Skip to main content

Exploratory Data Analysis

Project description

exploratory

Exploratory Data Analysis

Description

This project explortory was created to perform Exploratory Data Analysis on any structured dataset. Dataset can have categorical or numerical data types. This project takes pandas dataframe and gives summary statistics and individual plots having categorical count for catagorical variables and PDF's, CDF's with mean, median and mode for numerical variables. The both the results are stored in PDF and CSV file in your current directory/path.

Installation:

Use the package manager pip to install exploratory

pip install exploratory

Usage:

from exploratory import EDA
EDA(df)
# df --> pandas dataframe
#Please input the DPI value, as DPI value increases runtime would increase. Defualt DPI value: 150

Contributing

Pull requests are welcome. Please use this 'https://github.com/Abhilash-MS/exploratory' Please feel free to contact authors for any suggestions or issues, Ram kakarlaramcharan@gmail.com, Abhilash abhilashmaspalli1996@gmail.com

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

exploratory-3.4.3.tar.gz (6.0 kB view details)

Uploaded Source

File details

Details for the file exploratory-3.4.3.tar.gz.

File metadata

  • Download URL: exploratory-3.4.3.tar.gz
  • Upload date:
  • Size: 6.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.12

File hashes

Hashes for exploratory-3.4.3.tar.gz
Algorithm Hash digest
SHA256 538a617b7540ff0bec38450d5535ca50a7cb706091b0fc346d4895961fd2c39a
MD5 a9b94fd2c51d33d2c66a778071b2a915
BLAKE2b-256 d24abd84c5182d812d882904be3a601d98dc88f600c01b3a61b2e1ec8340bb69

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page