{% for var in CategoriesCount %} {% endfor %} {% for var in ContinuousSummary %} {% endfor %}

Pre-Modelling ExploriPy

List Of Fields

{% for field in ListOfFields %} {% endfor %}
Field Type
{{ loop.index0 + 1 }} {{field["name"]}} {{field["type"]}}

Categorical Vs Continuous

Continuous Variables
    {% for field in ContinuousFeatures %}
  • {{ field }}
  • {% endfor %}
Categorical Variables
    {% for field in CategoricalFeatures %}
  • {{ field }}
  • {% endfor %}
Other Variables
    {% for field in OtherFeatures %}
  • {{ field }}
  • {% endfor %}
Null Values
Null Percentage
{% for key, row in NullValue.iterrows() %} {% endfor %}
Feature Percentage
{{row["Feature"]}} {{row["NullPercentage"]}}%

Null Percentage

Continuous Variables
{% for var in ContinuousSummary %}

{{ var['Name'] }}

Statistic Value
Count {{var['Count']|round(2)}}
Mean {{var['Mean']|round(2)}}
Median {{var['Median']|round(2)}}
Std Dev {{var['STD']|round(2)}}
Min {{var['Min']|round(2)}}
25% {{var['TwentyFive']|round(2)}}
50% {{var['Fifty']|round(2)}}
75% {{var['SeventyFive']|round(2)}}
Max {{var['Max']|round(2)}}
Variance {{var['Variance']|round(4)}}
Kurtosis {{var['kurtosis']|round(4)}}
skew {{var['skew']|round(4)}}
{% endfor %}

Correlation Heatmap

Scatter Plot

Feature Reduction

Multi-Co-linearity check through VIF
{% for key, row in VIF_columns.iterrows() %} {% endfor %}
Feature VIF
{{row["column"]}} {{row["vif"]|round(3)}}
Variance
{% for key, row in Variance.iterrows() %} {% endfor %}
Feature Variance
{{row["column"]}} {{row["variance"]|round(3)}}

Categorical Variables

{% for var in CategoriesCount %}

{{ var['Variable'] }}

{% for key, row in var['Count'].iterrows() %} {% endfor %}
Category Number of Records
{{key}} {{row["Value"]}}
{% endfor %}

Summary based on Information Value and ChiSquare Test of Independence

Target Variable

Based on IV

Strong Predictors
{% for key, row in IVStrongPredictor.iterrows() %} {% endfor %}
Target Feature IV
{{row["DependentVar"]}} {{row["IndependentVar"]}} {{row["IV"]}}
Weak Predictors
{% for key, row in IVWeakPredictor.iterrows() %} {% endfor %}
Target Feature IV
{{row["DependentVar"]}} {{row["IndependentVar"]}} {{row["IV"]}}

Based on Chi Square

Dependent Features
{% for key, row in ChiSqDependent.iterrows() %} {% endfor %}
Target Feature Chi Square P-Value
{{row["DependentVar"]}} {{row["IndependentVar"]}} {{row["ChiSq"]|round(5)}} {{row["PValue"]|round(5)}}
Independent Features
{% for key, row in ChiSqIndependent.iterrows() %} {% endfor %}
Target Feature Chi Square P-Value
{{row["DependentVar"]}} {{row["IndependentVar"]}} {{row["ChiSq"]|round(5)}} {{row["PValue"]|round(5)}}

Weight Of Evidence, Information Value and ChiSquare Test of Independence

Independent Variable

Target Variable

{% for entry in WOEList %}
{% endfor %}
Categorical Vs Continuous

Summary based on Anova

Target Variable

Based on Anova

Influencing Categorical Feature
{% for key, row in AnovaInfluencing.iterrows() %} {% endfor %}
Target Categorical Feature PValue
{{row["Continuous"]}} {{row["Categorical"]}} {{row["PValue"]}}
NonInfluencing Categorical Feature
{% for key, row in AnovaNonInfluencing.iterrows() %} {% endfor %}
Target Categorical Feature PValue
{{row["Continuous"]}} {{row["Categorical"]}} {{row["PValue"]}}

Categorical Variable

Continuous Variable

{% for entry in AnovaList %} {% endfor %}