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BasedTab

Usage

Installation

For development:

git clone https://github.com/AnswerDotAI/basedtab.git
pip install -e .

Install latest from the GitHub repository:

$ pip install git+https://github.com/AnswerDotAI/basedtab.git

or from conda

$ conda install -c AnswerDotAI basedtab

or from pypi

$ pip install basedtab

How to use

from basedtab.core import *
from nbdev.config import get_config

data_path = str(get_config().config_path/'data/toy.csv')
bf = BFrame.read_csv(data_path)
bf.head(3).df
<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>
Number City Gender Age Income Illness
0 1 Dallas Male 41 40367.0 No
1 2 Dallas Male 54 45084.0 No
2 3 Dallas Male 42 52483.0 No
from basedpl import add, tally, square
MEAN = add.reduce_first / tally
bf.groupby("City", "Income", mean=MEAN).df.astype(int)
<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; } </style>
Income
0 mean 45252
1 mean 96857
2 mean 95264
3 mean 135078
4 mean 91554
5 mean 70991
6 mean 100756
7 mean 90277
RMSE = MEAN.under(square)
bf.head(100).groupby("Gender", ["Age", "Income"], mean=MEAN, rmse=RMSE)
┌→───────────────────────────┐
↓0⌷                          │
↓             Age      Income│
│mean 44.57407407 48301.42593│
│rmse 45.66970793 49632.10639│
│                            │
│1⌷                          │
│             Age      Income│
│mean 45.30434783 39739.36957│
│rmse 46.73468128 40738.65853│
└~───────────────────────────┘
bf["Income"].hist()

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