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Histogram is extremely skewed to the left

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1

$begingroup$

everyone.
Hope you are all okay.

I am pretty bad at visualizations in Python.
I am working on a movie dataset and now I want to understand how values of variable 'vote_count' for every movie in the dataset are distributed.
So I am using very simple code:

plt.hist(df_movies.vote_count,bins=7)
plt.show()

And the output looks the following way:

As it is easy to notice the distribution is skewed very much to left.

I realize that I should focus on plt.xticks(), but I tried to play around and the histogram still looked awful.

Could you please give me some advices how to make it more understandable and useful to get insights.

Thanks a lot in advance!

python visualization matplotlib

share|improve this question

edited Mar 19 at 21:45

user641597

asked Mar 19 at 10:46

user641597user641597

83

New contributor

user641597 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

1

$begingroup$

everyone.
Hope you are all okay.

I am pretty bad at visualizations in Python.
I am working on a movie dataset and now I want to understand how values of variable 'vote_count' for every movie in the dataset are distributed.
So I am using very simple code:

plt.hist(df_movies.vote_count,bins=7)
plt.show()

And the output looks the following way:

As it is easy to notice the distribution is skewed very much to left.

I realize that I should focus on plt.xticks(), but I tried to play around and the histogram still looked awful.

Could you please give me some advices how to make it more understandable and useful to get insights.

Thanks a lot in advance!

python visualization matplotlib

share|improve this question

edited Mar 19 at 21:45

user641597

asked Mar 19 at 10:46

user641597user641597

83

New contributor

user641597 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

everyone.
Hope you are all okay.

I am pretty bad at visualizations in Python.
I am working on a movie dataset and now I want to understand how values of variable 'vote_count' for every movie in the dataset are distributed.
So I am using very simple code:

plt.hist(df_movies.vote_count,bins=7)
plt.show()

And the output looks the following way:

As it is easy to notice the distribution is skewed very much to left.

I realize that I should focus on plt.xticks(), but I tried to play around and the histogram still looked awful.

Could you please give me some advices how to make it more understandable and useful to get insights.

Thanks a lot in advance!

python visualization matplotlib

share|improve this question

edited Mar 19 at 21:45

user641597

asked Mar 19 at 10:46

user641597user641597

83

New contributor

user641597 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

plt.hist(df_movies.vote_count,bins=7)
plt.show()

share|improve this question

edited Mar 19 at 21:45

user641597

asked Mar 19 at 10:46

user641597user641597

83

New contributor

user641597 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

edited Mar 19 at 21:45

user641597

asked Mar 19 at 10:46

user641597user641597

83

New contributor

user641597 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked Mar 19 at 10:46

user641597user641597

83

New contributor

user641597 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked Mar 19 at 10:46

user641597user641597

83

1 Answer
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2

$begingroup$

I think there are a few "easy wins" here.

1. You might add more bins - you are already using the bin setting. Just add something high like 100 or even 1000 to get a first feeling for the data


2. You can define the range of your bins. For example you could set the range with a list of two entries range = [0, 5000] as an additional parameter


3. You can consider not showing all data- maybe movies with a few ratings or movies with a lot are not what you focus on. You can use the range argument from point two to limit the plot to the region interesting for you.


4. You can try a cumulative and normed plot cumulative = True, normed = True this can be very useful to get a better estimate on statements like "80% of movies have less than 100 ratings" - for cumulative plots I recommend a very large number of bins.

I hope this helps and let me know if something is unclear

share|improve this answer

answered Mar 19 at 12:44

El BurroEl Burro

455311

$endgroup$

add a comment | 

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2

$begingroup$

I think there are a few "easy wins" here.

1. You might add more bins - you are already using the bin setting. Just add something high like 100 or even 1000 to get a first feeling for the data


2. You can define the range of your bins. For example you could set the range with a list of two entries range = [0, 5000] as an additional parameter


3. You can consider not showing all data- maybe movies with a few ratings or movies with a lot are not what you focus on. You can use the range argument from point two to limit the plot to the region interesting for you.


4. You can try a cumulative and normed plot cumulative = True, normed = True this can be very useful to get a better estimate on statements like "80% of movies have less than 100 ratings" - for cumulative plots I recommend a very large number of bins.

I hope this helps and let me know if something is unclear

share|improve this answer

answered Mar 19 at 12:44

El BurroEl Burro

455311

$endgroup$

add a comment | 

2

$begingroup$

I think there are a few "easy wins" here.

1. You might add more bins - you are already using the bin setting. Just add something high like 100 or even 1000 to get a first feeling for the data


2. You can define the range of your bins. For example you could set the range with a list of two entries range = [0, 5000] as an additional parameter


3. You can consider not showing all data- maybe movies with a few ratings or movies with a lot are not what you focus on. You can use the range argument from point two to limit the plot to the region interesting for you.


4. You can try a cumulative and normed plot cumulative = True, normed = True this can be very useful to get a better estimate on statements like "80% of movies have less than 100 ratings" - for cumulative plots I recommend a very large number of bins.

I hope this helps and let me know if something is unclear

share|improve this answer

answered Mar 19 at 12:44

El BurroEl Burro

455311

$endgroup$

add a comment | 

$begingroup$

I think there are a few "easy wins" here.

1. You might add more bins - you are already using the bin setting. Just add something high like 100 or even 1000 to get a first feeling for the data


2. You can define the range of your bins. For example you could set the range with a list of two entries range = [0, 5000] as an additional parameter


3. You can consider not showing all data- maybe movies with a few ratings or movies with a lot are not what you focus on. You can use the range argument from point two to limit the plot to the region interesting for you.


4. You can try a cumulative and normed plot cumulative = True, normed = True this can be very useful to get a better estimate on statements like "80% of movies have less than 100 ratings" - for cumulative plots I recommend a very large number of bins.

I hope this helps and let me know if something is unclear

share|improve this answer

answered Mar 19 at 12:44

El BurroEl Burro

455311

$endgroup$

share|improve this answer

answered Mar 19 at 12:44

El BurroEl Burro

455311

answered Mar 19 at 12:44

El BurroEl Burro

455311

answered Mar 19 at 12:44

El BurroEl Burro

455311