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How to transform entire pandas data frame in one hot representation?

0

$begingroup$

I want all the columns one hot encoded without the need of listing out the columns or apply one hot encode one by one. I know how to do it one column then another.

scikit-learn pandas dataframe

share|improve this question

edited Apr 2 at 1:17

Stephen Rauch♦

1,52551330

asked Mar 12 at 18:21

Ishrak Alaxander HasinIshrak Alaxander Hasin

154

$endgroup$

add a comment | 

0

$begingroup$

I want all the columns one hot encoded without the need of listing out the columns or apply one hot encode one by one. I know how to do it one column then another.

scikit-learn pandas dataframe

share|improve this question

edited Apr 2 at 1:17

Stephen Rauch♦

1,52551330

asked Mar 12 at 18:21

Ishrak Alaxander HasinIshrak Alaxander Hasin

154

$endgroup$

add a comment | 

$begingroup$

I want all the columns one hot encoded without the need of listing out the columns or apply one hot encode one by one. I know how to do it one column then another.

scikit-learn pandas dataframe

share|improve this question

edited Apr 2 at 1:17

Stephen Rauch♦

1,52551330

asked Mar 12 at 18:21

Ishrak Alaxander HasinIshrak Alaxander Hasin

154

$endgroup$

share|improve this question

edited Apr 2 at 1:17

Stephen Rauch♦

1,52551330

asked Mar 12 at 18:21

Ishrak Alaxander HasinIshrak Alaxander Hasin

154

share|improve this question

edited Apr 2 at 1:17

Stephen Rauch♦

1,52551330

asked Mar 12 at 18:21

Ishrak Alaxander HasinIshrak Alaxander Hasin

154

edited Apr 2 at 1:17

Stephen Rauch♦

1,52551330

edited Apr 2 at 1:17

Stephen Rauch♦

1,52551330

asked Mar 12 at 18:21

Ishrak Alaxander HasinIshrak Alaxander Hasin

154

asked Mar 12 at 18:21

Ishrak Alaxander HasinIshrak Alaxander Hasin

154

1 Answer
1

active

oldest

votes

4

$begingroup$

You can use:: pandas.get_dummies

get_dummies will only convert string columns and will keep numerical columns as it is. You can first convert categorical columns into string type and then apply get_dummies.

concated_dataset['1stFlrSF'] = concated_dataset['1stFlrSF'].astype("string")
pd.get_dummies(cacated_dataset)

share|improve this answer

edited Mar 12 at 19:09

n1k31t4

6,5312421

answered Mar 12 at 18:29

PreetPreet

4585

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Yeah then first convert all the columns you want to be one hot encoded into string type and then apply get_dummies on the whole dataframe.
  $endgroup$
  – Preet
  Mar 12 at 19:00
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Thanks a lot that worked.
  $endgroup$
  – Ishrak Alaxander Hasin
  Mar 12 at 19:01
  

  
  
  
  

add a comment | 

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4

$begingroup$

You can use:: pandas.get_dummies

get_dummies will only convert string columns and will keep numerical columns as it is. You can first convert categorical columns into string type and then apply get_dummies.

concated_dataset['1stFlrSF'] = concated_dataset['1stFlrSF'].astype("string")
pd.get_dummies(cacated_dataset)

share|improve this answer

edited Mar 12 at 19:09

n1k31t4

6,5312421

answered Mar 12 at 18:29

PreetPreet

4585

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Yeah then first convert all the columns you want to be one hot encoded into string type and then apply get_dummies on the whole dataframe.
  $endgroup$
  – Preet
  Mar 12 at 19:00
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Thanks a lot that worked.
  $endgroup$
  – Ishrak Alaxander Hasin
  Mar 12 at 19:01
  

  
  
  
  

add a comment | 

4

$begingroup$

You can use:: pandas.get_dummies

get_dummies will only convert string columns and will keep numerical columns as it is. You can first convert categorical columns into string type and then apply get_dummies.

concated_dataset['1stFlrSF'] = concated_dataset['1stFlrSF'].astype("string")
pd.get_dummies(cacated_dataset)

share|improve this answer

edited Mar 12 at 19:09

n1k31t4

6,5312421

answered Mar 12 at 18:29

PreetPreet

4585

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Yeah then first convert all the columns you want to be one hot encoded into string type and then apply get_dummies on the whole dataframe.
  $endgroup$
  – Preet
  Mar 12 at 19:00
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Thanks a lot that worked.
  $endgroup$
  – Ishrak Alaxander Hasin
  Mar 12 at 19:01
  

  
  
  
  

add a comment | 

$begingroup$

You can use:: pandas.get_dummies

get_dummies will only convert string columns and will keep numerical columns as it is. You can first convert categorical columns into string type and then apply get_dummies.

concated_dataset['1stFlrSF'] = concated_dataset['1stFlrSF'].astype("string")
pd.get_dummies(cacated_dataset)

share|improve this answer

edited Mar 12 at 19:09

n1k31t4

6,5312421

answered Mar 12 at 18:29

PreetPreet

4585

$endgroup$

concated_dataset['1stFlrSF'] = concated_dataset['1stFlrSF'].astype("string")
pd.get_dummies(cacated_dataset)

share|improve this answer

edited Mar 12 at 19:09

n1k31t4

6,5312421

answered Mar 12 at 18:29

PreetPreet

4585

edited Mar 12 at 19:09

n1k31t4

6,5312421

edited Mar 12 at 19:09

n1k31t4

6,5312421

answered Mar 12 at 18:29

PreetPreet

4585

answered Mar 12 at 18:29

PreetPreet

4585