it will return 11.
4. str.strip(): This method is used to remove leading and trailing whitespace from a string. For example, if the string is ” hello world “, calling str.strip() on it will return “hello world”.
5. str.replace(old, new): This method is used to replace all occurrences of a specified string with another string. For example, if the string is “hello world”, calling str.replace("world", "python") on it will return “hello python”.
6. str.contains(substring): This method is used to check if a specified substring is present in the string and returns a Boolean value. For example, if the string is “hello world”, calling str.contains("world") on it will return true.
7. str.startswith(substring): This method is used to check if the string starts with the specified substring and returns a Boolean value. For example, if the string is “hello world”, calling str.startswith("he") on it will return true.
8. str.endswith(substring): This method is used to check if the string ends with the specified substring and returns a Boolean value. For example, if the string is “hello world”, calling str.endswith("ld") on it will return true.
9. str.split(delimiter): This method is used to split a string into a list of substrings based on the specified delimiter. For example, if the string is “hello world”, calling str.split(" ") on it will return a list ["hello", "world"]
10. str.join(iterable): This method is used to join the elements of an iterable (such as a list) with the string as a separator. For example, if the list is ["hello", "world"] calling " ".join(list) will return “hello world”

These methods can be applied to Series and DataFrame columns containing string data using the .str accessor. For example, you can use the str.lower() method to convert all strings in a column to lowercase by calling df['column_name'].str.lower().

11. str.extract(pattern, flags=0, expand=True) – Extract capture groups in the regex pattern as columns in a DataFrame.
12. str.extractall(pattern, flags=0) – Extract capture groups in the regex pattern as a DataFrame.
13. str.findall(pattern, flags=0) – Return all non-overlapping matches of pattern as a list of strings.
14. str.get(i) – Return the i-th element of the underlying data as a string.
15. str.get_dummies() – Split each string on the delimiter passed to this method and return a DataFrame of dummy/indicator variables.
16. str.replace(pat, repl, n=-1, case=None, flags=0, regex=True) – Replace occurrences of pattern/regex in the Series/Index with some other string.
17. str.slice(start=None, stop=None, step=None) – Slice substrings from each element in the Series or Index.
18. str.slice_replace(start=None, stop=None, repl=None) – Replace a slice of a string by another.
19. str.split(pat=None, n=-1, expand=False) – Split strings around given separator/delimiter.
20. str.translate(table) – Map all characters in the string through the given mapping table.

These methods can be used in combination with other Pandas functions to perform advanced string manipulations and data cleaning tasks. It’s also important to note that some of these methods like str.extract() and str.extractall() use regular expressions, so it’s useful to have a basic understanding of regex syntax when working with these methods.