Metadata-Version: 2.1
Name: xplore
Version: 0.0.1
Summary: 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.
Home-page: https://github.com/buabaj/xplore
Author: Jerry Buaba
Author-email: buabajerry@gmail.com
License: UNKNOWN
Download-URL: https://github.com/buabaj/xplore/archive/v0.0.1.tar.gz
Description: # 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)
Keywords: Data-Science,Machine-Learning,python
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
