smartvis 0.0.2

Package to Visualize Columns Relationships in Ease.

SmartVis

A PY Library that can visualize Data Frames Columns in a Ease.

Installation and About

pip install smartvis

This is a wrap around Plotly for accessing the relationship between dataframe columns. This package cuts the cost of manual entry to find the realtionship between columns.

Parameters in visualizeEverything function

visualizeEverything(df, iColumns, maxGraph, maxPermutations, permute)

• df: DataFrame that needs to be passed, which needs to be visualized (Cleaned DF is preferred).
• iColumns (Optional): Takes a list of column names which nees to be visualized specifically.
• maxGraph (Optional): Takes an Integer, that plots maximum number of graphs, if set to one, will plot 1 graph.
• maxPermutations (Optional): Takes an Integer, that plots maximum number of column combinations.
• permute (Optional): Takes a bool, returns Permutation or Combination sorting. (Reference to know more)

Example Usage

Example Cleaned DataSet:

	Name	Age	City
0	Alice	25	New York
1	Bob	30	San Francisco
2	Charlie	22	Chicago

1. After Installing:

   pip install smartvis
   

2. Import the package to the file:

   from smartvis import visualizeEverything
   

   or

   from smartvis import visualizeEverything as ve
   

3. Code for Visualizing

   • Senario 1:

     from smartvis import visualizeEverything
     import pandas as pd
     df=pd.read_csv("cleanedDS.csv")
     visualizeEverything(df,maxGraph=2, maxPermutations=2)
     

     Plots a Scatter Plot of 2 Graphs:

     1. Name and Age
     2. Age and City

   • Senario 2:

     from smartvis import visualizeEverything as ev
     import pandas as pd
     df=pd.read_csv("cleanedDS.csv")
     ve(df,maxGraph=2, maxPermutations=2,premute=True)
     

     Will get an error, Both maxGraph and maxPermutations can't be not None if permute is True

   • Senario 3:

     from smartvis import visualizeEverything as ev
     import pandas as pd
     df=pd.read_csv("cleanedDS.csv")
     ve(df,maxGraph=1,premute=True)
     

     Plots a Scatter Plot of 1 Graph:

     1. Name and Age

   • Senario 4:

     from smartvis import visualizeEverything as ev
     import pandas as pd
     df=pd.read_csv("cleanedDS.csv")
     ve(df,iColumns=["Age","City"],maxGraph=2,maxPermutations=1)
     

     Plots a Scatter Plot of 1 Graph: (will only plot one graph as premute is false and it won't return more than 1 Graph for one Column)

     1. Name and Age

   • Senario 5:

     from smartvis import visualizeEverything as ev
     import pandas as pd
     df=pd.read_csv("cleanedDS.csv")
     ve(df, maxPermutations=3,premute=True)
     

     Will show an error as permute can't be True when maxPermutations is not None