StataLovers 1.3
Stata-like functions tab and summarize

# StataLovers package

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

This package contains two functions that are produce similar output as Stata's tab and sum functions.

## Installation

```
pip install StataLovers
```

## Usage

- The OOP way
- There is (for now) one main class with 2 functions:
  - summarize - this function provides the print output similar to the function
    in Stata with the same name
  - tab - a function that is similar to tab function in Stata, for now take only
    one or two arguments.
  - the arguments passed into function 'summarize' should be a list of column
    names represented as a list of strings, and a pandas DataFrame, where all
    those columns can be found in.
  - the arguments passed into function 'tab': can be one pandas Series (as in a
    dataframe column) or two pandas series (as in two columns of a pandas
    dataframe). Both entered separately.

## Example 1: summarize

```
import StataLovers
StataLovers.summarize(["BirthYear", "Year", "Married", "Health"], df)
```
**Output**

```
     Variable |        Obs        Mean    Std. Dev.       Min        Max
--------------+----------------------------------------------------------
    BirthYear |    59807.0    1913.154      245.723       -8.0     1987.0
         Year |    59807.0    2011.708        3.404     2006.0     2017.0
      Married |    59807.0       0.717        0.451        0.0        1.0
       Health |    59767.0       2.856        0.853        1.0        4.0
```

## Example 2: tab

```
StataLovers.tab(df['Health'])
```
**Output**
```
      Health|      Freq.     Percent        Cum.
------------+-----------------------------------
         1.0|       4649       7.779       7.779
       1.333|        683       1.143       8.921
       1.667|       1947       3.258      12.179
         2.0|       5938       9.935      22.114
       2.333|       3648       6.104      28.218
       2.667|       5689       9.519      37.737
         3.0|      17681      29.583       67.32
       3.333|       4934       8.255      75.575
       3.667|       4651       7.782      83.357
         4.0|       9947      16.643       100.0
------------+-----------------------------------
      Total |      59767      100.00
```

## Example 3: tab

```
StataLovers.tab(df["Health"], df["Female"])
```
**Output**

```
             |      Female
      Health |           0           1|     Total
-------------+------------------------+----------
         1.0 |        2052        2597|      4649
       1.333 |         404         279|       683
       1.667 |         909        1038|      1947
         2.0 |        2196        3742|      5938
       2.333 |        1752        1896|      3648
       2.667 |        2466        3223|      5689
         3.0 |        7074       10607|     17681
       3.333 |        2500        2434|      4934
       3.667 |        2160        2491|      4651
         4.0 |        5045        4902|      9947
-------------+------------------------+----------
       Total |       26581       33226|     59807
```

## Note

- Contributions are welcome. Contact: kamilakolpashnikova@gmail.com

## Author

Kamila Kolpashnikova 2021