vizard

Intuitive, Easy and Quick Visualizations for Data Science Projects

Installation

pip install vizard

pip install git+https://github.com/Ritvik19/vizard.git

Documentation

Instantiate Vizard Object

The Vizard object holds the DataFrame along with its configurations including the PROBLEM_TYPE, DEPENDENT_VARIABLE, CATEGORICAL_INDEPENDENT_VARIABLES, CONTINUOUS_INDEPENDENT_VARIABLES, and TEXT_VARIABLES

import vizard

class config:
    PROBLEM_TYPE = 'regression' or 'classification'
    DEPENDENT_VARIABLE = 'target_variable'
    CATEGORICAL_INDEPENDENT_VARIABLES = [categorical_features]
    CONTINUOUS_INDEPENDENT_VARIABLES = [continuous features]
    TEXT_VARIABLES = [text features]

viz = vizard.Vizard(df, config)

Exploratory Data Analysis

After Instatiating the Vizard object, you can try different plots for EDA

Check Missing Values:
```
viz.check_missing()
```
Count of Missing Values:
```
viz.count_missing()
```
Count of Unique Values:
```
viz.count_unique()
```

Count of Missing Values by Group:

viz.count_missing_by_group(class_variable)

Count of Unique Values by Group:

viz.count_unique_by_group(class_variable)

Target Column Analysis

Based on the type of problem, perform a univariate analysis of target column

viz.dependent_variable()

Segmented Univariate Analysis

Based on the type of problem, preform segmented univariate analysis of all feature columns with respect to the target column

Categorical Variables
```
  viz.categorical_variables()
```
Continuous Variables
```
  viz.continuous_variables()
```

Text Variables

  viz.wordcloud()

  viz.wordcloud_freq()

Bivariate/Multivariate Analysis

Based on the type of problem, perform bivariate and multivariate analysis on all the feature columns

Pairwise Scatter
```
  viz.pairwise_scatter()
```
Pairwise Violin
```
  viz.pairwise_violin()
```
Pairwise Cross Tabs
```
  viz.pairwise_crosstabs()
```

Correlation Analysis

Based on the type of variables, perform correaltion analysis on all the feature columns

Correlation Plot
```
  viz.corr_plot()
```
Pair Plot
```
  viz.pair_plot()
```
Chi Square Plot
```
  viz.chi_sq_plot()
```

kashy64/vizard