EDA for analysis of nominal variable with high cardinality
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I have a nominal variable (car model) with very high cardinality (~8500 labels) and I would like to analyse its relation with a binary target variable. While I can create logical groups and compare the distribution of target variable for each of the groups, can anyone suggest if there are any superior techniques/visualization tools for this type of analysis?
categorical-data data-analysis
asked yesterday
Rohit GavvalRohit Gavval
515
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add a comment |
$begingroup$
I have a nominal variable (car model) with very high cardinality (~8500 labels) and I would like to analyse its relation with a binary target variable. While I can create logical groups and compare the distribution of target variable for each of the groups, can anyone suggest if there are any superior techniques/visualization tools for this type of analysis?
categorical-data data-analysis
asked yesterday
Rohit GavvalRohit Gavval
515
$endgroup$
add a comment |
$begingroup$
I have a nominal variable (car model) with very high cardinality (~8500 labels) and I would like to analyse its relation with a binary target variable. While I can create logical groups and compare the distribution of target variable for each of the groups, can anyone suggest if there are any superior techniques/visualization tools for this type of analysis?
categorical-data data-analysis
asked yesterday
Rohit GavvalRohit Gavval
515
$endgroup$
I have a nominal variable (car model) with very high cardinality (~8500 labels) and I would like to analyse its relation with a binary target variable. While I can create logical groups and compare the distribution of target variable for each of the groups, can anyone suggest if there are any superior techniques/visualization tools for this type of analysis?
categorical-data data-analysis
categorical-data data-analysis
asked yesterday
Rohit GavvalRohit Gavval
515
asked yesterday
Rohit GavvalRohit Gavval
515
asked yesterday
Rohit GavvalRohit Gavval
515
asked yesterday
Rohit GavvalRohit Gavval
515
asked yesterday
Rohit GavvalRohit Gavval
515
515
add a comment |
add a comment |
1 Answer
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You can calculate mean target for each categorical variable and compare its values.
In pandas this can be done easily: df.groupby('categorical_feature').target.mean()
Then you can make a histogram to compare the approach. I also, seaborn has a catplot, where it do the same as above in a bar plot format, showing mean value for target variable based on each categorical one.
answered 17 hours ago
Victor OliveiraVictor Oliveira
11
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Victor Oliveira is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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1 Answer
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1 Answer
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$begingroup$
You can calculate mean target for each categorical variable and compare its values.
In pandas this can be done easily: df.groupby('categorical_feature').target.mean()
Then you can make a histogram to compare the approach. I also, seaborn has a catplot, where it do the same as above in a bar plot format, showing mean value for target variable based on each categorical one.
answered 17 hours ago
Victor OliveiraVictor Oliveira
11
New contributor
Victor Oliveira 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 |
$begingroup$
You can calculate mean target for each categorical variable and compare its values.
In pandas this can be done easily: df.groupby('categorical_feature').target.mean()
Then you can make a histogram to compare the approach. I also, seaborn has a catplot, where it do the same as above in a bar plot format, showing mean value for target variable based on each categorical one.
answered 17 hours ago
Victor OliveiraVictor Oliveira
11
New contributor
Victor Oliveira 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 |
$begingroup$
You can calculate mean target for each categorical variable and compare its values.
In pandas this can be done easily: df.groupby('categorical_feature').target.mean()
Then you can make a histogram to compare the approach. I also, seaborn has a catplot, where it do the same as above in a bar plot format, showing mean value for target variable based on each categorical one.
answered 17 hours ago
Victor OliveiraVictor Oliveira
11
New contributor
Victor Oliveira is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
You can calculate mean target for each categorical variable and compare its values.
In pandas this can be done easily: df.groupby('categorical_feature').target.mean()
Then you can make a histogram to compare the approach. I also, seaborn has a catplot, where it do the same as above in a bar plot format, showing mean value for target variable based on each categorical one.
answered 17 hours ago
Victor OliveiraVictor Oliveira
11
New contributor
Victor Oliveira is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 17 hours ago
Victor OliveiraVictor Oliveira
11
New contributor
Victor Oliveira is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 17 hours ago
Victor OliveiraVictor Oliveira
11
answered 17 hours ago
Victor OliveiraVictor Oliveira
11
11
New contributor
Victor Oliveira is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Victor Oliveira is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Victor Oliveira is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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