I get the following error:
TypeError Traceback (most recent call last)
C:\Users\levanim\Desktop\Levani Predictive\cosinesimilarity1.py in <module>()
39
40 for i in meowmix_nearest_neighbors.index:
---> 41 top_ten = pd.DataFrame(similarity_matrix.ix[i,]).sort([i],
ascending=False[1:6]).index.values
42 meowmix_nearest_neighbors.ix[i,:] = top_ten
43
TypeError: 'bool' object is not subscriptable
for the following code. I'm new to Python and can't quite put my finger on how I have to change the syntax(if its a syntax python 3 problem). Anybody encounter this? I think it's to do with the ascending=False[1:6] portion and have spent some time banging my head against the wall. Hoping it's a simple fix but don't know enough
import numpy as np
import pandas as pd
from scipy.spatial.distance import cosine
enrollments = pd.read_csv(r'C:\Users\levanim\Desktop\Levani
Predictive\smallsample.csv')
meowmix = enrollments.fillna(0)
meowmix.ix[0:5,0:5]
def getCosine(x,y) :
cosine = np.sum(x*y) / (np.sqrt(np.sum(x*x)) * np.sqrt(np.sum(y*y)))
return cosine
print("done creating cosine function")
similarity_matrix = pd.DataFrame(index=meowmix.columns,
columns=meowmix.columns)
similarity_matrix = similarity_matrix.fillna(np.nan)
similarity_matrix.ix[0:5,0:5]
print("done creating a matrix placeholder")
for i in similarity_matrix.columns:
for j in similarity_matrix.columns:
similarity_matrix.ix[i,j] = getCosine(meowmix[i].values,
meowmix[j].values)
print("done looping through each column and filling in placeholder with
cosine similarities")
meowmix_nearest_neighbors = pd.DataFrame(index=meowmix.columns,
columns=['top_'+str(i+1) for i in
range(5)])
meowmix_nearest_neighbors = meowmix_nearest_neighbors.fillna(np.nan)
print("done creating a nearest neighbor placeholder for each item")
for i in meowmix_nearest_neighbors.index:
top_ten = pd.DataFrame(similarity_matrix.ix[i,]).sort([i],
ascending=False[1:6]).index.values
meowmix_nearest_neighbors.ix[i,:] = top_ten
print("done creating the top 5 neighbors for each item")
meowmix_nearest_neighbors.head()
False[1:6]thing, anyway?