eda-SQL 0.0.1

Exploratory Data Analytics tool for SQL

SQL Bridge to Exploratory Data Analysis Tool

edaSQL is a library to link SQL to Exploratory Data Analysis and further more in the Data Engineering. This will solve many limitations in the SQL studios available in the market.

Installation

Clone this Repository. Run this from the root directory to install

python setup.py install

Documentation

Import Packages

import edaSQL
import pandas as pd

1. Connect to the DataBase

edasql = edaSQL.SQL()
edasql.connectToDataBase(server='your server name', 
                         database='your database', 
                         user='username', 
                         password='password')

2. Query Data

sampleQuery = "select  * from INX"
data = pd.read_sql(sampleQuery, edasql.dbConnection)

3. Data Overview

insights =  edaSQL.EDA(dataFrame=data,HTMLDisplay=True)
dataInsights =insights.dataInsights()
deepInsights = insights.deepInsights()

4.Correlation

eda = edaSQL.EDA(dataFrame=data)
eda.pearsonCorrelation()
eda.spearmanCorrelation()
eda.kendallCorrelation()

5. Missing Values

eda.missingValuesPlot(plot ='matrix')
eda.missingValuesPlot(plot ='bar')
eda.missingValuesPlot(plot ='heatmap')
eda.missingValuesPlot(plot ='dendrogram')

6. Outliers

eda.outliersVisualization(plot = 'box')
eda.outliersVisualization(plot = 'scatter')
outliers = eda.getOutliers()

Jupyter NoteBook Tutorial