Create new column in pandas df and assign string values conditionally
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}
I'm new to pandas
, trying to create a new column in Pandas Dataframe, and assign a string value based on a function, but the outcome outputs only 1 value ('residential) to all 5,000 columns. Any idea what's wrong with my code? Thank you
def programType(c):
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
return 'Residential'
elif c['Primary Property Type - Self Selected'] == 'Bank Branch' or 'Hotel' or 'Financial Office'
or 'Retail Store' or 'Distribution Center' or 'Non-Refrigerated Warehouse' or 'Fitness Center/Health Club/Gym'
or 'Mixed Use Property' or 'Self-Storage Facility' or 'Wholesale Club/Supercenter' or 'Supermarket/Grocery Store':
return 'Commercial'
elif c['Primary Property Type - Self Selected'] == 'Senior Care Community' or 'K-12 School' or 'College/University'
or 'Worship Facility' or 'Medical Office' or 'Hospital (General Medical & Surgical)':
return 'Institutional'
elif c['Primary Property Type - Self Selected'] == 'Manufacturing/Industrial Plant':
return 'Industrial'
else:
return 'Other'
The new column is called 'Program Type'
datav3['Program Type'] = datav3.apply(programType, axis=1)
python pandas
add a comment |
I'm new to pandas
, trying to create a new column in Pandas Dataframe, and assign a string value based on a function, but the outcome outputs only 1 value ('residential) to all 5,000 columns. Any idea what's wrong with my code? Thank you
def programType(c):
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
return 'Residential'
elif c['Primary Property Type - Self Selected'] == 'Bank Branch' or 'Hotel' or 'Financial Office'
or 'Retail Store' or 'Distribution Center' or 'Non-Refrigerated Warehouse' or 'Fitness Center/Health Club/Gym'
or 'Mixed Use Property' or 'Self-Storage Facility' or 'Wholesale Club/Supercenter' or 'Supermarket/Grocery Store':
return 'Commercial'
elif c['Primary Property Type - Self Selected'] == 'Senior Care Community' or 'K-12 School' or 'College/University'
or 'Worship Facility' or 'Medical Office' or 'Hospital (General Medical & Surgical)':
return 'Institutional'
elif c['Primary Property Type - Self Selected'] == 'Manufacturing/Industrial Plant':
return 'Industrial'
else:
return 'Other'
The new column is called 'Program Type'
datav3['Program Type'] = datav3.apply(programType, axis=1)
python pandas
I am a bit curious - do you need loops (apply) for some reason?
– jezrael
Nov 29 '18 at 6:59
Nope, if there's a better syntax i'm happy to use it. I also just went through your answer, and understood it now. Thank you.
– abigfatcat
Dec 1 '18 at 3:45
add a comment |
I'm new to pandas
, trying to create a new column in Pandas Dataframe, and assign a string value based on a function, but the outcome outputs only 1 value ('residential) to all 5,000 columns. Any idea what's wrong with my code? Thank you
def programType(c):
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
return 'Residential'
elif c['Primary Property Type - Self Selected'] == 'Bank Branch' or 'Hotel' or 'Financial Office'
or 'Retail Store' or 'Distribution Center' or 'Non-Refrigerated Warehouse' or 'Fitness Center/Health Club/Gym'
or 'Mixed Use Property' or 'Self-Storage Facility' or 'Wholesale Club/Supercenter' or 'Supermarket/Grocery Store':
return 'Commercial'
elif c['Primary Property Type - Self Selected'] == 'Senior Care Community' or 'K-12 School' or 'College/University'
or 'Worship Facility' or 'Medical Office' or 'Hospital (General Medical & Surgical)':
return 'Institutional'
elif c['Primary Property Type - Self Selected'] == 'Manufacturing/Industrial Plant':
return 'Industrial'
else:
return 'Other'
The new column is called 'Program Type'
datav3['Program Type'] = datav3.apply(programType, axis=1)
python pandas
I'm new to pandas
, trying to create a new column in Pandas Dataframe, and assign a string value based on a function, but the outcome outputs only 1 value ('residential) to all 5,000 columns. Any idea what's wrong with my code? Thank you
def programType(c):
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
return 'Residential'
elif c['Primary Property Type - Self Selected'] == 'Bank Branch' or 'Hotel' or 'Financial Office'
or 'Retail Store' or 'Distribution Center' or 'Non-Refrigerated Warehouse' or 'Fitness Center/Health Club/Gym'
or 'Mixed Use Property' or 'Self-Storage Facility' or 'Wholesale Club/Supercenter' or 'Supermarket/Grocery Store':
return 'Commercial'
elif c['Primary Property Type - Self Selected'] == 'Senior Care Community' or 'K-12 School' or 'College/University'
or 'Worship Facility' or 'Medical Office' or 'Hospital (General Medical & Surgical)':
return 'Institutional'
elif c['Primary Property Type - Self Selected'] == 'Manufacturing/Industrial Plant':
return 'Industrial'
else:
return 'Other'
The new column is called 'Program Type'
datav3['Program Type'] = datav3.apply(programType, axis=1)
python pandas
python pandas
edited Dec 4 '18 at 12:12
Mayank Porwal
5,0182725
5,0182725
asked Nov 29 '18 at 6:37
abigfatcatabigfatcat
225
225
I am a bit curious - do you need loops (apply) for some reason?
– jezrael
Nov 29 '18 at 6:59
Nope, if there's a better syntax i'm happy to use it. I also just went through your answer, and understood it now. Thank you.
– abigfatcat
Dec 1 '18 at 3:45
add a comment |
I am a bit curious - do you need loops (apply) for some reason?
– jezrael
Nov 29 '18 at 6:59
Nope, if there's a better syntax i'm happy to use it. I also just went through your answer, and understood it now. Thank you.
– abigfatcat
Dec 1 '18 at 3:45
I am a bit curious - do you need loops (apply) for some reason?
– jezrael
Nov 29 '18 at 6:59
I am a bit curious - do you need loops (apply) for some reason?
– jezrael
Nov 29 '18 at 6:59
Nope, if there's a better syntax i'm happy to use it. I also just went through your answer, and understood it now. Thank you.
– abigfatcat
Dec 1 '18 at 3:45
Nope, if there's a better syntax i'm happy to use it. I also just went through your answer, and understood it now. Thank you.
– abigfatcat
Dec 1 '18 at 3:45
add a comment |
2 Answers
2
active
oldest
votes
In pandas is best avoid loops (apply are loops under the hood) if exist vectorized solutions, because loops are slow.
I try rewrite your code - create dictionary with output and list of values, swap keys with values and call map
, last for not matched values add fillna
:
d = {'Residential' :['Multifamily Housing', 'Residence Hall/Dormitory'],
'Commercial' : ['Bank Branch', 'Hotel' , 'Financial Office' , 'Retail Store', 'Distribution Center',
'Non-Refrigerated Warehouse', 'Fitness Center/Health Club/Gym', 'Mixed Use Property',
'Self-Storage Facility', 'Wholesale Club/Supercenter', 'Supermarket/Grocery Store'],
'Institutional':['Senior Care Community', 'K-12 School', 'College/University', 'Worship Facility',
'Medical Office', 'Hospital (General Medical & Surgical)'],
'Industrial': ['Manufacturing/Industrial Plant'] }
d1 = {k: oldk for oldk, oldv in d.items() for k in oldv}
print (d1)
{
'Multifamily Housing': 'Residential',
'Residence Hall/Dormitory': 'Residential',
'Bank Branch': 'Commercial',
'Hotel': 'Commercial',
'Financial Office': 'Commercial',
'Retail Store': 'Commercial',
'Distribution Center': 'Commercial',
'Non-Refrigerated Warehouse': 'Commercial',
'Fitness Center/Health Club/Gym': 'Commercial',
'Mixed Use Property': 'Commercial',
'Self-Storage Facility': 'Commercial',
'Wholesale Club/Supercenter': 'Commercial',
'Supermarket/Grocery Store': 'Commercial',
'Senior Care Community': 'Institutional',
'K-12 School': 'Institutional',
'College/University': 'Institutional',
'Worship Facility': 'Institutional',
'Medical Office': 'Institutional',
'Hospital (General Medical & Surgical)': 'Institutional',
'Manufacturing/Industrial Plant': 'Industrial'
}
datav3 = pd.DataFrame({'Program':['Medical Office','Hotel',
'Residence Hall/Dormitory',
'Manufacturing/Industrial Plant','House']})
datav3['Program Type'] = datav3['Program'].map(d1).fillna('Other')
print (datav3)
Program Program Type
0 Medical Office Institutional
1 Hotel Commercial
2 Residence Hall/Dormitory Residential
3 Manufacturing/Industrial Plant Industrial
4 House Other
Could you please explain a little on this bit if you don't mind, i'm new to this syntax: d1 = {k: oldk for oldk, oldv in d.items() for k in oldv} Thanks!
– abigfatcat
Dec 1 '18 at 6:08
@SchratchieMe You can check this
– jezrael
Dec 1 '18 at 9:47
@SchratchieMe and this
– jezrael
Dec 1 '18 at 9:49
add a comment |
The issue is with your if loops. The way you are comparing after or
is not correct.
Writing or 'Residence Hall/Dormitory'
will always be true
, hence, only the first if
gets evaluated everytime and you get Residential
in all rows.
Instead of this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
Do this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory':
OR
if any([c['Primary Property Type - Self Selected'] == 'Multifamily Housing', c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory']):
Just make the above change, and your code should do what is expected. Hope this is clear.
@ScratchieMe Please consider upvoting the answer too. Thanks
– Mayank Porwal
Nov 29 '18 at 7:12
I did so, thanks very much
– abigfatcat
Dec 1 '18 at 3:46
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
In pandas is best avoid loops (apply are loops under the hood) if exist vectorized solutions, because loops are slow.
I try rewrite your code - create dictionary with output and list of values, swap keys with values and call map
, last for not matched values add fillna
:
d = {'Residential' :['Multifamily Housing', 'Residence Hall/Dormitory'],
'Commercial' : ['Bank Branch', 'Hotel' , 'Financial Office' , 'Retail Store', 'Distribution Center',
'Non-Refrigerated Warehouse', 'Fitness Center/Health Club/Gym', 'Mixed Use Property',
'Self-Storage Facility', 'Wholesale Club/Supercenter', 'Supermarket/Grocery Store'],
'Institutional':['Senior Care Community', 'K-12 School', 'College/University', 'Worship Facility',
'Medical Office', 'Hospital (General Medical & Surgical)'],
'Industrial': ['Manufacturing/Industrial Plant'] }
d1 = {k: oldk for oldk, oldv in d.items() for k in oldv}
print (d1)
{
'Multifamily Housing': 'Residential',
'Residence Hall/Dormitory': 'Residential',
'Bank Branch': 'Commercial',
'Hotel': 'Commercial',
'Financial Office': 'Commercial',
'Retail Store': 'Commercial',
'Distribution Center': 'Commercial',
'Non-Refrigerated Warehouse': 'Commercial',
'Fitness Center/Health Club/Gym': 'Commercial',
'Mixed Use Property': 'Commercial',
'Self-Storage Facility': 'Commercial',
'Wholesale Club/Supercenter': 'Commercial',
'Supermarket/Grocery Store': 'Commercial',
'Senior Care Community': 'Institutional',
'K-12 School': 'Institutional',
'College/University': 'Institutional',
'Worship Facility': 'Institutional',
'Medical Office': 'Institutional',
'Hospital (General Medical & Surgical)': 'Institutional',
'Manufacturing/Industrial Plant': 'Industrial'
}
datav3 = pd.DataFrame({'Program':['Medical Office','Hotel',
'Residence Hall/Dormitory',
'Manufacturing/Industrial Plant','House']})
datav3['Program Type'] = datav3['Program'].map(d1).fillna('Other')
print (datav3)
Program Program Type
0 Medical Office Institutional
1 Hotel Commercial
2 Residence Hall/Dormitory Residential
3 Manufacturing/Industrial Plant Industrial
4 House Other
Could you please explain a little on this bit if you don't mind, i'm new to this syntax: d1 = {k: oldk for oldk, oldv in d.items() for k in oldv} Thanks!
– abigfatcat
Dec 1 '18 at 6:08
@SchratchieMe You can check this
– jezrael
Dec 1 '18 at 9:47
@SchratchieMe and this
– jezrael
Dec 1 '18 at 9:49
add a comment |
In pandas is best avoid loops (apply are loops under the hood) if exist vectorized solutions, because loops are slow.
I try rewrite your code - create dictionary with output and list of values, swap keys with values and call map
, last for not matched values add fillna
:
d = {'Residential' :['Multifamily Housing', 'Residence Hall/Dormitory'],
'Commercial' : ['Bank Branch', 'Hotel' , 'Financial Office' , 'Retail Store', 'Distribution Center',
'Non-Refrigerated Warehouse', 'Fitness Center/Health Club/Gym', 'Mixed Use Property',
'Self-Storage Facility', 'Wholesale Club/Supercenter', 'Supermarket/Grocery Store'],
'Institutional':['Senior Care Community', 'K-12 School', 'College/University', 'Worship Facility',
'Medical Office', 'Hospital (General Medical & Surgical)'],
'Industrial': ['Manufacturing/Industrial Plant'] }
d1 = {k: oldk for oldk, oldv in d.items() for k in oldv}
print (d1)
{
'Multifamily Housing': 'Residential',
'Residence Hall/Dormitory': 'Residential',
'Bank Branch': 'Commercial',
'Hotel': 'Commercial',
'Financial Office': 'Commercial',
'Retail Store': 'Commercial',
'Distribution Center': 'Commercial',
'Non-Refrigerated Warehouse': 'Commercial',
'Fitness Center/Health Club/Gym': 'Commercial',
'Mixed Use Property': 'Commercial',
'Self-Storage Facility': 'Commercial',
'Wholesale Club/Supercenter': 'Commercial',
'Supermarket/Grocery Store': 'Commercial',
'Senior Care Community': 'Institutional',
'K-12 School': 'Institutional',
'College/University': 'Institutional',
'Worship Facility': 'Institutional',
'Medical Office': 'Institutional',
'Hospital (General Medical & Surgical)': 'Institutional',
'Manufacturing/Industrial Plant': 'Industrial'
}
datav3 = pd.DataFrame({'Program':['Medical Office','Hotel',
'Residence Hall/Dormitory',
'Manufacturing/Industrial Plant','House']})
datav3['Program Type'] = datav3['Program'].map(d1).fillna('Other')
print (datav3)
Program Program Type
0 Medical Office Institutional
1 Hotel Commercial
2 Residence Hall/Dormitory Residential
3 Manufacturing/Industrial Plant Industrial
4 House Other
Could you please explain a little on this bit if you don't mind, i'm new to this syntax: d1 = {k: oldk for oldk, oldv in d.items() for k in oldv} Thanks!
– abigfatcat
Dec 1 '18 at 6:08
@SchratchieMe You can check this
– jezrael
Dec 1 '18 at 9:47
@SchratchieMe and this
– jezrael
Dec 1 '18 at 9:49
add a comment |
In pandas is best avoid loops (apply are loops under the hood) if exist vectorized solutions, because loops are slow.
I try rewrite your code - create dictionary with output and list of values, swap keys with values and call map
, last for not matched values add fillna
:
d = {'Residential' :['Multifamily Housing', 'Residence Hall/Dormitory'],
'Commercial' : ['Bank Branch', 'Hotel' , 'Financial Office' , 'Retail Store', 'Distribution Center',
'Non-Refrigerated Warehouse', 'Fitness Center/Health Club/Gym', 'Mixed Use Property',
'Self-Storage Facility', 'Wholesale Club/Supercenter', 'Supermarket/Grocery Store'],
'Institutional':['Senior Care Community', 'K-12 School', 'College/University', 'Worship Facility',
'Medical Office', 'Hospital (General Medical & Surgical)'],
'Industrial': ['Manufacturing/Industrial Plant'] }
d1 = {k: oldk for oldk, oldv in d.items() for k in oldv}
print (d1)
{
'Multifamily Housing': 'Residential',
'Residence Hall/Dormitory': 'Residential',
'Bank Branch': 'Commercial',
'Hotel': 'Commercial',
'Financial Office': 'Commercial',
'Retail Store': 'Commercial',
'Distribution Center': 'Commercial',
'Non-Refrigerated Warehouse': 'Commercial',
'Fitness Center/Health Club/Gym': 'Commercial',
'Mixed Use Property': 'Commercial',
'Self-Storage Facility': 'Commercial',
'Wholesale Club/Supercenter': 'Commercial',
'Supermarket/Grocery Store': 'Commercial',
'Senior Care Community': 'Institutional',
'K-12 School': 'Institutional',
'College/University': 'Institutional',
'Worship Facility': 'Institutional',
'Medical Office': 'Institutional',
'Hospital (General Medical & Surgical)': 'Institutional',
'Manufacturing/Industrial Plant': 'Industrial'
}
datav3 = pd.DataFrame({'Program':['Medical Office','Hotel',
'Residence Hall/Dormitory',
'Manufacturing/Industrial Plant','House']})
datav3['Program Type'] = datav3['Program'].map(d1).fillna('Other')
print (datav3)
Program Program Type
0 Medical Office Institutional
1 Hotel Commercial
2 Residence Hall/Dormitory Residential
3 Manufacturing/Industrial Plant Industrial
4 House Other
In pandas is best avoid loops (apply are loops under the hood) if exist vectorized solutions, because loops are slow.
I try rewrite your code - create dictionary with output and list of values, swap keys with values and call map
, last for not matched values add fillna
:
d = {'Residential' :['Multifamily Housing', 'Residence Hall/Dormitory'],
'Commercial' : ['Bank Branch', 'Hotel' , 'Financial Office' , 'Retail Store', 'Distribution Center',
'Non-Refrigerated Warehouse', 'Fitness Center/Health Club/Gym', 'Mixed Use Property',
'Self-Storage Facility', 'Wholesale Club/Supercenter', 'Supermarket/Grocery Store'],
'Institutional':['Senior Care Community', 'K-12 School', 'College/University', 'Worship Facility',
'Medical Office', 'Hospital (General Medical & Surgical)'],
'Industrial': ['Manufacturing/Industrial Plant'] }
d1 = {k: oldk for oldk, oldv in d.items() for k in oldv}
print (d1)
{
'Multifamily Housing': 'Residential',
'Residence Hall/Dormitory': 'Residential',
'Bank Branch': 'Commercial',
'Hotel': 'Commercial',
'Financial Office': 'Commercial',
'Retail Store': 'Commercial',
'Distribution Center': 'Commercial',
'Non-Refrigerated Warehouse': 'Commercial',
'Fitness Center/Health Club/Gym': 'Commercial',
'Mixed Use Property': 'Commercial',
'Self-Storage Facility': 'Commercial',
'Wholesale Club/Supercenter': 'Commercial',
'Supermarket/Grocery Store': 'Commercial',
'Senior Care Community': 'Institutional',
'K-12 School': 'Institutional',
'College/University': 'Institutional',
'Worship Facility': 'Institutional',
'Medical Office': 'Institutional',
'Hospital (General Medical & Surgical)': 'Institutional',
'Manufacturing/Industrial Plant': 'Industrial'
}
datav3 = pd.DataFrame({'Program':['Medical Office','Hotel',
'Residence Hall/Dormitory',
'Manufacturing/Industrial Plant','House']})
datav3['Program Type'] = datav3['Program'].map(d1).fillna('Other')
print (datav3)
Program Program Type
0 Medical Office Institutional
1 Hotel Commercial
2 Residence Hall/Dormitory Residential
3 Manufacturing/Industrial Plant Industrial
4 House Other
edited Nov 29 '18 at 6:53
answered Nov 29 '18 at 6:42
jezraeljezrael
357k26321397
357k26321397
Could you please explain a little on this bit if you don't mind, i'm new to this syntax: d1 = {k: oldk for oldk, oldv in d.items() for k in oldv} Thanks!
– abigfatcat
Dec 1 '18 at 6:08
@SchratchieMe You can check this
– jezrael
Dec 1 '18 at 9:47
@SchratchieMe and this
– jezrael
Dec 1 '18 at 9:49
add a comment |
Could you please explain a little on this bit if you don't mind, i'm new to this syntax: d1 = {k: oldk for oldk, oldv in d.items() for k in oldv} Thanks!
– abigfatcat
Dec 1 '18 at 6:08
@SchratchieMe You can check this
– jezrael
Dec 1 '18 at 9:47
@SchratchieMe and this
– jezrael
Dec 1 '18 at 9:49
Could you please explain a little on this bit if you don't mind, i'm new to this syntax: d1 = {k: oldk for oldk, oldv in d.items() for k in oldv} Thanks!
– abigfatcat
Dec 1 '18 at 6:08
Could you please explain a little on this bit if you don't mind, i'm new to this syntax: d1 = {k: oldk for oldk, oldv in d.items() for k in oldv} Thanks!
– abigfatcat
Dec 1 '18 at 6:08
@SchratchieMe You can check this
– jezrael
Dec 1 '18 at 9:47
@SchratchieMe You can check this
– jezrael
Dec 1 '18 at 9:47
@SchratchieMe and this
– jezrael
Dec 1 '18 at 9:49
@SchratchieMe and this
– jezrael
Dec 1 '18 at 9:49
add a comment |
The issue is with your if loops. The way you are comparing after or
is not correct.
Writing or 'Residence Hall/Dormitory'
will always be true
, hence, only the first if
gets evaluated everytime and you get Residential
in all rows.
Instead of this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
Do this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory':
OR
if any([c['Primary Property Type - Self Selected'] == 'Multifamily Housing', c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory']):
Just make the above change, and your code should do what is expected. Hope this is clear.
@ScratchieMe Please consider upvoting the answer too. Thanks
– Mayank Porwal
Nov 29 '18 at 7:12
I did so, thanks very much
– abigfatcat
Dec 1 '18 at 3:46
add a comment |
The issue is with your if loops. The way you are comparing after or
is not correct.
Writing or 'Residence Hall/Dormitory'
will always be true
, hence, only the first if
gets evaluated everytime and you get Residential
in all rows.
Instead of this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
Do this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory':
OR
if any([c['Primary Property Type - Self Selected'] == 'Multifamily Housing', c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory']):
Just make the above change, and your code should do what is expected. Hope this is clear.
@ScratchieMe Please consider upvoting the answer too. Thanks
– Mayank Porwal
Nov 29 '18 at 7:12
I did so, thanks very much
– abigfatcat
Dec 1 '18 at 3:46
add a comment |
The issue is with your if loops. The way you are comparing after or
is not correct.
Writing or 'Residence Hall/Dormitory'
will always be true
, hence, only the first if
gets evaluated everytime and you get Residential
in all rows.
Instead of this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
Do this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory':
OR
if any([c['Primary Property Type - Self Selected'] == 'Multifamily Housing', c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory']):
Just make the above change, and your code should do what is expected. Hope this is clear.
The issue is with your if loops. The way you are comparing after or
is not correct.
Writing or 'Residence Hall/Dormitory'
will always be true
, hence, only the first if
gets evaluated everytime and you get Residential
in all rows.
Instead of this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or 'Residence Hall/Dormitory':
Do this:
if c['Primary Property Type - Self Selected'] == 'Multifamily Housing' or c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory':
OR
if any([c['Primary Property Type - Self Selected'] == 'Multifamily Housing', c['Primary Property Type - Self Selected'] == 'Residence Hall/Dormitory']):
Just make the above change, and your code should do what is expected. Hope this is clear.
edited Nov 29 '18 at 6:52
answered Nov 29 '18 at 6:42
Mayank PorwalMayank Porwal
5,0182725
5,0182725
@ScratchieMe Please consider upvoting the answer too. Thanks
– Mayank Porwal
Nov 29 '18 at 7:12
I did so, thanks very much
– abigfatcat
Dec 1 '18 at 3:46
add a comment |
@ScratchieMe Please consider upvoting the answer too. Thanks
– Mayank Porwal
Nov 29 '18 at 7:12
I did so, thanks very much
– abigfatcat
Dec 1 '18 at 3:46
@ScratchieMe Please consider upvoting the answer too. Thanks
– Mayank Porwal
Nov 29 '18 at 7:12
@ScratchieMe Please consider upvoting the answer too. Thanks
– Mayank Porwal
Nov 29 '18 at 7:12
I did so, thanks very much
– abigfatcat
Dec 1 '18 at 3:46
I did so, thanks very much
– abigfatcat
Dec 1 '18 at 3:46
add a comment |
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I am a bit curious - do you need loops (apply) for some reason?
– jezrael
Nov 29 '18 at 6:59
Nope, if there's a better syntax i'm happy to use it. I also just went through your answer, and understood it now. Thank you.
– abigfatcat
Dec 1 '18 at 3:45