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Ratings matrix plot

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1

$begingroup$

Hello fellows and folks.

I have been looking to do this for 1 month and still cannot find the way to do it.

Here’s what’s going on:

I have a csv file called ratings.csv with the following structure:

userID, movieID, rating
3, 12, 5
2, 7, 6

The rating scale goes from 0 to 5 stars. I want to be able to plot the sparsity of the matrix like it’s done in the following picture:

As you can see, ratings scale goes from 0 to 5 on the right. It is a very well thought plot.

I have Matlab, Python, R etc. Could you come up with something and help me? I’ve tried hard but I cannot find the way to do it.

This is what I have tried so far:

tbl = readtable('ratings.csv');
users = categorical(tbl.userId);
movies = categorical(tbl.movieId);
xlabels = categories(users);
ylabels = categories(movies);

numusers = numel(xlabels);
nummovies = numel(ylabels);

x = double(users);
y = double(movies);
ratings = tbl.rating;
cdata = accumarray([y,x],ratings,[numusers,nummovies]);
h = heatmap(xlabels,ylabels,cdata);

But it throws me this error:

Error using accumarray
First input SUBS and third input SZ must satisfy ALL(MAX(SUBS)<=SZ).

machine-learning recommender-system

share|improve this question

edited 1 hour ago

naveganteX

asked 6 hours ago

naveganteXnaveganteX

1204

$endgroup$

add a comment | 

1

$begingroup$

Hello fellows and folks.

I have been looking to do this for 1 month and still cannot find the way to do it.

Here’s what’s going on:

I have a csv file called ratings.csv with the following structure:

userID, movieID, rating
3, 12, 5
2, 7, 6

The rating scale goes from 0 to 5 stars. I want to be able to plot the sparsity of the matrix like it’s done in the following picture:

As you can see, ratings scale goes from 0 to 5 on the right. It is a very well thought plot.

I have Matlab, Python, R etc. Could you come up with something and help me? I’ve tried hard but I cannot find the way to do it.

This is what I have tried so far:

tbl = readtable('ratings.csv');
users = categorical(tbl.userId);
movies = categorical(tbl.movieId);
xlabels = categories(users);
ylabels = categories(movies);

numusers = numel(xlabels);
nummovies = numel(ylabels);

x = double(users);
y = double(movies);
ratings = tbl.rating;
cdata = accumarray([y,x],ratings,[numusers,nummovies]);
h = heatmap(xlabels,ylabels,cdata);

But it throws me this error:

Error using accumarray
First input SUBS and third input SZ must satisfy ALL(MAX(SUBS)<=SZ).

machine-learning recommender-system

share|improve this question

edited 1 hour ago

naveganteX

asked 6 hours ago

naveganteXnaveganteX

1204

$endgroup$

add a comment | 

$begingroup$

Hello fellows and folks.

I have been looking to do this for 1 month and still cannot find the way to do it.

Here’s what’s going on:

I have a csv file called ratings.csv with the following structure:

userID, movieID, rating
3, 12, 5
2, 7, 6

The rating scale goes from 0 to 5 stars. I want to be able to plot the sparsity of the matrix like it’s done in the following picture:

As you can see, ratings scale goes from 0 to 5 on the right. It is a very well thought plot.

I have Matlab, Python, R etc. Could you come up with something and help me? I’ve tried hard but I cannot find the way to do it.

This is what I have tried so far:

tbl = readtable('ratings.csv');
users = categorical(tbl.userId);
movies = categorical(tbl.movieId);
xlabels = categories(users);
ylabels = categories(movies);

numusers = numel(xlabels);
nummovies = numel(ylabels);

x = double(users);
y = double(movies);
ratings = tbl.rating;
cdata = accumarray([y,x],ratings,[numusers,nummovies]);
h = heatmap(xlabels,ylabels,cdata);

But it throws me this error:

Error using accumarray
First input SUBS and third input SZ must satisfy ALL(MAX(SUBS)<=SZ).

machine-learning recommender-system

share|improve this question

edited 1 hour ago

naveganteX

asked 6 hours ago

naveganteXnaveganteX

1204

$endgroup$

userID, movieID, rating
3, 12, 5
2, 7, 6

tbl = readtable('ratings.csv');
users = categorical(tbl.userId);
movies = categorical(tbl.movieId);
xlabels = categories(users);
ylabels = categories(movies);

numusers = numel(xlabels);
nummovies = numel(ylabels);

x = double(users);
y = double(movies);
ratings = tbl.rating;
cdata = accumarray([y,x],ratings,[numusers,nummovies]);
h = heatmap(xlabels,ylabels,cdata);

share|improve this question

edited 1 hour ago

naveganteX

asked 6 hours ago

naveganteXnaveganteX

1204

share|improve this question

edited 1 hour ago

naveganteX

asked 6 hours ago

naveganteXnaveganteX

1204

asked 6 hours ago

naveganteXnaveganteX

1204

asked 6 hours ago

naveganteXnaveganteX

1204

2 Answers
2

active

oldest

votes

2

$begingroup$

You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.

share|improve this answer

answered 5 hours ago

nbronbro

3,3302826

$endgroup$

add a comment | 

0

$begingroup$

I did it!

A = importdata('u.data');
user_id = A(:, 1);
movie_id = A(:, 2);
rating = A(:, 3);

% Build matrix R and w (weights matrix)
R = zeros(943, 1682);
w = zeros(943, 1682);
for i=1:100000
 R(user_id(i), movie_id(i)) = rating(i);
 w(user_id(i), movie_id(i)) = 1;
end


m = HeatMap(R)
ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
colorbar('Peer', ax); % Turn the colorbar on
caxis(ax, [0 5]); % Adjust the color limits

Output:

share|improve this answer

answered 24 mins ago

naveganteXnaveganteX

1204

$endgroup$

add a comment | 

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2

$begingroup$

You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.

share|improve this answer

answered 5 hours ago

nbronbro

3,3302826

$endgroup$

add a comment | 

2

$begingroup$

You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.

share|improve this answer

answered 5 hours ago

nbronbro

3,3302826

$endgroup$

add a comment | 

$begingroup$

You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.

share|improve this answer

answered 5 hours ago

nbronbro

3,3302826

$endgroup$

share|improve this answer

answered 5 hours ago

nbronbro

3,3302826

answered 5 hours ago

nbronbro

3,3302826

answered 5 hours ago

nbronbro

3,3302826

0

$begingroup$

I did it!

A = importdata('u.data');
user_id = A(:, 1);
movie_id = A(:, 2);
rating = A(:, 3);

% Build matrix R and w (weights matrix)
R = zeros(943, 1682);
w = zeros(943, 1682);
for i=1:100000
 R(user_id(i), movie_id(i)) = rating(i);
 w(user_id(i), movie_id(i)) = 1;
end


m = HeatMap(R)
ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
colorbar('Peer', ax); % Turn the colorbar on
caxis(ax, [0 5]); % Adjust the color limits

Output:

share|improve this answer

answered 24 mins ago

naveganteXnaveganteX

1204

$endgroup$

add a comment | 

0

$begingroup$

I did it!

A = importdata('u.data');
user_id = A(:, 1);
movie_id = A(:, 2);
rating = A(:, 3);

% Build matrix R and w (weights matrix)
R = zeros(943, 1682);
w = zeros(943, 1682);
for i=1:100000
 R(user_id(i), movie_id(i)) = rating(i);
 w(user_id(i), movie_id(i)) = 1;
end


m = HeatMap(R)
ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
colorbar('Peer', ax); % Turn the colorbar on
caxis(ax, [0 5]); % Adjust the color limits

Output:

share|improve this answer

answered 24 mins ago

naveganteXnaveganteX

1204

$endgroup$

add a comment | 

$begingroup$

I did it!

A = importdata('u.data');
user_id = A(:, 1);
movie_id = A(:, 2);
rating = A(:, 3);

% Build matrix R and w (weights matrix)
R = zeros(943, 1682);
w = zeros(943, 1682);
for i=1:100000
 R(user_id(i), movie_id(i)) = rating(i);
 w(user_id(i), movie_id(i)) = 1;
end


m = HeatMap(R)
ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
colorbar('Peer', ax); % Turn the colorbar on
caxis(ax, [0 5]); % Adjust the color limits

Output:

share|improve this answer

answered 24 mins ago

naveganteXnaveganteX

1204

$endgroup$

A = importdata('u.data');
user_id = A(:, 1);
movie_id = A(:, 2);
rating = A(:, 3);

% Build matrix R and w (weights matrix)
R = zeros(943, 1682);
w = zeros(943, 1682);
for i=1:100000
 R(user_id(i), movie_id(i)) = rating(i);
 w(user_id(i), movie_id(i)) = 1;
end


m = HeatMap(R)
ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
colorbar('Peer', ax); % Turn the colorbar on
caxis(ax, [0 5]); % Adjust the color limits

share|improve this answer

answered 24 mins ago

naveganteXnaveganteX

1204

answered 24 mins ago

naveganteXnaveganteX

1204

answered 24 mins ago

naveganteXnaveganteX

1204