Pandas.read_excel: Blanks in string columns convert to floats, converting via str() produces string 'Nan'
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In importing an excel file via read_excel, string columns containing blanks are read in as float. When I force them back to strings via str(), the blanks become the string 'Nan', such that when I specify df[df.column=='Nan'], the values are returned.
How can I revise my code to ensure that blanks within a column do not force the entire column to float, and that blanks in a string column are read in as ''?
python pandas nan
asked Dec 28 '18 at 3:14
UBHDNNX
53
|
show 1 more comment
In importing an excel file via read_excel, string columns containing blanks are read in as float. When I force them back to strings via str(), the blanks become the string 'Nan', such that when I specify df[df.column=='Nan'], the values are returned.
How can I revise my code to ensure that blanks within a column do not force the entire column to float, and that blanks in a string column are read in as ''?
python pandas nan
asked Dec 28 '18 at 3:14
UBHDNNX
53
you can replace theNanwith''
– meW
Dec 28 '18 at 3:16
but what if the string could actually be Nan? Example: last name column; last name is Nan.
– UBHDNNX
Dec 28 '18 at 3:18
provide a sample data in your question
– meW
Dec 28 '18 at 3:24
1
Try:df = pd.read_excel(...).fillna('')
– James
Dec 28 '18 at 3:27
@James that worked perfectly. Push it to an answer and I'll mark it correct.
– UBHDNNX
Dec 28 '18 at 3:39
|
show 1 more comment
In importing an excel file via read_excel, string columns containing blanks are read in as float. When I force them back to strings via str(), the blanks become the string 'Nan', such that when I specify df[df.column=='Nan'], the values are returned.
How can I revise my code to ensure that blanks within a column do not force the entire column to float, and that blanks in a string column are read in as ''?
python pandas nan
asked Dec 28 '18 at 3:14
UBHDNNX
53
In importing an excel file via read_excel, string columns containing blanks are read in as float. When I force them back to strings via str(), the blanks become the string 'Nan', such that when I specify df[df.column=='Nan'], the values are returned.
How can I revise my code to ensure that blanks within a column do not force the entire column to float, and that blanks in a string column are read in as ''?
python pandas nan
python pandas nan
asked Dec 28 '18 at 3:14
UBHDNNX
53
asked Dec 28 '18 at 3:14
UBHDNNX
53
asked Dec 28 '18 at 3:14
UBHDNNX
53
asked Dec 28 '18 at 3:14
UBHDNNX
53
asked Dec 28 '18 at 3:14
UBHDNNX
53
53
you can replace theNanwith''
– meW
Dec 28 '18 at 3:16
but what if the string could actually be Nan? Example: last name column; last name is Nan.
– UBHDNNX
Dec 28 '18 at 3:18
provide a sample data in your question
– meW
Dec 28 '18 at 3:24
1
Try:df = pd.read_excel(...).fillna('')
– James
Dec 28 '18 at 3:27
@James that worked perfectly. Push it to an answer and I'll mark it correct.
– UBHDNNX
Dec 28 '18 at 3:39
|
show 1 more comment
you can replace theNanwith''
– meW
Dec 28 '18 at 3:16
but what if the string could actually be Nan? Example: last name column; last name is Nan.
– UBHDNNX
Dec 28 '18 at 3:18
provide a sample data in your question
– meW
Dec 28 '18 at 3:24
1
Try:df = pd.read_excel(...).fillna('')
– James
Dec 28 '18 at 3:27
@James that worked perfectly. Push it to an answer and I'll mark it correct.
– UBHDNNX
Dec 28 '18 at 3:39
you can replace the
Nan with ''– meW
Dec 28 '18 at 3:16
you can replace the
Nan with ''– meW
Dec 28 '18 at 3:16
but what if the string could actually be Nan? Example: last name column; last name is Nan.
– UBHDNNX
Dec 28 '18 at 3:18
but what if the string could actually be Nan? Example: last name column; last name is Nan.
– UBHDNNX
Dec 28 '18 at 3:18
provide a sample data in your question
– meW
Dec 28 '18 at 3:24
provide a sample data in your question
– meW
Dec 28 '18 at 3:24
1
1
Try:
df = pd.read_excel(...).fillna('')– James
Dec 28 '18 at 3:27
Try:
df = pd.read_excel(...).fillna('')– James
Dec 28 '18 at 3:27
@James that worked perfectly. Push it to an answer and I'll mark it correct.
– UBHDNNX
Dec 28 '18 at 3:39
@James that worked perfectly. Push it to an answer and I'll mark it correct.
– UBHDNNX
Dec 28 '18 at 3:39
|
show 1 more comment
2 Answers
2
active
oldest
votes
Try filling NA values on read:
df = pd.read_excel(...).fillna('')
answered Dec 28 '18 at 21:43
James
13.1k11532
add a comment |
You don't actually have to convert to string. You can actually do a:
df[df.colname!=df.colname] #Returns True if it encounters a NaN
answered Dec 28 '18 at 3:50
ycx
1,13616
add a comment |
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2 Answers
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active
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2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
Try filling NA values on read:
df = pd.read_excel(...).fillna('')
answered Dec 28 '18 at 21:43
James
13.1k11532
add a comment |
Try filling NA values on read:
df = pd.read_excel(...).fillna('')
answered Dec 28 '18 at 21:43
James
13.1k11532
add a comment |
Try filling NA values on read:
df = pd.read_excel(...).fillna('')
answered Dec 28 '18 at 21:43
James
13.1k11532
Try filling NA values on read:
df = pd.read_excel(...).fillna('')
answered Dec 28 '18 at 21:43
James
13.1k11532
answered Dec 28 '18 at 21:43
James
13.1k11532
answered Dec 28 '18 at 21:43
James
13.1k11532
answered Dec 28 '18 at 21:43
James
13.1k11532
13.1k11532
add a comment |
add a comment |
You don't actually have to convert to string. You can actually do a:
df[df.colname!=df.colname] #Returns True if it encounters a NaN
answered Dec 28 '18 at 3:50
ycx
1,13616
add a comment |
You don't actually have to convert to string. You can actually do a:
df[df.colname!=df.colname] #Returns True if it encounters a NaN
answered Dec 28 '18 at 3:50
ycx
1,13616
add a comment |
You don't actually have to convert to string. You can actually do a:
df[df.colname!=df.colname] #Returns True if it encounters a NaN
answered Dec 28 '18 at 3:50
ycx
1,13616
You don't actually have to convert to string. You can actually do a:
df[df.colname!=df.colname] #Returns True if it encounters a NaN
answered Dec 28 '18 at 3:50
ycx
1,13616
answered Dec 28 '18 at 3:50
ycx
1,13616
answered Dec 28 '18 at 3:50
ycx
1,13616
answered Dec 28 '18 at 3:50
ycx
1,13616
1,13616
add a comment |
add a comment |
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you can replace the
Nanwith''– meW
Dec 28 '18 at 3:16
but what if the string could actually be Nan? Example: last name column; last name is Nan.
– UBHDNNX
Dec 28 '18 at 3:18
provide a sample data in your question
– meW
Dec 28 '18 at 3:24
1
Try:
df = pd.read_excel(...).fillna('')– James
Dec 28 '18 at 3:27
@James that worked perfectly. Push it to an answer and I'll mark it correct.
– UBHDNNX
Dec 28 '18 at 3:39