viper

Simple, expressive pipeline syntax to transform and manipulate data with ease

Overview

viper is a Python package that provides a simple, expressive way to work with data. It allows you to easily manipulate and transform data using a pipeline syntax similar to that of dplyr.

Pipelining your DataFrame manipulation operations offers several benefits:

• improved code readability (no need to 'comment the what')
• no need to save intermediate dataframes
• ability to chain a long sequence of operations in a single command
• thinking of coding as a series of transformations between the input and the desired output can improve the design and make it less coupled

Docs

Complete documentation is available here.

Quick Start

Installation:

pip install viper-df

Here is an example of how to use viper to analyze the famed mtcars dataset.

We want to find:

• the average consumption, expressed in Miles/(US) gallon
• the average power

Furthermore:

• only consider those cars that weigh more than 2000lbs
• group the results by the number of cylinders and number of gears
• arrange in descending orders by the grouping variables

import viper as v
from viper.data import mtcars

v.pipeline(
    mtcars,
    v.rename(
        "hp = power",
        "mpg = consumption",
    ),
    v.mutate(
        consumption=lambda r: 1 / r["consumption"]
    ),
    v.filter(
        lambda r: r["wt"] > 2
    ),
    v.group_by("cyl", "gear"),
    v.summarize(
        "power = mean()",
        "consumption = mean()"
    ),
    v.arrange(
        "cyl desc",
        "gear desc"
    ),
)
#                power  consumption
# cyl gear
# 8   5     299.500000     0.064979
#     3     194.166667     0.068824
# 6   5     175.000000     0.050761
#     4     116.500000     0.050875
#     3     107.500000     0.050989
# 4   5      91.000000     0.038462
#     4      85.000000     0.041259
#     3      97.000000     0.046512

Here you can find more examples, particularly on joins.

Roadmap

The future development of the package will probably focus on:

• adding pivot_longerand pivot_wider functions
• adding more join_* functions

Contributions

You are welcome to contribute to the project or open issues if you have any ideas.