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Assigning a variable in Python using analogue of '.format()'

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0

I have a dataset with several columns of which I want to convert from categorical to numerical dtype.

I have defined the following function:

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 dictionary.format(str(column)+'_cat')=dict(zip(df[column],df[str(column)+'_cat']))
 return dictionary.format(str(column)+'_cat')

I also want this function to create a dictionary so I will be able to understand what label was assigned to what value.

The problem here arises with naming of a dictionary as I have tried to use '.format()' and it has shown syntax error.

dictionary.format(str(column)+'_cat')=dict(zip(df.column,df[str(column)+'_cat']))

>SyntaxError: invalid syntax

I understand that this particular method works with strings but is there any way to 'automate' the naming of variable?

Thanks in advance.

python

share|improve this question

edited Mar 30 at 18:34

user641597

asked Mar 30 at 16:57

user641597user641597

11

migrated from datascience.stackexchange.com Mar 30 at 18:27

This question came from our site for Data science professionals, Machine Learning specialists, and those interested in learning more about the field.

add a comment | 

0

I have a dataset with several columns of which I want to convert from categorical to numerical dtype.

I have defined the following function:

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 dictionary.format(str(column)+'_cat')=dict(zip(df[column],df[str(column)+'_cat']))
 return dictionary.format(str(column)+'_cat')

I also want this function to create a dictionary so I will be able to understand what label was assigned to what value.

The problem here arises with naming of a dictionary as I have tried to use '.format()' and it has shown syntax error.

dictionary.format(str(column)+'_cat')=dict(zip(df.column,df[str(column)+'_cat']))

>SyntaxError: invalid syntax

I understand that this particular method works with strings but is there any way to 'automate' the naming of variable?

Thanks in advance.

python

share|improve this question

edited Mar 30 at 18:34

user641597

asked Mar 30 at 16:57

user641597user641597

11

migrated from datascience.stackexchange.com Mar 30 at 18:27

This question came from our site for Data science professionals, Machine Learning specialists, and those interested in learning more about the field.

add a comment | 

I have a dataset with several columns of which I want to convert from categorical to numerical dtype.

I have defined the following function:

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 dictionary.format(str(column)+'_cat')=dict(zip(df[column],df[str(column)+'_cat']))
 return dictionary.format(str(column)+'_cat')

I also want this function to create a dictionary so I will be able to understand what label was assigned to what value.

The problem here arises with naming of a dictionary as I have tried to use '.format()' and it has shown syntax error.

dictionary.format(str(column)+'_cat')=dict(zip(df.column,df[str(column)+'_cat']))

>SyntaxError: invalid syntax

I understand that this particular method works with strings but is there any way to 'automate' the naming of variable?

Thanks in advance.

python

share|improve this question

edited Mar 30 at 18:34

user641597

asked Mar 30 at 16:57

user641597user641597

11

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 dictionary.format(str(column)+'_cat')=dict(zip(df[column],df[str(column)+'_cat']))
 return dictionary.format(str(column)+'_cat')

share|improve this question

edited Mar 30 at 18:34

user641597

asked Mar 30 at 16:57

user641597user641597

11

share|improve this question

edited Mar 30 at 18:34

user641597

asked Mar 30 at 16:57

user641597user641597

11

asked Mar 30 at 16:57

user641597user641597

11

asked Mar 30 at 16:57

user641597user641597

11

1 Answer
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0

You cannot "dynamically" name a variable, and there is no need to do so. Simply return the dictionary:

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 return dict(zip(df.column,df[str(column)+'_cat']))

(There is a way to create variables or more generally objects with dynamic names in Python, but that's only very rarely useful.)

share|improve this answer

answered Mar 30 at 18:33

IonicSolutionsIonicSolutions

962718

add a comment | 

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0

You cannot "dynamically" name a variable, and there is no need to do so. Simply return the dictionary:

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 return dict(zip(df.column,df[str(column)+'_cat']))

(There is a way to create variables or more generally objects with dynamic names in Python, but that's only very rarely useful.)

share|improve this answer

answered Mar 30 at 18:33

IonicSolutionsIonicSolutions

962718

add a comment | 

0

You cannot "dynamically" name a variable, and there is no need to do so. Simply return the dictionary:

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 return dict(zip(df.column,df[str(column)+'_cat']))

(There is a way to create variables or more generally objects with dynamic names in Python, but that's only very rarely useful.)

share|improve this answer

answered Mar 30 at 18:33

IonicSolutionsIonicSolutions

962718

add a comment | 

You cannot "dynamically" name a variable, and there is no need to do so. Simply return the dictionary:

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 return dict(zip(df.column,df[str(column)+'_cat']))

(There is a way to create variables or more generally objects with dynamic names in Python, but that's only very rarely useful.)

share|improve this answer

answered Mar 30 at 18:33

IonicSolutionsIonicSolutions

962718

def create_num_column(df,column):
 df[str(column)]=df[str(column)].astype('category')
 df[str(column)+'_cat']=df[str(column)].cat.codes

 return dict(zip(df.column,df[str(column)+'_cat']))

share|improve this answer

answered Mar 30 at 18:33

IonicSolutionsIonicSolutions

962718

answered Mar 30 at 18:33

IonicSolutionsIonicSolutions

962718

answered Mar 30 at 18:33

IonicSolutionsIonicSolutions

962718