xplore 0.0.1
A python package built with pandas for data scientist/analysts, AI/ML engineers for exploring features of a dataset in minimal number of lines of code for quick analysis before data wrangling and feature extraction.
Requires Python: >=3.6
Keywords: Data-Science,Machine-Learning,python

# xplore
---
xplore is a python package built with Pandas for data scientist or analysts, AI/ML engineers or researchers for exploring features of a dataset in one line of code for quick analysis before data wrangling and feature extraction. You can also choose to generate a more detailed report on the exploration of your dataset upon request.
---
## Getting started

### Install the package
```bash
pip install xplore
```

### Import the package into your code
```python
from xplore.data import xplore
```

### Assign the read/open command to the file path or URL of your structured dataset to a variable name 
```python
data = < Read in your dataset file here >
```

### Explore your dataset using the xplore() method
```python
xplore(data)
```
---

### Testing xplore
Navigate to the test.py file after installing the package and run the code in that file to see and understand how xplore works.
---

## Sample Output
```python
------------------------------------
The fist 5 entries of your dataset are:

   rank country_full country_abrv  total_points  ...  three_year_ago_avg  three_year_ago_weighted  confederation   rank_date
0     1      Germany          GER           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
1     2        Italy          ITA           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
2     3  Switzerland          SUI           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
3     4       Sweden          SWE           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
4     5    Argentina          ARG           0.0  ...                 0.0                      0.0       CONMEBOL  1993-08-08

[5 rows x 16 columns]


------------------------------------
The last 5 entries of your dataset are:

       rank country_full country_abrv  total_points  ...  three_year_ago_avg  three_year_ago_weighted  confederation   rank_date
57788   206     Anguilla          AIA           0.0  ...                 0.0                      0.0       CONCACAF  2018-06-07
57789   206      Bahamas          BAH           0.0  ...                 0.0                      0.0       CONCACAF  2018-06-07
57790   206      Eritrea          ERI           0.0  ...                 0.0                      0.0            CAF  2018-06-07
57791   206      Somalia          SOM           0.0  ...                 0.0                      0.0            CAF  2018-06-07
57792   206        Tonga          TGA           0.0  ...                 0.0                      0.0            OFC  2018-06-07

[5 rows x 16 columns]


------------------------------------
Stats on your dataset:

<bound method NDFrame.describe of        rank country_full country_abrv  total_points  ...  three_year_ago_avg  three_year_ago_weighted  confederation   rank_date
0         1      Germany          GER           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
1         2        Italy          ITA           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
2         3  Switzerland          SUI           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
3         4       Sweden          SWE           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
4         5    Argentina          ARG           0.0  ...                 0.0                      0.0       CONMEBOL  1993-08-08
...     ...          ...          ...           ...  ...                 ...                      ...            ...         ...
57788   206     Anguilla          AIA           0.0  ...                 0.0                      0.0       CONCACAF  2018-06-07
57789   206      Bahamas          BAH           0.0  ...                 0.0                      0.0       CONCACAF  2018-06-07
57790   206      Eritrea          ERI           0.0  ...                 0.0                      0.0            CAF  2018-06-07
57791   206      Somalia          SOM           0.0  ...                 0.0                      0.0            CAF  2018-06-07
57792   206        Tonga          TGA           0.0  ...                 0.0                      0.0            OFC  2018-06-07

[57793 rows x 16 columns]>


------------------------------------
The Value types of each column are:

rank                         int64
country_full                object
country_abrv                object
total_points               float64
previous_points              int64
rank_change                  int64
cur_year_avg               float64
cur_year_avg_weighted      float64
last_year_avg              float64
last_year_avg_weighted     float64
two_year_ago_avg           float64
two_year_ago_weighted      float64
three_year_ago_avg         float64
three_year_ago_weighted    float64
confederation               object
rank_date                   object
dtype: object


------------------------------------
Info on your Dataset:

<bound method DataFrame.info of        rank country_full country_abrv  total_points  ...  three_year_ago_avg  three_year_ago_weighted  confederation   rank_date
0         1      Germany          GER           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
1         2        Italy          ITA           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
2         3  Switzerland          SUI           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
3         4       Sweden          SWE           0.0  ...                 0.0                      0.0           UEFA  1993-08-08
4         5    Argentina          ARG           0.0  ...                 0.0                      0.0       CONMEBOL  1993-08-08
...     ...          ...          ...           ...  ...                 ...                      ...            ...         ...
57788   206     Anguilla          AIA           0.0  ...                 0.0                      0.0       CONCACAF  2018-06-07
57789   206      Bahamas          BAH           0.0  ...                 0.0                      0.0       CONCACAF  2018-06-07
57790   206      Eritrea          ERI           0.0  ...                 0.0                      0.0            CAF  2018-06-07
57791   206      Somalia          SOM           0.0  ...                 0.0                      0.0            CAF  2018-06-07
57792   206        Tonga          TGA           0.0  ...                 0.0                      0.0            OFC  2018-06-07

[57793 rows x 16 columns]>


------------------------------------
The shape of your dataset in the order of rows and columns is:

(57793, 16)


------------------------------------
The features of your dataset are:

Index(['rank', 'country_full', 'country_abrv', 'total_points',
       'previous_points', 'rank_change', 'cur_year_avg',
       'cur_year_avg_weighted', 'last_year_avg', 'last_year_avg_weighted',
       'two_year_ago_avg', 'two_year_ago_weighted', 'three_year_ago_avg',
       'three_year_ago_weighted', 'confederation', 'rank_date'],
      dtype='object')


------------------------------------
The total number of null values from individual columns of your data set are:

rank                       0
country_full               0
country_abrv               0
total_points               0
previous_points            0
rank_change                0
cur_year_avg               0
cur_year_avg_weighted      0
last_year_avg              0
last_year_avg_weighted     0
two_year_ago_avg           0
two_year_ago_weighted      0
three_year_ago_avg         0
three_year_ago_weighted    0
confederation              0
rank_date                  0
dtype: int64


------------------------------------
The number of rows in your dataset are:

57793


------------------------------------
The values in your dataset are:

[[1 'Germany' 'GER' ... 0.0 'UEFA' '1993-08-08']
 [2 'Italy' 'ITA' ... 0.0 'UEFA' '1993-08-08']
 [3 'Switzerland' 'SUI' ... 0.0 'UEFA' '1993-08-08']
 ...
 [206 'Eritrea' 'ERI' ... 0.0 'CAF' '2018-06-07']
 [206 'Somalia' 'SOM' ... 0.0 'CAF' '2018-06-07']
 [206 'Tonga' 'TGA' ... 0.0 'OFC' '2018-06-07']]


------------------------------------


Do you want to generate a detailed report on the exploration of your dataset?
[y/n]:
```
---

## Contributing to xplore
Fork and clone this repo if you have any contributions you want to make. 
Push your commits to a new branch and send a PR when done.
I'll review your code and merge your PR as soon as possible.

## Maintainers: 
[Jerry Buaba](https://www.linkedin.com/in/buabaj/) | 
[Labaran Mohammed](https://linkedin.com/in/adam-labaran-111358181) | 
[Benjamin Acquaah](https://linkedin.com/in/benjamin-acquaah-9294aa14b)