fixes absolute paths
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@ -27,7 +27,7 @@ N=3
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#read in csv as panda file
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#read in csv as panda file
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df = pd.read_csv("/Users/Carsten/GitRepos/NLP-LAB/Project/Tools/Emoji_Sentiment_Data_v1.0.csv", delimiter=";")
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df = pd.read_csv("../Tools/Emoji_Sentiment_Data_v1.0.csv", delimiter=";")
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#df.head()
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#df.head()
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@ -65,7 +65,7 @@ def dataframe_to_dictionary():
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# In[4]:
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# In[4]:
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# create global emoji lists and datasets
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data , data_only_emoticons, list_sentiment_vectors , list_emojis , list_sentiment_emoticon_vectors , list_emoticon_emojis = dataframe_to_dictionary()
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data , data_only_emoticons, list_sentiment_vectors , list_emojis , list_sentiment_emoticon_vectors , list_emoticon_emojis = dataframe_to_dictionary()
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@ -219,7 +219,7 @@ def show_demo_min_distances(only_emoticons = True):
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# In[29]:
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# In[29]:
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show_demo_min_distances()
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#show_demo_min_distances()
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# In[30]:
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# In[30]:
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@ -237,11 +237,11 @@ show_demo_min_distances()
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# In[36]:
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# In[36]:
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[(e,sentiment_vector_to_emoji(emoji_to_sentiment_vector(e,only_emoticons=False))) for e in list_emojis]
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#[(e,sentiment_vector_to_emoji(emoji_to_sentiment_vector(e,only_emoticons=False))) for e in list_emojis]
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# In[26]:
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# In[26]:
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sentiment_vector_to_emoji(np.array([ 0.72967448, 0.05173769, 0.21858783]))
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#sentiment_vector_to_emoji(np.array([ 0.72967448, 0.05173769, 0.21858783]))
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