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bitcoin = cryptos[0]
bitcoin_cash = cryptos[1]
dash = cryptos[2]
ethereum_classic = cryptos[3]
bitconnect = cryptos[4]
litecoin = cryptos[5]
monero = cryptos[6]
nem = cryptos[7]
neo = cryptos[8]
numeraire = cryptos[9]
#!/usr/bin/env python
# coding: utf-8
# ## Perform Chi-Square test for Bank Churn prediction (find out different patterns on customer leaves the bank) . Here I am considering only few columns to make things clear
# ### Import libraries
# In[2]:
SELECT m.* FROM #matches m
INNER JOIN #matches m1 ON m.fromid = m1.toid AND m.toid = m1.fromid AND m1.fromid <=m1.toid
ORDER BY m.toteam
SELECT t.id fromid,t.Team fromteam,t1.id toid,t1.Team toteam
INTO #matches
FROM #Team t
INNER JOIN #Team t1 ON t.id <> t1.id
SELECT * FROM #matches
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# more than 3 -> 1, less than 5 -> 0
data_df['preference'] = np.where(data_df['rating'] > 3, 1, 0)
data_df.head()
@Sandy4321
Sandy4321 / Criteo.ipynb
Created January 26, 2020 19:55 — forked from stsievert/Criteo.ipynb
Criteo dataset example
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@Sandy4321
Sandy4321 / pinterest_follower_scraper.py
Created October 17, 2018 19:52 — forked from syphon5/pinterest_follower_scraper.py
Pinterest account follower scraper in Python 3.5
# Pinterest Follower Scraper - 20171002 - www.syphon5.com
# Python 3.5
# Also found: https://github.com/syphon5/blog/tree/master/pinterest_follower_scraper
#Import visualization packages
import seaborn as sns
import matplotlib.pyplot as plt
#Import HTTPS requests package
import requests
#Import web scraping package