Question

我有很多带注释的照片（2个注释/ Foto）。在脚本中，我使用word2vec表示向量中的单词。现在，我想将单词（属于每张图片）连同矢量一起写在csv中。每行应代表一个Foto，其每列中都有一个注释，然后是该列中每个注释的向量。

错误信息：AssertionError：传递了8列，传递的数据有1列

错误应该在第89行 datalist.append（[pd.DataFrame（rowlist，columns = header）]）

我已经进行了很多更改和尝试（将行列表放入数据框），等等，但是仍然出现相同的错误

from nltk.tokenize import sent_tokenize, word_tokenize 
import pandas as pd

import warnings 



warnings.filterwarnings(action = 'ignore') 



import gensim 

from gensim.models import Word2Vec 

# csv einlesen
testdata=pd.read_csv("./Test1.csv", sep=";", header=None)




#  Reads ‘alice.txt’ file 

sample = open("G:/Dropbox/_Uni/1. Dissertation/Scripts/word2vec/input.txt", "r", encoding="ISO-8859-1") 

s = sample.read() 


# Replaces escape character with space 

f = s.replace("\n", " ") 



data = [] 


# iterate through each sentence in the file 

for i in sent_tokenize(f): 

    temp = [] 



    # tokenize the sentence into words 

    for j in word_tokenize(i): 

        temp.append(j.lower()) 



    data.append(temp) 


# Create CBOW model 

model1 = gensim.models.Word2Vec(data, min_count = 1,  

                              size = 100, window = 5) 

datalist=[]

for i, row in testdata.iterrows():
  rowlist= []
  fotocounter="Foto "+ str(i+1)
  for x in row: 
     try: 
         x=str(x)

         #i+1 = Fotonummer
         rowlist.append([model1[x]])




     except KeyError:
        rowlist.append(["False"])
  print(len(rowlist))
  header= ["1","2","3","4","5","6","7","8"]
  print(header)
  datalist.append([fotocounter, pd.DataFrame(rowlist, columns=header)])
print(datalist)     


df=pd.DataFrame(datalist)
#transponiert zeilen und spalten
#df_transposed = df.T
df.to_csv("vector-output.csv", index=False)



# Create Skip Gram model 

#model2 = gensim.models.Word2Vec(data, min_count = 1, size = 100, 
#
#                                             window = 5, sg = 1)

AssertionError-公证问题

0 个答案: