我有2个dataframes
。我想把它们组合起来dataframe 1
具有列content
和embeddings
myquerycontents_and_embeddings_df.content
0 i live in space
1 i live my life to fullest
2 dogs live in kennel
3 we live to eat and not eat to live
4 cricket lives in heart of every indian
5 live and let live
6 my house is in someplace
7 my office is in someotherplace
8 chair is red
Name: content, dtype: object
myquerycontents_and_embeddings_df.embeddings
0 [0.0016913715517148376, -0.013320472091436386,...
1 [-0.01872972585260868, -0.010366685688495636, ...
2 [8.654659177409485e-05, -0.024498699232935905,...
3 [-0.024393899366259575, -0.008192254230380058,...
4 [-0.021614402532577515, -0.006505827885121107,...
5 [-0.01553483959287405, -0.014875221997499466, ...
6 [0.002573014236986637, -0.005427114199846983, ...
7 [0.013354390859603882, -0.007010389119386673, ...
8 [0.00505671463906765, -0.00909961387515068, -0...
Name: embeddings, dtype: object
dataframe2
具有列cosinesimilarity
similarityvaluedf.cosinesimilarity
0 0.994341
1 0.808836
2 0.818914
3 0.727792
4 0.675430
5 0.802331
6 0.849596
7 0.778798
8 0.776794
Name: cosinesimilarity, dtype: float64
我想创建一个新的dataframe
,它有3列和8行,但我得到NaN
combineddf = pd.DataFrame((myquerycontents_and_embeddings_df.content,myquerycontents_and_embeddings_df.embeddings,similarityvaluedf.cosinesimilarity),columns=['content','embeddings','cosine_similarity'])
combineddf
1条答案
按热度按时间j8ag8udp1#
我解决了