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/hidden_relationships.py

Created May 28, 2017 18:02
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hidden_relationships.py
import numpy as np
import pandas as pd
from sklearn.decomposition import PCA
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
import seaborn as sb
np.seterr(divide='ignore', invalid='ignore')
# Quick way to test just a few column features
# stocks = pd.read_csv('supercolumns-elements-nasdaq-nyse-otcbb-general-UPDATE-2017-03-01.csv', usecols=range(1,16))
stocks = pd.read_csv('supercolumns-elements-nasdaq-nyse-otcbb-general-UPDATE-2017-03-01.csv')
print(stocks.head())
str_list = []
for colname, colvalue in stocks.iteritems():
if type(colvalue[1]) == str:
str_list.append(colname)
# Get to the numeric columns by inversion
num_list = stocks.columns.difference(str_list)
stocks_num = stocks[num_list]
print(stocks_num.head())
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