Python Package that performs Exploratory Data Analysis

exploredata is built on Pandas and Numpy. It gives an overview of a csv data file.

• It imports csv file and returns the summary of the data in the file using the Pandas Dataframe.info() function.
• It contains method (null_cat and null_num) that returns the number of missing categorical and numerical features respectively
• It also has method that returns the number of numerical and categorical features as well the number of features containing outliers
• It also contains method (num_viz and cat_viz) that plot histogram and boxplot for each numerical variable as well as the count plot for each categorical variables.

Installing

pip install exploredata

Usage

• import exploredata as ep #imports the exploredata package

• new_variable = ep.EDA(file path) #calls the EDA module in the package. The module import your csv file and assign it as a pandas dataframe to the variable 'train'. It also returns the summarry of the data

• new_variable.df #prints the pandas dataframe

• new_variable.num_var() #returns a tuple containing the number and the list of numerical variables in the dataframe

• train.null_var() #returns a tuple containing the number and the list of numerical variables containing null values

• help(ep.EDA) #provide information on all methods defined in the EDA module