================ by Jawad Haider
Chpt 2 - Data Manipulation with Pandas¶
10 - Vectorized String Operations¶
Vectorized String Operations¶
One strength of Python is its relative ease in handling and manipulating string data. Pandas builds on this and provides a comprehensive set of vectorized string operations that become an essential piece of the type of munging required when one is working with (read: cleaning up) real-world data. ## Introducing Pandas String Operations We saw in previous sections how tools like NumPy and Pandas generalize arithmetic operations so that we can easily and quickly perform the same operation on many array elements.
array([ 4, 6, 10, 14, 22, 26])
This vectorization of operations simplifies the syntax of operating on arrays of data: we no longer have to worry about the size or shape of the array, but just about what operation we want done. For arrays of strings, NumPy does not provide such simple access, and thus you’re stuck using a more verbose loop syntax:
['Peter', 'Khan', 'Haider', 'Killy', 'Guidol', ' ']
AttributeError: 'NoneType' object has no attribute 'capitalize'
Pandas includes features to address both this need for vectorized string operations and for correctly handling missing data via the str attribute of Pandas Series and Index objects containing strings.
0 peteR
1 khan
2 Haider
3 None
4 KILLY
5 GuIDol
dtype: object
0 Peter
1 Khan
2 Haider
3 None
4 Killy
5 Guidol
dtype: object
Tables of Pandas String Methods¶
If you have a good understanding of string manipulation in Python, most of Pandas’ string syntax is intuitive enough that it’s probably sufficient to just list a table of avail‐ able methods; we will start with that here, before diving deeper into a few of the sub‐ tleties.
monte = pd.Series(['Graham Chapman', 'John Cleese', 'Terry Gilliam',
'Eric Idle', 'Terry Jones', 'Michael Palin'])
0 Graham Chapman
1 John Cleese
2 Terry Gilliam
3 Eric Idle
4 Terry Jones
5 Michael Palin
dtype: object
Methods similar to Python string methods Nearly all Python’s built-in string methods are mirrored by a Pandas vectorized string method. Here is a list of Pandas str methods that mirror Python string methods:
| len() | lower() | translate() | ljust() | upper() | startswith() | isupper() | islower() |
| rjust() | find() | endswith() | isnumeric() | center() | rfind() | isalnum() | |
| rsplit() | rstrip() | capitalize() | isspace() | partition() | lstrip() | swapcase() | rpartition()` |