如何將數據幀轉換與串列到csr_matrix

Question

我工作的一個PMI的問題，到目前爲止，我有這樣一個數據幀：

w = ['by', 'step', 'by', 'the', 'is', 'step', 'is', 'by', 'is'] 
c = ['step', 'what', 'is', 'what', 'the', 'the', 'step', 'the', 'what'] 
ppmi = [1, 3, 12, 3, 123, 1, 321, 1, 23] 
df = pd.DataFrame({'w':w, 'c':c, 'ppmi': ppmi}) 

我想這個數據幀轉換成稀疏矩陣。由於w和c是字符串列表，如果我做csr_matrix((ppmi, (w, c)))，它會給我一個錯誤TypeError: cannot perform reduce with flexible type。什麼是轉換此數據框的另一種方法？

Answer 1

也許你可以嘗試用coo_matrix：

import pandas as pd 
import scipy.sparse as sps 
w = ['by', 'step', 'by', 'the', 'is', 'step', 'is', 'by', 'is'] 
c = ['step', 'what', 'is', 'what', 'the', 'the', 'step', 'the', 'what'] 
ppmi = [1, 3, 12, 3, 123, 1, 321, 1, 23] 
df = pd.DataFrame({'w':w, 'c':c, 'ppmi': ppmi}) 
df.set_index(['w', 'c'], inplace=True) 
mat = sps.coo_matrix((df['ppmi'],(df.index.labels[0], df.index.labels[1]))) 
print(mat.todense()) 

輸出：

[[ 12 1 1 0] 
[ 0 321 123 23] 
[ 0 0 1 3] 
[ 0 0 0 3]]