Trying to change pandas column dtype from str to float
$begingroup$
I am trying to convert a pandas column from a str to a float. Before I convert the strings to floats using astype(float), I need to remove characters from the string which cannot be converted into floats, like a comma or a space. In trying to remove these characters, I am using list compression and the str.replace method like this:
data.loc[:,'column_name'] = [char.replace(',', '') for char in
data.loc[:,'column_name']]
but I am getting an error saying:
AttributeError: 'float' object has no attribute 'replace'.
The confusing part, though, is that when I look at the dtypes, the dtype for that column shows up as 'o', or object. So I have no idea what is going on.
python pandas
edited 15 hours ago
Siong Thye Goh
1,122418
asked 19 hours ago
SebastianSebastian
12
New contributor
Sebastian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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add a comment |
$begingroup$
I am trying to convert a pandas column from a str to a float. Before I convert the strings to floats using astype(float), I need to remove characters from the string which cannot be converted into floats, like a comma or a space. In trying to remove these characters, I am using list compression and the str.replace method like this:
data.loc[:,'column_name'] = [char.replace(',', '') for char in
data.loc[:,'column_name']]
but I am getting an error saying:
AttributeError: 'float' object has no attribute 'replace'.
The confusing part, though, is that when I look at the dtypes, the dtype for that column shows up as 'o', or object. So I have no idea what is going on.
python pandas
edited 15 hours ago
Siong Thye Goh
1,122418
asked 19 hours ago
SebastianSebastian
12
New contributor
Sebastian 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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1
$begingroup$
look at set([type(x) for x in data['column_name'].values] - a common problem is that it has some NaN values which are float, not string.
$endgroup$
– Valentas
18 hours ago
$begingroup$
The question is about programming, not about Data Science, it is better if you move your question to StackOverflow.
$endgroup$
– omar
18 hours ago
add a comment |
$begingroup$
I am trying to convert a pandas column from a str to a float. Before I convert the strings to floats using astype(float), I need to remove characters from the string which cannot be converted into floats, like a comma or a space. In trying to remove these characters, I am using list compression and the str.replace method like this:
data.loc[:,'column_name'] = [char.replace(',', '') for char in
data.loc[:,'column_name']]
but I am getting an error saying:
AttributeError: 'float' object has no attribute 'replace'.
The confusing part, though, is that when I look at the dtypes, the dtype for that column shows up as 'o', or object. So I have no idea what is going on.
python pandas
edited 15 hours ago
Siong Thye Goh
1,122418
asked 19 hours ago
SebastianSebastian
12
New contributor
Sebastian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am trying to convert a pandas column from a str to a float. Before I convert the strings to floats using astype(float), I need to remove characters from the string which cannot be converted into floats, like a comma or a space. In trying to remove these characters, I am using list compression and the str.replace method like this:
data.loc[:,'column_name'] = [char.replace(',', '') for char in
data.loc[:,'column_name']]
but I am getting an error saying:
AttributeError: 'float' object has no attribute 'replace'.
The confusing part, though, is that when I look at the dtypes, the dtype for that column shows up as 'o', or object. So I have no idea what is going on.
python pandas
python pandas
edited 15 hours ago
Siong Thye Goh
1,122418
asked 19 hours ago
SebastianSebastian
12
New contributor
Sebastian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 15 hours ago
Siong Thye Goh
1,122418
asked 19 hours ago
SebastianSebastian
12
New contributor
Sebastian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 15 hours ago
Siong Thye Goh
1,122418
edited 15 hours ago
Siong Thye Goh
1,122418
edited 15 hours ago
Siong Thye Goh
1,122418
1,122418
asked 19 hours ago
SebastianSebastian
12
New contributor
Sebastian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 19 hours ago
SebastianSebastian
12
asked 19 hours ago
SebastianSebastian
12
12
New contributor
Sebastian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Sebastian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Sebastian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
1
$begingroup$
look at set([type(x) for x in data['column_name'].values] - a common problem is that it has some NaN values which are float, not string.
$endgroup$
– Valentas
18 hours ago
$begingroup$
The question is about programming, not about Data Science, it is better if you move your question to StackOverflow.
$endgroup$
– omar
18 hours ago
add a comment |
1
$begingroup$
look at set([type(x) for x in data['column_name'].values] - a common problem is that it has some NaN values which are float, not string.
$endgroup$
– Valentas
18 hours ago
$begingroup$
The question is about programming, not about Data Science, it is better if you move your question to StackOverflow.
$endgroup$
– omar
18 hours ago
1
1
$begingroup$
look at set([type(x) for x in data['column_name'].values] - a common problem is that it has some NaN values which are float, not string.
$endgroup$
– Valentas
18 hours ago
$begingroup$
look at set([type(x) for x in data['column_name'].values] - a common problem is that it has some NaN values which are float, not string.
$endgroup$
– Valentas
18 hours ago
$begingroup$
The question is about programming, not about Data Science, it is better if you move your question to StackOverflow.
$endgroup$
– omar
18 hours ago
$begingroup$
The question is about programming, not about Data Science, it is better if you move your question to StackOverflow.
$endgroup$
– omar
18 hours ago
add a comment |
2 Answers
2
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$begingroup$
In pandas the object type is used when there is not a clear distinction between the types stored in the column.
So, I guess that in your column, some objects are float type and some objects are str type. Or maybe, you are also dealing with NaN objects, NaN objects are float objects.
a) Convert the column to string: Are you getting your DataFrame from a CSV or XLS format file? Then at the moment of reading the file, you can specify that that column is an str type or just make the type conversion of the column you are dealing with.
b) After that, you can apply the string changes and/or deal with the NaN objects.
c) Finally, you transform your column into float type`.
answered 18 hours ago
omaromar
16114
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add a comment |
$begingroup$
Maybe it's a very rudimentary method but I would just do
listt =
for i in data['column_name']:
listt.append(float(i))
data['FloatData'] = listt
answered 15 hours ago
Armando DelgadoArmando Delgado
1
New contributor
Armando Delgado is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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add a comment |
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2 Answers
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$begingroup$
In pandas the object type is used when there is not a clear distinction between the types stored in the column.
So, I guess that in your column, some objects are float type and some objects are str type. Or maybe, you are also dealing with NaN objects, NaN objects are float objects.
a) Convert the column to string: Are you getting your DataFrame from a CSV or XLS format file? Then at the moment of reading the file, you can specify that that column is an str type or just make the type conversion of the column you are dealing with.
b) After that, you can apply the string changes and/or deal with the NaN objects.
c) Finally, you transform your column into float type`.
answered 18 hours ago
omaromar
16114
$endgroup$
add a comment |
$begingroup$
In pandas the object type is used when there is not a clear distinction between the types stored in the column.
So, I guess that in your column, some objects are float type and some objects are str type. Or maybe, you are also dealing with NaN objects, NaN objects are float objects.
a) Convert the column to string: Are you getting your DataFrame from a CSV or XLS format file? Then at the moment of reading the file, you can specify that that column is an str type or just make the type conversion of the column you are dealing with.
b) After that, you can apply the string changes and/or deal with the NaN objects.
c) Finally, you transform your column into float type`.
answered 18 hours ago
omaromar
16114
$endgroup$
add a comment |
$begingroup$
In pandas the object type is used when there is not a clear distinction between the types stored in the column.
So, I guess that in your column, some objects are float type and some objects are str type. Or maybe, you are also dealing with NaN objects, NaN objects are float objects.
a) Convert the column to string: Are you getting your DataFrame from a CSV or XLS format file? Then at the moment of reading the file, you can specify that that column is an str type or just make the type conversion of the column you are dealing with.
b) After that, you can apply the string changes and/or deal with the NaN objects.
c) Finally, you transform your column into float type`.
answered 18 hours ago
omaromar
16114
$endgroup$
In pandas the object type is used when there is not a clear distinction between the types stored in the column.
So, I guess that in your column, some objects are float type and some objects are str type. Or maybe, you are also dealing with NaN objects, NaN objects are float objects.
a) Convert the column to string: Are you getting your DataFrame from a CSV or XLS format file? Then at the moment of reading the file, you can specify that that column is an str type or just make the type conversion of the column you are dealing with.
b) After that, you can apply the string changes and/or deal with the NaN objects.
c) Finally, you transform your column into float type`.
answered 18 hours ago
omaromar
16114
edited 18 hours ago
answered 18 hours ago
omaromar
16114
answered 18 hours ago
omaromar
16114
answered 18 hours ago
omaromar
16114
16114
add a comment |
add a comment |
$begingroup$
Maybe it's a very rudimentary method but I would just do
listt =
for i in data['column_name']:
listt.append(float(i))
data['FloatData'] = listt
answered 15 hours ago
Armando DelgadoArmando Delgado
1
New contributor
Armando Delgado 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 |
$begingroup$
Maybe it's a very rudimentary method but I would just do
listt =
for i in data['column_name']:
listt.append(float(i))
data['FloatData'] = listt
answered 15 hours ago
Armando DelgadoArmando Delgado
1
New contributor
Armando Delgado 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 |
$begingroup$
Maybe it's a very rudimentary method but I would just do
listt =
for i in data['column_name']:
listt.append(float(i))
data['FloatData'] = listt
answered 15 hours ago
Armando DelgadoArmando Delgado
1
New contributor
Armando Delgado is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
Maybe it's a very rudimentary method but I would just do
listt =
for i in data['column_name']:
listt.append(float(i))
data['FloatData'] = listt
answered 15 hours ago
Armando DelgadoArmando Delgado
1
New contributor
Armando Delgado is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 15 hours ago
Armando DelgadoArmando Delgado
1
New contributor
Armando Delgado is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 15 hours ago
Armando DelgadoArmando Delgado
1
answered 15 hours ago
Armando DelgadoArmando Delgado
1
1
New contributor
Armando Delgado is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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New contributor
Armando Delgado is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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1
$begingroup$
look at set([type(x) for x in data['column_name'].values] - a common problem is that it has some NaN values which are float, not string.
$endgroup$
– Valentas
18 hours ago
$begingroup$
The question is about programming, not about Data Science, it is better if you move your question to StackOverflow.
$endgroup$
– omar
18 hours ago