plydata

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plydata is a library that provides a grammar for data manipulation. The grammar consists of verbs that can be applied to pandas dataframes or database tables. It is based on the R package dplyr. plydata uses the >> operator as a pipe symbol.

At present the only supported data store is the pandas dataframe. We expect to support sqlite and maybe postgresql and mysql.

Installation

plydata only supports Python 3.

Official version

$ pip install plydata

Development version

$ pip install git+https://github.com/has2k1/plydata.git@master

Example

import pandas as pd
import numpy as np
from plydata import define, query, modify_where

df = pd.DataFrame({
    'x': [0, 1, 2, 3],
    'y': ['zero', 'one', 'two', 'three']})

df >> define(z='x')
"""
   x      y  z
0  0   zero  0
1  1    one  1
2  2    two  2
3  3  three  3
"""

df >> define(z=0) >> modify_where('x > 1', z=1)
"""
   x      y  z
0  0   zero  0
1  1    one  0
2  2    two  1
3  3  three  1
"""

# You can pass the dataframe as the # first argument
query(df, 'x > 1')  # same as `df >> query('x > 2')`
"""
   x      y
2  2    two
3  3  three
"""

plydata piping works with plotnine.

from plotnine import ggplot, aes, geom_line

df = pd.DataFrame({'x': np.linspace(0, 2*np.pi, 100)})
df >> define(y='np.sin(x)') >> ggplot(aes('x', 'y')) + geom_line()

What about dplython or pandas-ply?

dplython and pandas-ply are two other packages that have a similar objective to plydata. The big difference is plydata does not use a placeholder variable (X) as a stand-in for the dataframe. For example:

diamonds >> select(X.carat, X.cut, X.price)  # dplython

diamonds >> select('carat', 'cut', 'price')  # plydata
select(diamonds, 'carat', 'cut', 'price')    # plydata

For more, see the documentation.

Nyxaoc/plydata

plydata

Installation

Example

What about dplython or pandas-ply?