df-and-order 0.2.3

Using df-and-order your interactions with dataframes become very clean and predictable.

🗄️ df-and-order

Yeah, it's just like Law & Order, but Dataframe & Order!

pip install df_and_order

Using df-and-order your interactions with dataframes become very clean and predictable.

• Tired of absolute file paths in shared notebooks in your repository?
• Can't remember how your dataframes were generated?
• Want to have a reproducibility on data transformations?
• Like declarative config-based solutions?

Good news for you!

Imagine the world where all you need to do for reading some dataframe you need just a few lines:

reader = MagicDfReader()
df = reader.read(df_id='user_activity_may_2020')

Maybe you are interested in some transformed version of that dataframe? No problem!

reader = MagicDfReader()
# ready to fit a model on!
model_input_df = reader.read(df_id='user_activity_may_2020', transform_id='model_input')

It is possible by having a config file that will look like this:

df_id: user_activity_may_2020 # here's the dataframe identifier
initial_df_format: csv
metadata: # some useful information about the dataset
  author: Data Man
  data_collection_date: 2020-05-01
transformed_df_format: csv
transforms:
  model_input: # here's the transform identifier
    in_memory: # means we want to perform transformations in memory every time we calling it, permanent transforms are supported as well
    - module_path: df_and_order.steps.DropColsTransformStep # file with the transformation's code
      params: # init params for the transformation
        cols:
        - redundant_col
    - module_path: df_and_order.steps.DatesTransformStep - another transformation
      params:
        cols:
        - date_col

Just by looking at the config you can say how the transformed dataframe was created.

Take a look at the more detailed overview to find more exciting stuff.

I also wrote an article to describe the benefits, check it out! There are lemurs and stuff.

Hope the lib will help somebody to boost the productivity.

Unit-tested, btw!

Requirements

pandas
python 3.7