Skip to main content

A python library to help do reproducible research in social sciences

Project description

Soscipy

This library attempts to solve some of the most basic challenges with data science pipelines and analysis. Some of the most repeated functions have been extracted while some other useful tools have been added.

There are four different parts to the library that talks to specific needs while working with data.

  1. Data analysis
  2. Data processing
  3. Data visualisation
  4. Utilities

1. Data Analysis

dat2csv: A simple module to export data into a csv file

2. Data processing

Combine Takes two dataframes as input and exports a merged dataframe automatically. It figures out a primary key for the dataset and utilised TfIdf to match entities before merging

from socipy.process.rename_pd import rename_pd
df = rename_pd(df,[col1,col2,col3],[new_col1,new_col2,new_col3])

Thin Panda: A set of commonly used pandas functions such as renaming the columns etc.

Parallelize: A simple wrapper that takes a function and list of parameters and runs them in parallel to help you save the time and effort of dealing with more complicated multi-processing tools

3. Data visualisation

Plot: Simple functions to quickly export visualised graphs

from kornect.plot import sns_cntplt_array
sns_cntplt_array([1,2,2,3,3,4],chart_title='Random chart',export=False) 

Count Plot Chart

istates: Takes a dataframe with state names and values and plots a geomap of India for you as a PNG or GIF

idistrict: Takes a dataframe with district names and values and plots a geomap of India for you as a PNG or GIF

4. Utilities

Browser: Creates a selenium browser for you Update Progress: This takes a float as an input and creates a beautiful progress bar and shows you the percentage. No added libraries just pure python implementation.

from kornect.utilities import update_progress
import time

for i in range(100):
    update_progress(i/100.0)
    time.sleep(0.01)

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

soscipy-0.0.3.tar.gz (7.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

soscipy-0.0.3-py3-none-any.whl (7.7 kB view details)

Uploaded Python 3

File details

Details for the file soscipy-0.0.3.tar.gz.

File metadata

  • Download URL: soscipy-0.0.3.tar.gz
  • Upload date:
  • Size: 7.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.2

File hashes

Hashes for soscipy-0.0.3.tar.gz
Algorithm Hash digest
SHA256 46b53cdc7fc4f4b36558926420875e7c7c08628a0756a837aeb6b7b2d0b9ffd5
MD5 79971b788f92e1389b4c31d2aaa78e53
BLAKE2b-256 3224be823388df67f262bf2a081360241e0006bd13a66038ee504ab2544484cc

See more details on using hashes here.

File details

Details for the file soscipy-0.0.3-py3-none-any.whl.

File metadata

  • Download URL: soscipy-0.0.3-py3-none-any.whl
  • Upload date:
  • Size: 7.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.2

File hashes

Hashes for soscipy-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 719934289d9447ed6857489a1ada073ae7423ff343524385d8750c24f2560c40
MD5 18dccb03fdfef98f902ffdc0b2a4c7ac
BLAKE2b-256 2ae7a9749423ed9de5b8d58e2980f9659ac255eda8e9bdb47dee59a7ba80a249

See more details on using hashes here.

Supported by

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