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Assigning a variable in Python using analogue of '.format()'
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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
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
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
asked Mar 30 at 16:57
user641597user641597
11
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
python
asked Mar 30 at 16:57
user641597user641597
11
asked Mar 30 at 16:57
user641597user641597
11
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
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.
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 |
add a comment |
1 Answer
1
active
oldest
votes
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.)
answered Mar 30 at 18:33
IonicSolutionsIonicSolutions
962718
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
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.)
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.)
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.)
answered Mar 30 at 18:33
IonicSolutionsIonicSolutions
962718
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.)
answered Mar 30 at 18:33
IonicSolutionsIonicSolutions
962718
answered Mar 30 at 18:33
IonicSolutionsIonicSolutions
962718
answered Mar 30 at 18:33
IonicSolutionsIonicSolutions
962718
answered Mar 30 at 18:33
IonicSolutionsIonicSolutions
962718
962718
add a comment |
add a comment |
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