Function to check if object-dtype column value is float or string
1
I am trying to write a function which is equal to isnumber[column] function in excel
dataset:
feature1 feature2 feature3
123 1.07 1
231 2.08 3
122 ab 4
111 3.04 6
555 cde 8
feature1: integer dtype
feature2: object dtype
feature3: integer dtype
I tried this piece of code
for item in df.feature2.iteritems():
if isinstance(item, float):
print('yes')
else:
print('no')
I got the result as
no
no
no
no
no
But i want the result as
yes
yes
no
yes
no
When i tried to check the type of individual feature2 values, this is what see
type(df.feature2[0]) = str
type(df.feature2[1]) = str
type(df.feature2[2]) = str
type(df.feature2[3]) = str
type(df.feature2[4]) = str
But clearly 0,1,3 should be shown as float, but they show up as str
What am i doing wrong?
python python-3.x python-2.7 user-defined-types isinstance
asked Nov 21 '18 at 18:26
Sai SumanthSai Sumanth
313
add a comment |
1
I am trying to write a function which is equal to isnumber[column] function in excel
dataset:
feature1 feature2 feature3
123 1.07 1
231 2.08 3
122 ab 4
111 3.04 6
555 cde 8
feature1: integer dtype
feature2: object dtype
feature3: integer dtype
I tried this piece of code
for item in df.feature2.iteritems():
if isinstance(item, float):
print('yes')
else:
print('no')
I got the result as
no
no
no
no
no
But i want the result as
yes
yes
no
yes
no
When i tried to check the type of individual feature2 values, this is what see
type(df.feature2[0]) = str
type(df.feature2[1]) = str
type(df.feature2[2]) = str
type(df.feature2[3]) = str
type(df.feature2[4]) = str
But clearly 0,1,3 should be shown as float, but they show up as str
What am i doing wrong?
python python-3.x python-2.7 user-defined-types isinstance
asked Nov 21 '18 at 18:26
Sai SumanthSai Sumanth
313
add a comment |
1
1
1
I am trying to write a function which is equal to isnumber[column] function in excel
dataset:
feature1 feature2 feature3
123 1.07 1
231 2.08 3
122 ab 4
111 3.04 6
555 cde 8
feature1: integer dtype
feature2: object dtype
feature3: integer dtype
I tried this piece of code
for item in df.feature2.iteritems():
if isinstance(item, float):
print('yes')
else:
print('no')
I got the result as
no
no
no
no
no
But i want the result as
yes
yes
no
yes
no
When i tried to check the type of individual feature2 values, this is what see
type(df.feature2[0]) = str
type(df.feature2[1]) = str
type(df.feature2[2]) = str
type(df.feature2[3]) = str
type(df.feature2[4]) = str
But clearly 0,1,3 should be shown as float, but they show up as str
What am i doing wrong?
python python-3.x python-2.7 user-defined-types isinstance
asked Nov 21 '18 at 18:26
Sai SumanthSai Sumanth
313
I am trying to write a function which is equal to isnumber[column] function in excel
dataset:
feature1 feature2 feature3
123 1.07 1
231 2.08 3
122 ab 4
111 3.04 6
555 cde 8
feature1: integer dtype
feature2: object dtype
feature3: integer dtype
I tried this piece of code
for item in df.feature2.iteritems():
if isinstance(item, float):
print('yes')
else:
print('no')
I got the result as
no
no
no
no
no
But i want the result as
yes
yes
no
yes
no
When i tried to check the type of individual feature2 values, this is what see
type(df.feature2[0]) = str
type(df.feature2[1]) = str
type(df.feature2[2]) = str
type(df.feature2[3]) = str
type(df.feature2[4]) = str
But clearly 0,1,3 should be shown as float, but they show up as str
What am i doing wrong?
python python-3.x python-2.7 user-defined-types isinstance
python python-3.x python-2.7 user-defined-types isinstance
asked Nov 21 '18 at 18:26
Sai SumanthSai Sumanth
313
asked Nov 21 '18 at 18:26
Sai SumanthSai Sumanth
313
edited Nov 21 '18 at 18:52
Sai Sumanth
asked Nov 21 '18 at 18:26
Sai SumanthSai Sumanth
313
asked Nov 21 '18 at 18:26
Sai SumanthSai Sumanth
313
asked Nov 21 '18 at 18:26
Sai SumanthSai Sumanth
313
313
add a comment |
add a comment |
4 Answers
4
active
oldest
votes
1
Iteritems is returning a tuple, ((123, '1.07'), 1.07) and since you want to loop over each value try the below code.
You just need to remove .iteritems() and it will work like a charm.
df['feature2']=[1.07,2.08,'ab',3.04,'cde']
for item in df.feature2:
if isinstance(item,float):
print('yes')
else:
print('no')
Here is your output:
yes
yes
no
yes
no
answered Nov 21 '18 at 18:42
Ankur GulatiAnkur Gulati
14510
If it helps, please care to accept and upvote the answer. Thanks :)
– Ankur Gulati
Nov 21 '18 at 18:43
Sorry, it did not work. I'm not sure why
– Sai Sumanth
Nov 21 '18 at 18:58
@SaiSumanth Can you tell me what's the error? I included the data frame creation line that I used for testing and it is working from me. Also, I am using Python3
– Ankur Gulati
Nov 21 '18 at 19:03
Its working now, actually my features values were in 'float string' type instead of float type. Thanks
– Sai Sumanth
Nov 21 '18 at 19:20
No Problem. Please accept the answer.
– Ankur Gulati
Nov 21 '18 at 19:30
add a comment |
0
Try this:
for i in range(len(df["feature2"])):
test = df.loc[i,"feature2"]
if isinstance(test, float):
print('yes')
else:
print('no')
answered Nov 21 '18 at 18:37
Ellie HannaEllie Hanna
585
bear in mind that this just tests for floats - if you want any number, float or integer, you'd have to change the third line to if isinstance(test, float) or isinstance(test, int):
– Ellie Hanna
Nov 21 '18 at 18:39
okay i will try
– Sai Sumanth
Nov 21 '18 at 18:40
add a comment |
0
This is because iteritems() returns a tuple which is the (index, value).
So you are trying to check for example if (0, 1.07) or (1, 2.08) are of type float, which they aren't of course.
It should work if you change df.feature2.iteritems() to df.feature2.values :)
answered Nov 21 '18 at 18:38
hmajid2301hmajid2301
178
add a comment |
0
You can do something like this:
from pandas import DataFrame as df
columns = ['feature1', 'feature2', 'feature3']
data = [[123, 1.07, 1],
[231, 2.08, 3],
[122, 'ab', 4],
[111, 3.04, 6],
[555, 'cde', 8]]
df_ = df(data, columns=columns)
types =
for k in df_:
a = set(type(m) for m in df_[k])
if len(a) > 1:
types.append({k: 'object'})
else:
types.append({k: str(list(a)[0].__name__)})
print(types)
Output:
[{'feature1': 'int'}, {'feature2': 'object'}, {'feature3': 'int'}]
answered Nov 21 '18 at 19:13
Chiheb NexusChiheb Nexus
5,31631829
add a comment |
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4 Answers
4
active
oldest
votes
4 Answers
4
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
Iteritems is returning a tuple, ((123, '1.07'), 1.07) and since you want to loop over each value try the below code.
You just need to remove .iteritems() and it will work like a charm.
df['feature2']=[1.07,2.08,'ab',3.04,'cde']
for item in df.feature2:
if isinstance(item,float):
print('yes')
else:
print('no')
Here is your output:
yes
yes
no
yes
no
answered Nov 21 '18 at 18:42
Ankur GulatiAnkur Gulati
14510
If it helps, please care to accept and upvote the answer. Thanks :)
– Ankur Gulati
Nov 21 '18 at 18:43
Sorry, it did not work. I'm not sure why
– Sai Sumanth
Nov 21 '18 at 18:58
@SaiSumanth Can you tell me what's the error? I included the data frame creation line that I used for testing and it is working from me. Also, I am using Python3
– Ankur Gulati
Nov 21 '18 at 19:03
Its working now, actually my features values were in 'float string' type instead of float type. Thanks
– Sai Sumanth
Nov 21 '18 at 19:20
No Problem. Please accept the answer.
– Ankur Gulati
Nov 21 '18 at 19:30
add a comment |
1
Iteritems is returning a tuple, ((123, '1.07'), 1.07) and since you want to loop over each value try the below code.
You just need to remove .iteritems() and it will work like a charm.
df['feature2']=[1.07,2.08,'ab',3.04,'cde']
for item in df.feature2:
if isinstance(item,float):
print('yes')
else:
print('no')
Here is your output:
yes
yes
no
yes
no
answered Nov 21 '18 at 18:42
Ankur GulatiAnkur Gulati
14510
If it helps, please care to accept and upvote the answer. Thanks :)
– Ankur Gulati
Nov 21 '18 at 18:43
Sorry, it did not work. I'm not sure why
– Sai Sumanth
Nov 21 '18 at 18:58
@SaiSumanth Can you tell me what's the error? I included the data frame creation line that I used for testing and it is working from me. Also, I am using Python3
– Ankur Gulati
Nov 21 '18 at 19:03
Its working now, actually my features values were in 'float string' type instead of float type. Thanks
– Sai Sumanth
Nov 21 '18 at 19:20
No Problem. Please accept the answer.
– Ankur Gulati
Nov 21 '18 at 19:30
add a comment |
1
1
1
Iteritems is returning a tuple, ((123, '1.07'), 1.07) and since you want to loop over each value try the below code.
You just need to remove .iteritems() and it will work like a charm.
df['feature2']=[1.07,2.08,'ab',3.04,'cde']
for item in df.feature2:
if isinstance(item,float):
print('yes')
else:
print('no')
Here is your output:
yes
yes
no
yes
no
answered Nov 21 '18 at 18:42
Ankur GulatiAnkur Gulati
14510
Iteritems is returning a tuple, ((123, '1.07'), 1.07) and since you want to loop over each value try the below code.
You just need to remove .iteritems() and it will work like a charm.
df['feature2']=[1.07,2.08,'ab',3.04,'cde']
for item in df.feature2:
if isinstance(item,float):
print('yes')
else:
print('no')
Here is your output:
yes
yes
no
yes
no
answered Nov 21 '18 at 18:42
Ankur GulatiAnkur Gulati
14510
edited Nov 21 '18 at 19:01
answered Nov 21 '18 at 18:42
Ankur GulatiAnkur Gulati
14510
answered Nov 21 '18 at 18:42
Ankur GulatiAnkur Gulati
14510
answered Nov 21 '18 at 18:42
Ankur GulatiAnkur Gulati
14510
14510
If it helps, please care to accept and upvote the answer. Thanks :)
– Ankur Gulati
Nov 21 '18 at 18:43
Sorry, it did not work. I'm not sure why
– Sai Sumanth
Nov 21 '18 at 18:58
@SaiSumanth Can you tell me what's the error? I included the data frame creation line that I used for testing and it is working from me. Also, I am using Python3
– Ankur Gulati
Nov 21 '18 at 19:03
Its working now, actually my features values were in 'float string' type instead of float type. Thanks
– Sai Sumanth
Nov 21 '18 at 19:20
No Problem. Please accept the answer.
– Ankur Gulati
Nov 21 '18 at 19:30
add a comment |
If it helps, please care to accept and upvote the answer. Thanks :)
– Ankur Gulati
Nov 21 '18 at 18:43
Sorry, it did not work. I'm not sure why
– Sai Sumanth
Nov 21 '18 at 18:58
@SaiSumanth Can you tell me what's the error? I included the data frame creation line that I used for testing and it is working from me. Also, I am using Python3
– Ankur Gulati
Nov 21 '18 at 19:03
Its working now, actually my features values were in 'float string' type instead of float type. Thanks
– Sai Sumanth
Nov 21 '18 at 19:20
No Problem. Please accept the answer.
– Ankur Gulati
Nov 21 '18 at 19:30
If it helps, please care to accept and upvote the answer. Thanks :)
– Ankur Gulati
Nov 21 '18 at 18:43
If it helps, please care to accept and upvote the answer. Thanks :)
– Ankur Gulati
Nov 21 '18 at 18:43
Sorry, it did not work. I'm not sure why
– Sai Sumanth
Nov 21 '18 at 18:58
Sorry, it did not work. I'm not sure why
– Sai Sumanth
Nov 21 '18 at 18:58
@SaiSumanth Can you tell me what's the error? I included the data frame creation line that I used for testing and it is working from me. Also, I am using Python3
– Ankur Gulati
Nov 21 '18 at 19:03
@SaiSumanth Can you tell me what's the error? I included the data frame creation line that I used for testing and it is working from me. Also, I am using Python3
– Ankur Gulati
Nov 21 '18 at 19:03
Its working now, actually my features values were in 'float string' type instead of float type. Thanks
– Sai Sumanth
Nov 21 '18 at 19:20
Its working now, actually my features values were in 'float string' type instead of float type. Thanks
– Sai Sumanth
Nov 21 '18 at 19:20
No Problem. Please accept the answer.
– Ankur Gulati
Nov 21 '18 at 19:30
No Problem. Please accept the answer.
– Ankur Gulati
Nov 21 '18 at 19:30
add a comment |
0
Try this:
for i in range(len(df["feature2"])):
test = df.loc[i,"feature2"]
if isinstance(test, float):
print('yes')
else:
print('no')
answered Nov 21 '18 at 18:37
Ellie HannaEllie Hanna
585
bear in mind that this just tests for floats - if you want any number, float or integer, you'd have to change the third line to if isinstance(test, float) or isinstance(test, int):
– Ellie Hanna
Nov 21 '18 at 18:39
okay i will try
– Sai Sumanth
Nov 21 '18 at 18:40
add a comment |
0
Try this:
for i in range(len(df["feature2"])):
test = df.loc[i,"feature2"]
if isinstance(test, float):
print('yes')
else:
print('no')
answered Nov 21 '18 at 18:37
Ellie HannaEllie Hanna
585
bear in mind that this just tests for floats - if you want any number, float or integer, you'd have to change the third line to if isinstance(test, float) or isinstance(test, int):
– Ellie Hanna
Nov 21 '18 at 18:39
okay i will try
– Sai Sumanth
Nov 21 '18 at 18:40
add a comment |
0
0
0
Try this:
for i in range(len(df["feature2"])):
test = df.loc[i,"feature2"]
if isinstance(test, float):
print('yes')
else:
print('no')
answered Nov 21 '18 at 18:37
Ellie HannaEllie Hanna
585
Try this:
for i in range(len(df["feature2"])):
test = df.loc[i,"feature2"]
if isinstance(test, float):
print('yes')
else:
print('no')
answered Nov 21 '18 at 18:37
Ellie HannaEllie Hanna
585
answered Nov 21 '18 at 18:37
Ellie HannaEllie Hanna
585
answered Nov 21 '18 at 18:37
Ellie HannaEllie Hanna
585
answered Nov 21 '18 at 18:37
Ellie HannaEllie Hanna
585
585
bear in mind that this just tests for floats - if you want any number, float or integer, you'd have to change the third line to if isinstance(test, float) or isinstance(test, int):
– Ellie Hanna
Nov 21 '18 at 18:39
okay i will try
– Sai Sumanth
Nov 21 '18 at 18:40
add a comment |
bear in mind that this just tests for floats - if you want any number, float or integer, you'd have to change the third line to if isinstance(test, float) or isinstance(test, int):
– Ellie Hanna
Nov 21 '18 at 18:39
okay i will try
– Sai Sumanth
Nov 21 '18 at 18:40
bear in mind that this just tests for floats - if you want any number, float or integer, you'd have to change the third line to if isinstance(test, float) or isinstance(test, int):
– Ellie Hanna
Nov 21 '18 at 18:39
bear in mind that this just tests for floats - if you want any number, float or integer, you'd have to change the third line to if isinstance(test, float) or isinstance(test, int):
– Ellie Hanna
Nov 21 '18 at 18:39
okay i will try
– Sai Sumanth
Nov 21 '18 at 18:40
okay i will try
– Sai Sumanth
Nov 21 '18 at 18:40
add a comment |
0
This is because iteritems() returns a tuple which is the (index, value).
So you are trying to check for example if (0, 1.07) or (1, 2.08) are of type float, which they aren't of course.
It should work if you change df.feature2.iteritems() to df.feature2.values :)
answered Nov 21 '18 at 18:38
hmajid2301hmajid2301
178
add a comment |
0
This is because iteritems() returns a tuple which is the (index, value).
So you are trying to check for example if (0, 1.07) or (1, 2.08) are of type float, which they aren't of course.
It should work if you change df.feature2.iteritems() to df.feature2.values :)
answered Nov 21 '18 at 18:38
hmajid2301hmajid2301
178
add a comment |
0
0
0
This is because iteritems() returns a tuple which is the (index, value).
So you are trying to check for example if (0, 1.07) or (1, 2.08) are of type float, which they aren't of course.
It should work if you change df.feature2.iteritems() to df.feature2.values :)
answered Nov 21 '18 at 18:38
hmajid2301hmajid2301
178
This is because iteritems() returns a tuple which is the (index, value).
So you are trying to check for example if (0, 1.07) or (1, 2.08) are of type float, which they aren't of course.
It should work if you change df.feature2.iteritems() to df.feature2.values :)
answered Nov 21 '18 at 18:38
hmajid2301hmajid2301
178
answered Nov 21 '18 at 18:38
hmajid2301hmajid2301
178
answered Nov 21 '18 at 18:38
hmajid2301hmajid2301
178
answered Nov 21 '18 at 18:38
hmajid2301hmajid2301
178
178
add a comment |
add a comment |
0
You can do something like this:
from pandas import DataFrame as df
columns = ['feature1', 'feature2', 'feature3']
data = [[123, 1.07, 1],
[231, 2.08, 3],
[122, 'ab', 4],
[111, 3.04, 6],
[555, 'cde', 8]]
df_ = df(data, columns=columns)
types =
for k in df_:
a = set(type(m) for m in df_[k])
if len(a) > 1:
types.append({k: 'object'})
else:
types.append({k: str(list(a)[0].__name__)})
print(types)
Output:
[{'feature1': 'int'}, {'feature2': 'object'}, {'feature3': 'int'}]
answered Nov 21 '18 at 19:13
Chiheb NexusChiheb Nexus
5,31631829
add a comment |
0
You can do something like this:
from pandas import DataFrame as df
columns = ['feature1', 'feature2', 'feature3']
data = [[123, 1.07, 1],
[231, 2.08, 3],
[122, 'ab', 4],
[111, 3.04, 6],
[555, 'cde', 8]]
df_ = df(data, columns=columns)
types =
for k in df_:
a = set(type(m) for m in df_[k])
if len(a) > 1:
types.append({k: 'object'})
else:
types.append({k: str(list(a)[0].__name__)})
print(types)
Output:
[{'feature1': 'int'}, {'feature2': 'object'}, {'feature3': 'int'}]
answered Nov 21 '18 at 19:13
Chiheb NexusChiheb Nexus
5,31631829
add a comment |
0
0
0
You can do something like this:
from pandas import DataFrame as df
columns = ['feature1', 'feature2', 'feature3']
data = [[123, 1.07, 1],
[231, 2.08, 3],
[122, 'ab', 4],
[111, 3.04, 6],
[555, 'cde', 8]]
df_ = df(data, columns=columns)
types =
for k in df_:
a = set(type(m) for m in df_[k])
if len(a) > 1:
types.append({k: 'object'})
else:
types.append({k: str(list(a)[0].__name__)})
print(types)
Output:
[{'feature1': 'int'}, {'feature2': 'object'}, {'feature3': 'int'}]
answered Nov 21 '18 at 19:13
Chiheb NexusChiheb Nexus
5,31631829
You can do something like this:
from pandas import DataFrame as df
columns = ['feature1', 'feature2', 'feature3']
data = [[123, 1.07, 1],
[231, 2.08, 3],
[122, 'ab', 4],
[111, 3.04, 6],
[555, 'cde', 8]]
df_ = df(data, columns=columns)
types =
for k in df_:
a = set(type(m) for m in df_[k])
if len(a) > 1:
types.append({k: 'object'})
else:
types.append({k: str(list(a)[0].__name__)})
print(types)
Output:
[{'feature1': 'int'}, {'feature2': 'object'}, {'feature3': 'int'}]
answered Nov 21 '18 at 19:13
Chiheb NexusChiheb Nexus
5,31631829
answered Nov 21 '18 at 19:13
Chiheb NexusChiheb Nexus
5,31631829
answered Nov 21 '18 at 19:13
Chiheb NexusChiheb Nexus
5,31631829
answered Nov 21 '18 at 19:13
Chiheb NexusChiheb Nexus
5,31631829
5,31631829
add a comment |
add a comment |
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