rdoume / New_entities.py

Created February 4, 2020 14:34

	def getTopNewEntities(conn, country, category=None, window=-2, limit=100, count=None):
	numday = window
	now = pendulum.now(tz='Europe/Paris')
	all_en = []
	cur = conn.cursor()
	for i in range(0, abs(numday)):
	from_date = now.subtract(days=abs(numday + i)).to_datetime_string()
	to_date = now.subtract(days=abs(numday + i + 1)).to_datetime_string()
	query = getQueryTopEntity(from_date, to_date, country, category)
	# cur = conn.cursor()

rdoume / Install_Cuda.sh

Created January 21, 2020 17:21

	#!/bin/bash
	#Ubuntu28.04
	curl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
	sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
	sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
	sudo apt-get update
	sudo apt-get install cuda
	conda install pytorch torchvision cudatoolkit=10.1 -c pytorch

rdoume / Install_Cuda.sh

Created January 21, 2020 17:21

	#!/bin/bash
	#Ubuntu28.04
	curl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
	sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
	sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
	sudo apt-get update
	sudo apt-get install cuda
	conda install pytorch torchvision cudatoolkit=10.1 -c pytorch

rdoume / Sponsored

Created January 14, 2020 09:22

	SPONSORED_HASHTAGS = ["#ad", "#brandambassador", "#collaboration", "#disclosure", "#gift", "#gifted", "#giftedby",
	"#giftfrom", "#partner", "#promo", "#promotion", "#sp", "#spon", "#sponsored", "#sponsor",
	"#sponsorship", "#sponsoreret", "#sponsoredpost", ""]

	SPONSORED_PHRASES = ["brought to you by", "compensated by", "gift from", "gifted by", "in collaboration with",
	"collaborated with", "in partnership with", "paid ad", "paid advertisement", "paid by",
	"paid for by", "paid partnership with", "paid post", "paid promo", "paid promotion",
	"paid sponsorship", "partnered up with", "partnered with", "partnering with", "partnership with",
	"sponsored by", "sponsored post", "teamed up with", "teamed with", "teaming up with",
	"teaming with", "brand partner", "working with", "promo code", "coupon code", "discount code",

rdoume / Make Spinx.md

Created May 28, 2019 13:17

You must ensure that there is a folder docs in your main folder. This folder docs must have:

rdoume / Package for Data.md

Last active December 7, 2020 18:31

Awesome Data Science with Python

rdoume / tfidf

Created October 25, 2018 20:42


	def getTopNewEntities(conn, country, category=None, window=-2, limit=100, count=None):
	numday = window
	now = pendulum.now(tz='Europe/Paris')
	all_en = []
	cur = conn.cursor()
	for i in range(0, abs(numday)):
	from_date = now.subtract(days=abs(numday + i)).to_datetime_string()
	to_date = now.subtract(days=abs(numday + i + 1)).to_datetime_string()
	query = getQueryTopEntity(from_date, to_date, country, category)

rdoume / categorical_encoder.py

Created August 17, 2018 12:29

	# coding: utf-8
	# Author: Axel ARONIO DE ROMBLAY <[email protected]>
	# License: BSD 3 clause

	import numpy as np
	import pandas as pd
	import warnings

	import os

rdoume / useful_pandas_snippets.py

Created November 18, 2017 19:25 — forked from bsweger/useful_pandas_snippets.md

Useful Pandas Snippets

	# List unique values in a DataFrame column
	# h/t @makmanalp for the updated syntax!
	df['Column Name'].unique()

	# Convert Series datatype to numeric (will error if column has non-numeric values)
	# h/t @makmanalp
	pd.to_numeric(df['Column Name'])

	# Convert Series datatype to numeric, changing non-numeric values to NaN
	# h/t @makmanalp for the updated syntax!

rdoume / useful_pandas_snippets.py

Created November 18, 2017 19:25 — forked from bsweger/useful_pandas_snippets.md

Useful Pandas Snippets

	# List unique values in a DataFrame column
	# h/t @makmanalp for the updated syntax!
	df['Column Name'].unique()

	# Convert Series datatype to numeric (will error if column has non-numeric values)
	# h/t @makmanalp
	pd.to_numeric(df['Column Name'])

	# Convert Series datatype to numeric, changing non-numeric values to NaN
	# h/t @makmanalp for the updated syntax!

Robin rdoume