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Ediscere, Scire, Agere, Vincere

Henrique Gomide henriquepgomide

:octocat:
Ediscere, Scire, Agere, Vincere
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@MrEliptik
MrEliptik / text_preprocessing.py
Created Jan 14, 2019
A python script to preprocess text (remove URL, lowercase, tokenize, etc..)
View text_preprocessing.py
import re, string, unicodedata
import nltk
import contractions
import inflect
from nltk import word_tokenize, sent_tokenize
from nltk.corpus import stopwords
from nltk.stem import LancasterStemmer, WordNetLemmatizer
def replace_contractions(text):
"""Replace contractions in string of text"""
@conormm
conormm / r-to-python-data-wrangling-basics.md
Last active Jun 20, 2021
R to Python: Data wrangling with dplyr and pandas
View r-to-python-data-wrangling-basics.md

R to python data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. The beauty of dplyr is that, by design, the options available are limited. Specifically, a set of key verbs form the core of the package. Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).

dplyr is organised around six key verbs: