distance between two array movie
0
I want to create a function that calculates the distance between two array movie.
This is my DataFrame :
movie_title movieId Action Adventure Fantasy Sci-Fi Thriller
Avatar 1 1.0 1.0 1.0 1.0 0.0
Spectre 2 1.0 1.0 0.0 0.0 1
John Carter 3 1.0 1.0 0.0 1.0 0.0
then I represent movies as an array :
df_array = userGenreTable.as_matrix(columns=userGenreTable.columns[2:])
Output :
array([[1., 1., 1., ..., 0., 0., 0.],
[1., 1., 1., ..., 0., 0., 0.],
[1., 1., 0., ..., 0., 0., 0.]])
I represented the dataset as a dictionary:
df_2_dict = userGenreTable_2.to_dict('records')
so my question is How can I calculates the distance between two array movie ?
python pandas
asked Dec 28 '18 at 23:39
G.MG.M
317
add a comment |
0
I want to create a function that calculates the distance between two array movie.
This is my DataFrame :
movie_title movieId Action Adventure Fantasy Sci-Fi Thriller
Avatar 1 1.0 1.0 1.0 1.0 0.0
Spectre 2 1.0 1.0 0.0 0.0 1
John Carter 3 1.0 1.0 0.0 1.0 0.0
then I represent movies as an array :
df_array = userGenreTable.as_matrix(columns=userGenreTable.columns[2:])
Output :
array([[1., 1., 1., ..., 0., 0., 0.],
[1., 1., 1., ..., 0., 0., 0.],
[1., 1., 0., ..., 0., 0., 0.]])
I represented the dataset as a dictionary:
df_2_dict = userGenreTable_2.to_dict('records')
so my question is How can I calculates the distance between two array movie ?
python pandas
asked Dec 28 '18 at 23:39
G.MG.M
317
What metric defines "distance"? And "array movie" does not make sense, I assume you mean "movie array" in that it is an array of movie details. If that's the case, the fact that it focuses on movies is pretty much irrelevant since you just have an array of features that are either 1 or 0.
– roganjosh
Dec 28 '18 at 23:42
@roganjosh, yes I want to say " movie array"
– G.M
Dec 28 '18 at 23:46
to compare 2 movies, you do the euclidian distance, that is the square root of the sum of the squared differences. You can even skip the square root part to be faster. In dataframe computations, that'd be row1^2 - row2 ^2 and then sum
– MrE
Dec 29 '18 at 6:56
add a comment |
0
0
0
I want to create a function that calculates the distance between two array movie.
This is my DataFrame :
movie_title movieId Action Adventure Fantasy Sci-Fi Thriller
Avatar 1 1.0 1.0 1.0 1.0 0.0
Spectre 2 1.0 1.0 0.0 0.0 1
John Carter 3 1.0 1.0 0.0 1.0 0.0
then I represent movies as an array :
df_array = userGenreTable.as_matrix(columns=userGenreTable.columns[2:])
Output :
array([[1., 1., 1., ..., 0., 0., 0.],
[1., 1., 1., ..., 0., 0., 0.],
[1., 1., 0., ..., 0., 0., 0.]])
I represented the dataset as a dictionary:
df_2_dict = userGenreTable_2.to_dict('records')
so my question is How can I calculates the distance between two array movie ?
python pandas
asked Dec 28 '18 at 23:39
G.MG.M
317
I want to create a function that calculates the distance between two array movie.
This is my DataFrame :
movie_title movieId Action Adventure Fantasy Sci-Fi Thriller
Avatar 1 1.0 1.0 1.0 1.0 0.0
Spectre 2 1.0 1.0 0.0 0.0 1
John Carter 3 1.0 1.0 0.0 1.0 0.0
then I represent movies as an array :
df_array = userGenreTable.as_matrix(columns=userGenreTable.columns[2:])
Output :
array([[1., 1., 1., ..., 0., 0., 0.],
[1., 1., 1., ..., 0., 0., 0.],
[1., 1., 0., ..., 0., 0., 0.]])
I represented the dataset as a dictionary:
df_2_dict = userGenreTable_2.to_dict('records')
so my question is How can I calculates the distance between two array movie ?
python pandas
python pandas
asked Dec 28 '18 at 23:39
G.MG.M
317
asked Dec 28 '18 at 23:39
G.MG.M
317
asked Dec 28 '18 at 23:39
G.MG.M
317
asked Dec 28 '18 at 23:39
G.MG.M
317
asked Dec 28 '18 at 23:39
G.MG.M
317
317
What metric defines "distance"? And "array movie" does not make sense, I assume you mean "movie array" in that it is an array of movie details. If that's the case, the fact that it focuses on movies is pretty much irrelevant since you just have an array of features that are either 1 or 0.
– roganjosh
Dec 28 '18 at 23:42
@roganjosh, yes I want to say " movie array"
– G.M
Dec 28 '18 at 23:46
to compare 2 movies, you do the euclidian distance, that is the square root of the sum of the squared differences. You can even skip the square root part to be faster. In dataframe computations, that'd be row1^2 - row2 ^2 and then sum
– MrE
Dec 29 '18 at 6:56
add a comment |
What metric defines "distance"? And "array movie" does not make sense, I assume you mean "movie array" in that it is an array of movie details. If that's the case, the fact that it focuses on movies is pretty much irrelevant since you just have an array of features that are either 1 or 0.
– roganjosh
Dec 28 '18 at 23:42
@roganjosh, yes I want to say " movie array"
– G.M
Dec 28 '18 at 23:46
to compare 2 movies, you do the euclidian distance, that is the square root of the sum of the squared differences. You can even skip the square root part to be faster. In dataframe computations, that'd be row1^2 - row2 ^2 and then sum
– MrE
Dec 29 '18 at 6:56
What metric defines "distance"? And "array movie" does not make sense, I assume you mean "movie array" in that it is an array of movie details. If that's the case, the fact that it focuses on movies is pretty much irrelevant since you just have an array of features that are either 1 or 0.
– roganjosh
Dec 28 '18 at 23:42
What metric defines "distance"? And "array movie" does not make sense, I assume you mean "movie array" in that it is an array of movie details. If that's the case, the fact that it focuses on movies is pretty much irrelevant since you just have an array of features that are either 1 or 0.
– roganjosh
Dec 28 '18 at 23:42
@roganjosh, yes I want to say " movie array"
– G.M
Dec 28 '18 at 23:46
@roganjosh, yes I want to say " movie array"
– G.M
Dec 28 '18 at 23:46
to compare 2 movies, you do the euclidian distance, that is the square root of the sum of the squared differences. You can even skip the square root part to be faster. In dataframe computations, that'd be row1^2 - row2 ^2 and then sum
– MrE
Dec 29 '18 at 6:56
to compare 2 movies, you do the euclidian distance, that is the square root of the sum of the squared differences. You can even skip the square root part to be faster. In dataframe computations, that'd be row1^2 - row2 ^2 and then sum
– MrE
Dec 29 '18 at 6:56
add a comment |
1 Answer
1
active
oldest
votes
2
To obtain distance between all possible pairs in df_array, you need to calculate a distance matrix. Using scipy.spatial:
from scipy.spatial import distance_matrix
# p = 2 for euclidean distances
distance_matrix(df_array, df_array, p = 2)
answered Dec 29 '18 at 0:01
Mankind_008Mankind_008
1,4862312
thank you that's what I was looking for
– G.M
Dec 29 '18 at 8:01
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
2
To obtain distance between all possible pairs in df_array, you need to calculate a distance matrix. Using scipy.spatial:
from scipy.spatial import distance_matrix
# p = 2 for euclidean distances
distance_matrix(df_array, df_array, p = 2)
answered Dec 29 '18 at 0:01
Mankind_008Mankind_008
1,4862312
thank you that's what I was looking for
– G.M
Dec 29 '18 at 8:01
add a comment |
2
To obtain distance between all possible pairs in df_array, you need to calculate a distance matrix. Using scipy.spatial:
from scipy.spatial import distance_matrix
# p = 2 for euclidean distances
distance_matrix(df_array, df_array, p = 2)
answered Dec 29 '18 at 0:01
Mankind_008Mankind_008
1,4862312
thank you that's what I was looking for
– G.M
Dec 29 '18 at 8:01
add a comment |
2
2
2
To obtain distance between all possible pairs in df_array, you need to calculate a distance matrix. Using scipy.spatial:
from scipy.spatial import distance_matrix
# p = 2 for euclidean distances
distance_matrix(df_array, df_array, p = 2)
answered Dec 29 '18 at 0:01
Mankind_008Mankind_008
1,4862312
To obtain distance between all possible pairs in df_array, you need to calculate a distance matrix. Using scipy.spatial:
from scipy.spatial import distance_matrix
# p = 2 for euclidean distances
distance_matrix(df_array, df_array, p = 2)
answered Dec 29 '18 at 0:01
Mankind_008Mankind_008
1,4862312
edited Dec 29 '18 at 19:13
answered Dec 29 '18 at 0:01
Mankind_008Mankind_008
1,4862312
answered Dec 29 '18 at 0:01
Mankind_008Mankind_008
1,4862312
answered Dec 29 '18 at 0:01
Mankind_008Mankind_008
1,4862312
1,4862312
thank you that's what I was looking for
– G.M
Dec 29 '18 at 8:01
add a comment |
thank you that's what I was looking for
– G.M
Dec 29 '18 at 8:01
thank you that's what I was looking for
– G.M
Dec 29 '18 at 8:01
thank you that's what I was looking for
– G.M
Dec 29 '18 at 8:01
add a comment |
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What metric defines "distance"? And "array movie" does not make sense, I assume you mean "movie array" in that it is an array of movie details. If that's the case, the fact that it focuses on movies is pretty much irrelevant since you just have an array of features that are either 1 or 0.
– roganjosh
Dec 28 '18 at 23:42
@roganjosh, yes I want to say " movie array"
– G.M
Dec 28 '18 at 23:46
to compare 2 movies, you do the euclidian distance, that is the square root of the sum of the squared differences. You can even skip the square root part to be faster. In dataframe computations, that'd be row1^2 - row2 ^2 and then sum
– MrE
Dec 29 '18 at 6:56