pandas_path-0.1.1.tar.gz

# `pandas_path` - Path style access for pandas [](https://pypi.org/project/pandas-path/) Love [`pathlib.Path`]()*? Love pandas? Wish it were easy to use pathlib methods on pandas Series? This package is for you. Just one import adds a `.path` accessor to any pandas Series or Index so that you can use all of the methods on a `Path` object. <small> * If not, you should.</small> Here's an example: ```python from pathlib import Path import pandas as pd # This is the only line you need to register `.path` as an accessor # on any Series or Index in pandas. import pandas_path # we'll make an example series from the py files in this repo; # note that every element here is just a string--no need to make Path objects yourself file_paths = pd.Series(str(s) for s in Path().glob('**/*.py')) # 0 setup.py # 1 pandas_path/accessor.py # 2 pandas_path/test.py # dtype: object ``` Use the `.path` accessor to get just the filename rather than the full path: ```python file_paths.path.name # 0 setup.py # 1 accessor.py # 2 test.py # dtype: object ``` Use the `.path` accessor to get just the parent folder of each file: ```python file_paths.path.parent # 0 . # 1 pandas_path # 2 pandas_path # dtype: object ``` Use calculated methods like `exists` to filter for what exists on the filesystem: ```python file_paths.loc[3] = 'fake_file.txt' # 0 setup.py # 1 pandas_path/accessor.py # 2 pandas_path/test.py # 3 fake_file.txt # dtype: object file_paths.path.exists() # 0 True # 1 True # 2 True # 3 False # dtype: bool ``` Use path methods like `with_suffix` to dynamically create new filenames: ```python file_paths.path.with_suffix('.png') # 0 setup.png # 1 pandas_path/accessor.png # 2 pandas_path/test.png # 3 fake_file.png # dtype: object ``` Use the `/` operators just as you would in `pathlib` (with the `.path` accessor on either side of the operator.) ```python "different_root_folder" / file_paths.path # 0 different_root_folder/setup.py # 1 different_root_folder/pandas_path/accessor.py # 2 different_root_folder/pandas_path/test.py # dtype: object ``` We'll even do element wise operations with lists/arrays/series of the same length. ```python file_paths.path.parent.path / ["other_file1.txt", "other_file2.txt", "other_file3.txt"] # 0 other_file1.txt # 1 pandas_path/other_file2.txt # 2 pandas_path/other_file3.txt # dtype: object ``` ### Limitations 1. While most operations work out of the box, operator chaining with `/` will not work as expected since we always return the series itself, not the accessor. ```python file_paths.path.parent.path / "subfolder" / "other_file1.txt" # ----> 1 file_paths.path.parent.path / "subfolder" / "other_file1.txt" # ... # TypeError: unsupported operand type(s) for /: 'str' and 'str' ``` Instead, either use the `.path` accessor on the result or re-write without chaining: ```python (file_paths.path.parent.path / "subfolder").path / "other_file1.txt" # 0 subfolder/other_file1.txt # 1 pandas_path/subfolder/other_file1.txt # 2 pandas_path/subfolder/other_file1.txt # dtype: object file_paths.path.parent.path / "subfolder/other_file1.txt" # 0 subfolder/other_file1.txt # 1 pandas_path/subfolder/other_file1.txt # 2 pandas_path/subfolder/other_file1.txt # dtype: object ``` 2. A numpy array or pandas series on the left hand side of `/` will not work properly. ```python pd.Series(['a', 'b', 'c']) / pd.Series(['1', '2', '3']).path ## IMPROPERLY BROADCASTS :'( # 0 0 a/1 # 1 a/2 # 2 a/3 # dtype: object # 1 0 b/1 # 1 b/2 # 2 b/3 # dtype: object # 2 0 c/1 # 1 c/2 # 2 c/3 # dtype: object # dtype: object ``` Instead, use the path accessor on the right-hand side as well. ```python pd.Series(['a', 'b', 'c']).path / pd.Series(['1', '2', '3']).path # 0 a/1 # 1 b/2 # 2 c/3 # dtype: object ``` That's all folks, enjoy! Developed and maintained by your friends at DrivenData! [ml competitions](https://www.drivendata.org/) | [ai consulting](http://drivendata.co/)