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Data Frame Row Value Correlation

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0

1

How do I find the correlation between the following fields for each row value in the Product_Code column based on the following df?

I have already tried df.corr() with no success.

The actual data frame is 2mm+ rows. Sample data frame below:

df = pd.DataFrame ‘Company_Numb’: ["125", "137", "129"],
'Year' : [“2016”, ”2017”, “2018”],'Product_Code' : [“Batteries”, “Clothes”, “Tablet”],'Sales_Success_Code' : [0, 1, 0],‘Peer_Group_Rank’ : [65.65, 41.24, 16.12],‘Store_Count’ : [5, 14, 2],‘Employee_Count’ : [74, 19, 10]

• What is the correlation between Sales_Success_Code and Peer_Group_Rank for each product code

• What is the correlation between Sales_Success_Code and Store_Count for each product code

• What is the correlation between Sales_Success_Code and Employee_count for each product code

Thank You,

python-3.x pandas correlation

share|improve this question

edited Mar 26 at 22:50

Regul8or

asked Mar 26 at 21:35

Regul8orRegul8or

855 bronze badges

add a comment | 

0

1

How do I find the correlation between the following fields for each row value in the Product_Code column based on the following df?

I have already tried df.corr() with no success.

The actual data frame is 2mm+ rows. Sample data frame below:

df = pd.DataFrame ‘Company_Numb’: ["125", "137", "129"],
'Year' : [“2016”, ”2017”, “2018”],'Product_Code' : [“Batteries”, “Clothes”, “Tablet”],'Sales_Success_Code' : [0, 1, 0],‘Peer_Group_Rank’ : [65.65, 41.24, 16.12],‘Store_Count’ : [5, 14, 2],‘Employee_Count’ : [74, 19, 10]

• What is the correlation between Sales_Success_Code and Peer_Group_Rank for each product code

• What is the correlation between Sales_Success_Code and Store_Count for each product code

• What is the correlation between Sales_Success_Code and Employee_count for each product code

Thank You,

python-3.x pandas correlation

share|improve this question

edited Mar 26 at 22:50

Regul8or

asked Mar 26 at 21:35

Regul8orRegul8or

855 bronze badges

add a comment | 

How do I find the correlation between the following fields for each row value in the Product_Code column based on the following df?

I have already tried df.corr() with no success.

The actual data frame is 2mm+ rows. Sample data frame below:

df = pd.DataFrame ‘Company_Numb’: ["125", "137", "129"],
'Year' : [“2016”, ”2017”, “2018”],'Product_Code' : [“Batteries”, “Clothes”, “Tablet”],'Sales_Success_Code' : [0, 1, 0],‘Peer_Group_Rank’ : [65.65, 41.24, 16.12],‘Store_Count’ : [5, 14, 2],‘Employee_Count’ : [74, 19, 10]

• What is the correlation between Sales_Success_Code and Peer_Group_Rank for each product code

• What is the correlation between Sales_Success_Code and Store_Count for each product code

• What is the correlation between Sales_Success_Code and Employee_count for each product code

Thank You,

python-3.x pandas correlation

share|improve this question

edited Mar 26 at 22:50

Regul8or

asked Mar 26 at 21:35

Regul8orRegul8or

855 bronze badges

df = pd.DataFrame ‘Company_Numb’: ["125", "137", "129"],
'Year' : [“2016”, ”2017”, “2018”],'Product_Code' : [“Batteries”, “Clothes”, “Tablet”],'Sales_Success_Code' : [0, 1, 0],‘Peer_Group_Rank’ : [65.65, 41.24, 16.12],‘Store_Count’ : [5, 14, 2],‘Employee_Count’ : [74, 19, 10]

share|improve this question

edited Mar 26 at 22:50

Regul8or

asked Mar 26 at 21:35

Regul8orRegul8or

855 bronze badges

share|improve this question

edited Mar 26 at 22:50

Regul8or

asked Mar 26 at 21:35

Regul8orRegul8or

855 bronze badges

asked Mar 26 at 21:35

Regul8orRegul8or

855 bronze badges

asked Mar 26 at 21:35

Regul8orRegul8or

855 bronze badges

2 Answers
2

active

oldest

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0

I used the same code as yours and got the result. Just initialized the pandas object and that's it.

df = pd.DataFrame('Company_Numb': ["125", "137", "129"],
 'Year': ['2016', '2017', '2018'], 'Product_Code': ['Batteries', 'Clothes', 'Tablet'], 'Sales_Success_Code': [0, 1, 0], 'Peer_Group_Rank': [65.65, 41.24, 16.12], 'Store_Count': [5, 14, 2], 'Employee_Count': [74, 19, 10])

print(df.corr())

#OUTPUT:
 Employee_Count ... Store_Count
Employee_Count 1.000000 ... -0.150210
Peer_Group_Rank 0.920429 ... 0.248218
Sales_Success_Code -0.383280 ... 0.970725
Store_Count -0.150210 ... 1.000000

share|improve this answer

answered Mar 26 at 22:01

RobexRobex

1733 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Robex, I was able to get to that point; however, I am trying to find the correlation for each Product_Code. So column zero of the output would read: 'Batteries', 'Clothes', 'Tablet'. Thanks
  
  – Regul8or
  Mar 26 at 22:40
  
  

  
  
  
  

add a comment | 

0

It is not possible to find a correlation of a single item in the list. Correlation in itself is used the measure the changes between two vectors. It's because of how the Pearson formula calculates correlation with the standard deviation and covariances of the two vectors.
However, there is a solution to finding the correlation coefficient of an individual column with relation to another column.

print(df.Sales_Success_Code.corr(df.Peer_Group_Rank))

share|improve this answer

answered Mar 26 at 23:33

RobexRobex

1733 bronze badges

add a comment | 

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0

I used the same code as yours and got the result. Just initialized the pandas object and that's it.

df = pd.DataFrame('Company_Numb': ["125", "137", "129"],
 'Year': ['2016', '2017', '2018'], 'Product_Code': ['Batteries', 'Clothes', 'Tablet'], 'Sales_Success_Code': [0, 1, 0], 'Peer_Group_Rank': [65.65, 41.24, 16.12], 'Store_Count': [5, 14, 2], 'Employee_Count': [74, 19, 10])

print(df.corr())

#OUTPUT:
 Employee_Count ... Store_Count
Employee_Count 1.000000 ... -0.150210
Peer_Group_Rank 0.920429 ... 0.248218
Sales_Success_Code -0.383280 ... 0.970725
Store_Count -0.150210 ... 1.000000

share|improve this answer

answered Mar 26 at 22:01

RobexRobex

1733 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Robex, I was able to get to that point; however, I am trying to find the correlation for each Product_Code. So column zero of the output would read: 'Batteries', 'Clothes', 'Tablet'. Thanks
  
  – Regul8or
  Mar 26 at 22:40
  
  

  
  
  
  

add a comment | 

0

I used the same code as yours and got the result. Just initialized the pandas object and that's it.

df = pd.DataFrame('Company_Numb': ["125", "137", "129"],
 'Year': ['2016', '2017', '2018'], 'Product_Code': ['Batteries', 'Clothes', 'Tablet'], 'Sales_Success_Code': [0, 1, 0], 'Peer_Group_Rank': [65.65, 41.24, 16.12], 'Store_Count': [5, 14, 2], 'Employee_Count': [74, 19, 10])

print(df.corr())

#OUTPUT:
 Employee_Count ... Store_Count
Employee_Count 1.000000 ... -0.150210
Peer_Group_Rank 0.920429 ... 0.248218
Sales_Success_Code -0.383280 ... 0.970725
Store_Count -0.150210 ... 1.000000

share|improve this answer

answered Mar 26 at 22:01

RobexRobex

1733 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Robex, I was able to get to that point; however, I am trying to find the correlation for each Product_Code. So column zero of the output would read: 'Batteries', 'Clothes', 'Tablet'. Thanks
  
  – Regul8or
  Mar 26 at 22:40
  
  

  
  
  
  

add a comment | 

I used the same code as yours and got the result. Just initialized the pandas object and that's it.

df = pd.DataFrame('Company_Numb': ["125", "137", "129"],
 'Year': ['2016', '2017', '2018'], 'Product_Code': ['Batteries', 'Clothes', 'Tablet'], 'Sales_Success_Code': [0, 1, 0], 'Peer_Group_Rank': [65.65, 41.24, 16.12], 'Store_Count': [5, 14, 2], 'Employee_Count': [74, 19, 10])

print(df.corr())

#OUTPUT:
 Employee_Count ... Store_Count
Employee_Count 1.000000 ... -0.150210
Peer_Group_Rank 0.920429 ... 0.248218
Sales_Success_Code -0.383280 ... 0.970725
Store_Count -0.150210 ... 1.000000

share|improve this answer

answered Mar 26 at 22:01

RobexRobex

1733 bronze badges

df = pd.DataFrame('Company_Numb': ["125", "137", "129"],
 'Year': ['2016', '2017', '2018'], 'Product_Code': ['Batteries', 'Clothes', 'Tablet'], 'Sales_Success_Code': [0, 1, 0], 'Peer_Group_Rank': [65.65, 41.24, 16.12], 'Store_Count': [5, 14, 2], 'Employee_Count': [74, 19, 10])

print(df.corr())

#OUTPUT:
 Employee_Count ... Store_Count
Employee_Count 1.000000 ... -0.150210
Peer_Group_Rank 0.920429 ... 0.248218
Sales_Success_Code -0.383280 ... 0.970725
Store_Count -0.150210 ... 1.000000

share|improve this answer

answered Mar 26 at 22:01

RobexRobex

1733 bronze badges

answered Mar 26 at 22:01

RobexRobex

1733 bronze badges

answered Mar 26 at 22:01

RobexRobex

1733 bronze badges

0

It is not possible to find a correlation of a single item in the list. Correlation in itself is used the measure the changes between two vectors. It's because of how the Pearson formula calculates correlation with the standard deviation and covariances of the two vectors.
However, there is a solution to finding the correlation coefficient of an individual column with relation to another column.

print(df.Sales_Success_Code.corr(df.Peer_Group_Rank))

share|improve this answer

answered Mar 26 at 23:33

RobexRobex

1733 bronze badges

add a comment | 

0

It is not possible to find a correlation of a single item in the list. Correlation in itself is used the measure the changes between two vectors. It's because of how the Pearson formula calculates correlation with the standard deviation and covariances of the two vectors.
However, there is a solution to finding the correlation coefficient of an individual column with relation to another column.

print(df.Sales_Success_Code.corr(df.Peer_Group_Rank))

share|improve this answer

answered Mar 26 at 23:33

RobexRobex

1733 bronze badges

add a comment | 

It is not possible to find a correlation of a single item in the list. Correlation in itself is used the measure the changes between two vectors. It's because of how the Pearson formula calculates correlation with the standard deviation and covariances of the two vectors.
However, there is a solution to finding the correlation coefficient of an individual column with relation to another column.

print(df.Sales_Success_Code.corr(df.Peer_Group_Rank))

share|improve this answer

answered Mar 26 at 23:33

RobexRobex

1733 bronze badges

print(df.Sales_Success_Code.corr(df.Peer_Group_Rank))

share|improve this answer

answered Mar 26 at 23:33

RobexRobex

1733 bronze badges

answered Mar 26 at 23:33

RobexRobex

1733 bronze badges

answered Mar 26 at 23:33

RobexRobex

1733 bronze badges