Metadata-Version: 2.1
Name: datastand
Version: 2.4.3
Summary: A python package to help Data Scientists, Machine Learning Engineers and Analysts      better understand data. Gives quick insights about given data; general dataset statistics, size and      shape of dataset, number of unique data types, number of numerical and non-numerical columns, small      overview of dataset, missing data statistics, missing data heatmap and provides methodology to impute      missing data.
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 Data Scientists, Machine Learning Engineers and Analysts better understand data. Gives quick insights about a given dataset.  
        
        
        ------------------
        
        # Installation
        Run the following command on the terminal to install the package:
        ```python
        pip install datastand
        ```
        ### Usage :
        Code:
        ```python
        from 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
        
        
        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 import plot_missing
        
        plot_missing(df)
        
        ```
        Output:
        
        ![missing data heatmap](images/missing_data_heatmap.png)
        
        Code:
        ```python
        from 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 N.**
        [[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
