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How do I plot my histogram for density rather than count? (Matplotlib)

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0

I have a data frame called 'train' with a column 'string' and a column 'string length' and a column 'rank' which has ranking ranging from 0-4.

I want to create a histogram of the string length for each ranking and plot all of the histograms on one graph to compare. I am experiencing two issues with this:

The only way I can manage to do this is by creating separate datasets e.g. with the following type of code:

S0 = train.loc[train['rank'] == 0]
S1 = train.loc[train['rank'] == 1]

Then I create individual histograms for each dataset using:

plt.hist(train['string length'], bins = 100)
plt.show()

This code doesn't plot the density but instead plots the counts. How do I alter my code such that it plots density instead?

Is there also a way to do this without having to create separate datasets? I was told that my method is 'unpythonic'

python pandas matplotlib statistics histogram

share|improve this question

asked Mar 21 at 15:23

summer_ZUGGsummer_ZUGG

82

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Please read How to create a Minimal, Complete, and Verifiable example
  
  – Bazingaa
  Mar 21 at 15:27
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Do you feel that I am missing any relevant information that needs to be added to my question?
  
  – summer_ZUGG
  Mar 21 at 15:31
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  An ideal question is where the code can simply be copied to reproduce the problem. Your question lacks the dataset and the minimal code to do so. If one wants to play with the code, one can't
  
  – Bazingaa
  Mar 21 at 15:32
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thanks for clarifying, I will edit my question accordingly
  
  – summer_ZUGG
  Mar 21 at 15:35
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Does adding the density=True keyword not do what you want?
  
  – Ed Smith
  Mar 21 at 15:38
  

  
  
  
  

 | 
show 1 more comment

0

I have a data frame called 'train' with a column 'string' and a column 'string length' and a column 'rank' which has ranking ranging from 0-4.

I want to create a histogram of the string length for each ranking and plot all of the histograms on one graph to compare. I am experiencing two issues with this:

The only way I can manage to do this is by creating separate datasets e.g. with the following type of code:

S0 = train.loc[train['rank'] == 0]
S1 = train.loc[train['rank'] == 1]

Then I create individual histograms for each dataset using:

plt.hist(train['string length'], bins = 100)
plt.show()

This code doesn't plot the density but instead plots the counts. How do I alter my code such that it plots density instead?

Is there also a way to do this without having to create separate datasets? I was told that my method is 'unpythonic'

python pandas matplotlib statistics histogram

share|improve this question

asked Mar 21 at 15:23

summer_ZUGGsummer_ZUGG

82

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Please read How to create a Minimal, Complete, and Verifiable example
  
  – Bazingaa
  Mar 21 at 15:27
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Do you feel that I am missing any relevant information that needs to be added to my question?
  
  – summer_ZUGG
  Mar 21 at 15:31
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  An ideal question is where the code can simply be copied to reproduce the problem. Your question lacks the dataset and the minimal code to do so. If one wants to play with the code, one can't
  
  – Bazingaa
  Mar 21 at 15:32
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thanks for clarifying, I will edit my question accordingly
  
  – summer_ZUGG
  Mar 21 at 15:35
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Does adding the density=True keyword not do what you want?
  
  – Ed Smith
  Mar 21 at 15:38
  

  
  
  
  

 | 
show 1 more comment

I have a data frame called 'train' with a column 'string' and a column 'string length' and a column 'rank' which has ranking ranging from 0-4.

I want to create a histogram of the string length for each ranking and plot all of the histograms on one graph to compare. I am experiencing two issues with this:

The only way I can manage to do this is by creating separate datasets e.g. with the following type of code:

S0 = train.loc[train['rank'] == 0]
S1 = train.loc[train['rank'] == 1]

Then I create individual histograms for each dataset using:

plt.hist(train['string length'], bins = 100)
plt.show()

This code doesn't plot the density but instead plots the counts. How do I alter my code such that it plots density instead?

Is there also a way to do this without having to create separate datasets? I was told that my method is 'unpythonic'

python pandas matplotlib statistics histogram

share|improve this question

asked Mar 21 at 15:23

summer_ZUGGsummer_ZUGG

82

S0 = train.loc[train['rank'] == 0]
S1 = train.loc[train['rank'] == 1]

plt.hist(train['string length'], bins = 100)
plt.show()

share|improve this question

asked Mar 21 at 15:23

summer_ZUGGsummer_ZUGG

82

share|improve this question

asked Mar 21 at 15:23

summer_ZUGGsummer_ZUGG

82

asked Mar 21 at 15:23

summer_ZUGGsummer_ZUGG

82

asked Mar 21 at 15:23

summer_ZUGGsummer_ZUGG

82

1 Answer
1

active

oldest

votes

0

You could do something like:

df.loc[:, df.columns != 'string'].groupby('rank').hist(density=True, bins =10, figsize=(5,5))

Basically, what it does is select all columns except string, group them by rank and make an histogram of all them following the arguments.

The density argument set to density=True draws it in a normalized manner, as

Hope this has helped.

EDIT:

f there are more variables and you want the histograms overlapped, try:

df.groupby('rank')['string length'].hist(density=True, histtype='step', bins =10,figsize=(5,5))

share|improve this answer

edited Mar 21 at 17:07

answered Mar 21 at 15:43

BCJuanBCJuan

313

New contributor

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

• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  Hi, thank you for your answer. I tried this method but this seems to be giving me a histogram for every column in my data rather than a histogram for every rank. It is also plotting the histograms on separate graphs rather than overlapping them.
  
  – summer_ZUGG
  Mar 21 at 15:54
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  My apologies. If there are more variables and you want the histograms overlapped, try: df.groupby('rank')['string length'].hist(density=True, histtype='step', bins =10,figsize=(5,5))
  
  – BCJuan
  Mar 21 at 16:39
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I have added it as an edit of the main answer so everyone can see it.
  
  – BCJuan
  Mar 21 at 17:06
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you so much for this! Very helpful :)
  
  – summer_ZUGG
  Mar 21 at 17:16
  

  
  
  
  

add a comment | 

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0

You could do something like:

df.loc[:, df.columns != 'string'].groupby('rank').hist(density=True, bins =10, figsize=(5,5))

Basically, what it does is select all columns except string, group them by rank and make an histogram of all them following the arguments.

The density argument set to density=True draws it in a normalized manner, as

Hope this has helped.

EDIT:

f there are more variables and you want the histograms overlapped, try:

df.groupby('rank')['string length'].hist(density=True, histtype='step', bins =10,figsize=(5,5))

share|improve this answer

edited Mar 21 at 17:07

answered Mar 21 at 15:43

BCJuanBCJuan

313

New contributor

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

• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  Hi, thank you for your answer. I tried this method but this seems to be giving me a histogram for every column in my data rather than a histogram for every rank. It is also plotting the histograms on separate graphs rather than overlapping them.
  
  – summer_ZUGG
  Mar 21 at 15:54
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  My apologies. If there are more variables and you want the histograms overlapped, try: df.groupby('rank')['string length'].hist(density=True, histtype='step', bins =10,figsize=(5,5))
  
  – BCJuan
  Mar 21 at 16:39
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I have added it as an edit of the main answer so everyone can see it.
  
  – BCJuan
  Mar 21 at 17:06
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you so much for this! Very helpful :)
  
  – summer_ZUGG
  Mar 21 at 17:16
  

  
  
  
  

add a comment | 

0

You could do something like:

df.loc[:, df.columns != 'string'].groupby('rank').hist(density=True, bins =10, figsize=(5,5))

Basically, what it does is select all columns except string, group them by rank and make an histogram of all them following the arguments.

The density argument set to density=True draws it in a normalized manner, as

Hope this has helped.

EDIT:

f there are more variables and you want the histograms overlapped, try:

df.groupby('rank')['string length'].hist(density=True, histtype='step', bins =10,figsize=(5,5))

share|improve this answer

edited Mar 21 at 17:07

answered Mar 21 at 15:43

BCJuanBCJuan

313

New contributor

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

• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  Hi, thank you for your answer. I tried this method but this seems to be giving me a histogram for every column in my data rather than a histogram for every rank. It is also plotting the histograms on separate graphs rather than overlapping them.
  
  – summer_ZUGG
  Mar 21 at 15:54
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  My apologies. If there are more variables and you want the histograms overlapped, try: df.groupby('rank')['string length'].hist(density=True, histtype='step', bins =10,figsize=(5,5))
  
  – BCJuan
  Mar 21 at 16:39
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I have added it as an edit of the main answer so everyone can see it.
  
  – BCJuan
  Mar 21 at 17:06
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you so much for this! Very helpful :)
  
  – summer_ZUGG
  Mar 21 at 17:16
  

  
  
  
  

add a comment | 

You could do something like:

df.loc[:, df.columns != 'string'].groupby('rank').hist(density=True, bins =10, figsize=(5,5))

Basically, what it does is select all columns except string, group them by rank and make an histogram of all them following the arguments.

The density argument set to density=True draws it in a normalized manner, as

Hope this has helped.

EDIT:

f there are more variables and you want the histograms overlapped, try:

df.groupby('rank')['string length'].hist(density=True, histtype='step', bins =10,figsize=(5,5))

share|improve this answer

edited Mar 21 at 17:07

answered Mar 21 at 15:43

BCJuanBCJuan

313

New contributor

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

df.loc[:, df.columns != 'string'].groupby('rank').hist(density=True, bins =10, figsize=(5,5))

df.groupby('rank')['string length'].hist(density=True, histtype='step', bins =10,figsize=(5,5))

share|improve this answer

edited Mar 21 at 17:07

answered Mar 21 at 15:43

BCJuanBCJuan

313

New contributor

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

answered Mar 21 at 15:43

BCJuanBCJuan

313

New contributor

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

answered Mar 21 at 15:43

BCJuanBCJuan

313