Metadata-Version: 2.1
Name: DataStand
Version: 1.2
Summary: A python package that helps Data Scientists, Machine Learning Engineers and Analysts to quickly explore and understand a dataset.
Home-page: https://github.com/lyraxvincent/DataStand
Author: Vincent Njonge
Author-email: njongevincent@gmail.com
License: MIT  
Description: # DataStand
        
        -----------
        ![package logo](images/logo.jpg)
        Why DataStand? __Data + Understand__  
        A python package to help users especially Data Scientists, Machine Learning Engineers and Analysts to better understand DATA. Gives quick insights about given Data.  
        
        
        ------------------
        
        # Installation
        Run the following command on the terminal to install the package:
        ```python
        pip install DataStand
        ```
        ### Usage :
        Code:
        ```python
        from DataStand.DataStand import DataStand
        import pandas as pd
        
        df = pd.read_csv("path/to/target/dataframe")
        
        DataStand(df)
        
        ```
        Output:
        ```python
        
        General stats:
        ______________
        Size of DataFrame: 309200
        Shape of DataFrame: (3865, 80)
        Number of unique data types : {dtype('int64'), dtype('O'), dtype('float64')}
        Number of numerical columns: 79
        Number of non-numerical columns: 1
        
        Head of DataFrame:
        __________________
           galactic year                        galaxy  existence expectancy index  ...  Private galaxy capital flows (% of GGP)  Gender Inequality Index (GII)         y
        0         990025  Large Magellanic Cloud (LMC)                    0.628657  ...                                      NaN                            NaN  0.052590
        1         990025              Camelopardalis B                    0.818082  ...                                22.785018                            NaN  0.059868
        2         990025                       Virgo I                    0.659443  ...                                      NaN                            NaN  0.050449
        3         990025            UGC 8651 (DDO 181)                    0.555862  ...                                      NaN                            NaN  0.049394
        4         990025                  Tucana Dwarf                    0.991196  ...                                      NaN                            NaN  0.154247
        
        [5 rows x 80 columns]
        
        Tail of DataFrame:
        __________________
              galactic year                        galaxy  existence expectancy index  ...  Private galaxy capital flows (% of GGP)  Gender Inequality Index (GII)         y
        3860        1015056                     Columba I                    1.029704  ...                                29.294865                       0.580785  0.042324
        3861        1015056  Leo II Dwarf (Leo B, DDO 93)                    0.937869  ...                                31.085400                       0.517558  0.036725
        3862        1015056        Canes Venatici I Dwarf                    1.036144  ...                                32.145570                       0.363862  0.166271
        3863        1015056                         KKs 3                    0.939034  ...                                27.227179                       0.711878  0.024187
        3864        1015056                      NGC 5237                    1.032244  ...                                29.957851                       0.583706  0.100069
        
        [5 rows x 80 columns]
        
        Missing data:
        =======================
        DataFrame contains 185698 missing values(60.06%) as follows column-wise:
        -----------------------------------------------------------------------
        galactic year                                                                   0
        galaxy                                                                          0
        existence expectancy index                                                      1
        existence expectancy at birth                                                   1
        Gross income per capita                                                        28
                                                                                     ... 
        Adjusted net savings                                                         2953
        Creature Immunodeficiency Disease prevalence, adult (% ages 15-49), total    2924
        Private galaxy capital flows (% of GGP)                                      2991
        Gender Inequality Index (GII)                                                3021
        y                                                                               0
        Length: 80, dtype: int64
        -----------------------------------------------------------------------
        
        Do you wish to long-list missing data statistics?(y/n): y
        .
        .
        .
        ```
        Code:
        ```python
        # This function is already available in the DataStand class and also available separately
        # Here we're running it separately 
        from DataStand.DataStand import plot_missing
        
        plot_missing(df)
        
        ```
        Output:
        
        ![missing data heatmap](images/missing_data_heatmap.png)
        
        Code:
        ```python
        from DataStand.DataStand import impute_missing
        
        impute_missing(df)
        
        ```
        Output:
        ```python
        Imputing missing data...
        100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 80/80 [00:02<00:00, 30.52it/s]
        Imputation complete.
        ```
        ## Author/Maintainer
        **Vincent Njonge.**
        [[LinkedIn]](https://www.linkedin.com/in/vincent-njonge-528070178)  [[Twitter]](https://twitter.com/lyraxvincent)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
