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View dash_simple_example_pandas_datareader.py
import dash
from dash.dependencies import Input, Output
import dash_core_components as dcc
import dash_html_components as html
from pandas_datareader import data as web
from datetime import datetime as dt
app = dash.Dash('Hello World')
View dash_crossfilter_example.py
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
import pandas as pd
app = dash.Dash()
df = pd.read_csv(
'https://gist.githubusercontent.com/chriddyp/'
@gachet
gachet / producer_consumer.py
Last active Dec 10, 2019 — forked from cristipufu/producer_consumer.py
Producer-consumer problem in python
View producer_consumer.py
import sys
import random
import time
from threading import *
class Producer(Thread):
def __init__(self, items, can_produce, can_consume):
Thread.__init__(self)
self.items = items
self.can_produce = can_produce
@gachet
gachet / Assignment2 (1).ipynb
Created Nov 21, 2018 — forked from GeorgyGol/Assignment2 (1).ipynb
Assignment 2 for Week 2 of Applied Plotting, Charting and Data Representation in Python Coursera course
View Assignment2 (1).ipynb
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View test_pyspark.ipynb
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@gachet
gachet / Ubidots_PubSubClient_Example.ino
Created Mar 3, 2018 — forked from jotathebest/Ubidots_PubSubClient_Example.ino
This script is a basic example for sending data to Ubidots using the PubSubClient library. It is useful for developers that want to make their own libraries to connect their devices.
View Ubidots_PubSubClient_Example.ino
/****************************************
* Include Libraries
****************************************/
#include <PubSubClient.h>
#include <ESP8266WiFi.h>
#include <ESP8266WiFiMulti.h>
#include <stdio.h>
View annoytutorial-text8.ipynb
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@gachet
gachet / gensim_word2vec_demo.py
Created Jun 13, 2017 — forked from bhaettasch/gensim_word2vec_demo.py
Use gensim to load a word2vec model pretrained on google news and perform some simple actions with the word vectors.
View gensim_word2vec_demo.py
from gensim.models import Word2Vec
# Load pretrained model (since intermediate data is not included, the model cannot be refined with additional data)
model = Word2Vec.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True, norm_only=True)
dog = model['dog']
print(dog.shape)
print(dog[:10])
# Deal with an out of dictionary word: Михаил (Michail)
@gachet
gachet / word2vec_tweets_preprocessor.py
Created Jun 13, 2017 — forked from ravyg/word2vec_tweets_preprocessor.py
Clean tweets json for tensorflow or gensim based word2vec plain text
View word2vec_tweets_preprocessor.py
# -*- coding: utf-8 -*-
import json
import re
import os
import nltk
input_file = open('<JSON FILE To INPUT>','r').readlines()
for line in input_file:
try:
tweet = json.loads(line)