# BasedTab
## Usage
### Installation
For development:
``` bash
git clone https://github.com/AnswerDotAI/basedtab.git
pip install -e .
```
Install latest from the GitHub
[repository](https://github.com/AnswerDotAI/basedtab):
``` sh
$ pip install git+https://github.com/AnswerDotAI/basedtab.git
```
or from [conda](https://anaconda.org/AnswerDotAI/basedtab)
``` sh
$ conda install -c AnswerDotAI basedtab
```
or from [pypi](https://pypi.org/project/basedtab)
``` sh
$ pip install basedtab
```
## How to use
``` python
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
```
|
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 |
``` python
from basedpl import add, tally, square
MEAN = add.reduce_first / tally
bf.groupby("City", "Income", mean=MEAN).df.astype(int)
```
|
|
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 |
``` python
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│
└~───────────────────────────┘
``` python
bf["Income"].hist()
```
