Cannot compare types 'ndarray(dtype=int64)' and 'str'
Example of data that I want to replace
Data has following attributes
Buying v-high,high,med,low
Maint v-high,high,med,low
Doors 2,3,4,5-more
persons 2,4-more
lug_boot small,med,big
safety low,med.high
here is what I did
enter code here
#Buying price generalization
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
df["Buying_Price"]=df["Buying_Price"].replace({"high":3})
df["Buying_Price"]=df["Buying_Price"].replace({"med":2})
df["Buying_Price"]=df["Buying_Price"].replace({"low":1})
#Maintanace generalization
df["Maintanance_price"]=df["Maintanance_price"].replace({"vhigh":4})
df["Maintanance_price"]=df["Maintanance_price"].replace({"high":3})
df["Maintanance_price"]=df["Maintanance_price"].replace({"med":2})
df["Maintanance_price"]=df["Maintanance_price"].replace({"low":1})
#lug_boot generalization
df["Lug_boot"]=df["Lug_boot"].replace({"small":1})
df["Lug_boot"]=df["Lug_boot"].replace({"med":2})
df["Lug_boot"]=df["Lug_boot"].replace({"big":3})
#Safety Generalization
df["Safety"]=df["Safety"].replace({"low":1})
df["Safety"]=df["Safety"].replace({"med":2})
df["Safety"]=df["Safety"].replace({"big":3})
print(df.head())
while printing it showed "Cannot compare types 'ndarray(dtype=int64)' and 'str'"
python numpy
asked Nov 26 '18 at 10:15
MiteshMitesh
5151515
add a comment |
Example of data that I want to replace
Data has following attributes
Buying v-high,high,med,low
Maint v-high,high,med,low
Doors 2,3,4,5-more
persons 2,4-more
lug_boot small,med,big
safety low,med.high
here is what I did
enter code here
#Buying price generalization
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
df["Buying_Price"]=df["Buying_Price"].replace({"high":3})
df["Buying_Price"]=df["Buying_Price"].replace({"med":2})
df["Buying_Price"]=df["Buying_Price"].replace({"low":1})
#Maintanace generalization
df["Maintanance_price"]=df["Maintanance_price"].replace({"vhigh":4})
df["Maintanance_price"]=df["Maintanance_price"].replace({"high":3})
df["Maintanance_price"]=df["Maintanance_price"].replace({"med":2})
df["Maintanance_price"]=df["Maintanance_price"].replace({"low":1})
#lug_boot generalization
df["Lug_boot"]=df["Lug_boot"].replace({"small":1})
df["Lug_boot"]=df["Lug_boot"].replace({"med":2})
df["Lug_boot"]=df["Lug_boot"].replace({"big":3})
#Safety Generalization
df["Safety"]=df["Safety"].replace({"low":1})
df["Safety"]=df["Safety"].replace({"med":2})
df["Safety"]=df["Safety"].replace({"big":3})
print(df.head())
while printing it showed "Cannot compare types 'ndarray(dtype=int64)' and 'str'"
python numpy
asked Nov 26 '18 at 10:15
MiteshMitesh
5151515
df.headdoesn't do any computations on your data. Are you sure your error isn't some other line? Please provide full traceback.
– jpp
Nov 26 '18 at 10:19
Echo jpp's comment. Also you can considerably tidy your code by doing your replaces all at once using a dictionary:replace_all_these = {'low' : 1, 'med' : 2, 'high' : 3, 'vhigh' : 4 }; df['col'] = df['col'].replace(replace_all_these)
– T Burgis
Nov 26 '18 at 10:22
add a comment |
Example of data that I want to replace
Data has following attributes
Buying v-high,high,med,low
Maint v-high,high,med,low
Doors 2,3,4,5-more
persons 2,4-more
lug_boot small,med,big
safety low,med.high
here is what I did
enter code here
#Buying price generalization
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
df["Buying_Price"]=df["Buying_Price"].replace({"high":3})
df["Buying_Price"]=df["Buying_Price"].replace({"med":2})
df["Buying_Price"]=df["Buying_Price"].replace({"low":1})
#Maintanace generalization
df["Maintanance_price"]=df["Maintanance_price"].replace({"vhigh":4})
df["Maintanance_price"]=df["Maintanance_price"].replace({"high":3})
df["Maintanance_price"]=df["Maintanance_price"].replace({"med":2})
df["Maintanance_price"]=df["Maintanance_price"].replace({"low":1})
#lug_boot generalization
df["Lug_boot"]=df["Lug_boot"].replace({"small":1})
df["Lug_boot"]=df["Lug_boot"].replace({"med":2})
df["Lug_boot"]=df["Lug_boot"].replace({"big":3})
#Safety Generalization
df["Safety"]=df["Safety"].replace({"low":1})
df["Safety"]=df["Safety"].replace({"med":2})
df["Safety"]=df["Safety"].replace({"big":3})
print(df.head())
while printing it showed "Cannot compare types 'ndarray(dtype=int64)' and 'str'"
python numpy
asked Nov 26 '18 at 10:15
MiteshMitesh
5151515
Example of data that I want to replace
Data has following attributes
Buying v-high,high,med,low
Maint v-high,high,med,low
Doors 2,3,4,5-more
persons 2,4-more
lug_boot small,med,big
safety low,med.high
here is what I did
enter code here
#Buying price generalization
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
df["Buying_Price"]=df["Buying_Price"].replace({"high":3})
df["Buying_Price"]=df["Buying_Price"].replace({"med":2})
df["Buying_Price"]=df["Buying_Price"].replace({"low":1})
#Maintanace generalization
df["Maintanance_price"]=df["Maintanance_price"].replace({"vhigh":4})
df["Maintanance_price"]=df["Maintanance_price"].replace({"high":3})
df["Maintanance_price"]=df["Maintanance_price"].replace({"med":2})
df["Maintanance_price"]=df["Maintanance_price"].replace({"low":1})
#lug_boot generalization
df["Lug_boot"]=df["Lug_boot"].replace({"small":1})
df["Lug_boot"]=df["Lug_boot"].replace({"med":2})
df["Lug_boot"]=df["Lug_boot"].replace({"big":3})
#Safety Generalization
df["Safety"]=df["Safety"].replace({"low":1})
df["Safety"]=df["Safety"].replace({"med":2})
df["Safety"]=df["Safety"].replace({"big":3})
print(df.head())
while printing it showed "Cannot compare types 'ndarray(dtype=int64)' and 'str'"
python numpy
python numpy
asked Nov 26 '18 at 10:15
MiteshMitesh
5151515
asked Nov 26 '18 at 10:15
MiteshMitesh
5151515
asked Nov 26 '18 at 10:15
MiteshMitesh
5151515
asked Nov 26 '18 at 10:15
MiteshMitesh
5151515
asked Nov 26 '18 at 10:15
MiteshMitesh
5151515
5151515
df.headdoesn't do any computations on your data. Are you sure your error isn't some other line? Please provide full traceback.
– jpp
Nov 26 '18 at 10:19
Echo jpp's comment. Also you can considerably tidy your code by doing your replaces all at once using a dictionary:replace_all_these = {'low' : 1, 'med' : 2, 'high' : 3, 'vhigh' : 4 }; df['col'] = df['col'].replace(replace_all_these)
– T Burgis
Nov 26 '18 at 10:22
add a comment |
df.headdoesn't do any computations on your data. Are you sure your error isn't some other line? Please provide full traceback.
– jpp
Nov 26 '18 at 10:19
Echo jpp's comment. Also you can considerably tidy your code by doing your replaces all at once using a dictionary:replace_all_these = {'low' : 1, 'med' : 2, 'high' : 3, 'vhigh' : 4 }; df['col'] = df['col'].replace(replace_all_these)
– T Burgis
Nov 26 '18 at 10:22
df.head doesn't do any computations on your data. Are you sure your error isn't some other line? Please provide full traceback.– jpp
Nov 26 '18 at 10:19
df.head doesn't do any computations on your data. Are you sure your error isn't some other line? Please provide full traceback.– jpp
Nov 26 '18 at 10:19
Echo jpp's comment. Also you can considerably tidy your code by doing your replaces all at once using a dictionary:
replace_all_these = {'low' : 1, 'med' : 2, 'high' : 3, 'vhigh' : 4 }; df['col'] = df['col'].replace(replace_all_these)– T Burgis
Nov 26 '18 at 10:22
Echo jpp's comment. Also you can considerably tidy your code by doing your replaces all at once using a dictionary:
replace_all_these = {'low' : 1, 'med' : 2, 'high' : 3, 'vhigh' : 4 }; df['col'] = df['col'].replace(replace_all_these)– T Burgis
Nov 26 '18 at 10:22
add a comment |
1 Answer
1
active
oldest
votes
Some of you string you passed to replace with an (int)value, actually is an ndarray of int64 values.
You only have int64( here actually ndarray(dtype=int64)) type data in this column.
See document pandas.Dataframe.replace().
replace() try to seek and compare them with the str values you passed.
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
find all "vhigh" value and compare with the value currently contains, the replace it with 4.
At the comparing it fails as try to compare str data with int64 ('ndarray(dtype=int64)')
A brief example to simulate this:
import pandas as pd
import numpy as np
a = np.array([1])
df = pd.DataFrame({"Maintanance_price": a})
df["Maintanance_price"] = df["Maintanance_price"].replace({"a":1})
print(df)
Out:
TypeError: Cannot compare types 'ndarray(dtype=int64)' and 'str'
answered Nov 26 '18 at 10:32
GeeocodeGeeocode
2,41011021
found my problem, my code works fine and Thanks for the brief explanation .. The dataset has a space after 'Safety ' that was causing the problem
– Mitesh
Nov 26 '18 at 23:29
@Mitesh you're welcome and happy to your success.
– Geeocode
Nov 26 '18 at 23:58
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
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oldest
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active
oldest
votes
Some of you string you passed to replace with an (int)value, actually is an ndarray of int64 values.
You only have int64( here actually ndarray(dtype=int64)) type data in this column.
See document pandas.Dataframe.replace().
replace() try to seek and compare them with the str values you passed.
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
find all "vhigh" value and compare with the value currently contains, the replace it with 4.
At the comparing it fails as try to compare str data with int64 ('ndarray(dtype=int64)')
A brief example to simulate this:
import pandas as pd
import numpy as np
a = np.array([1])
df = pd.DataFrame({"Maintanance_price": a})
df["Maintanance_price"] = df["Maintanance_price"].replace({"a":1})
print(df)
Out:
TypeError: Cannot compare types 'ndarray(dtype=int64)' and 'str'
answered Nov 26 '18 at 10:32
GeeocodeGeeocode
2,41011021
found my problem, my code works fine and Thanks for the brief explanation .. The dataset has a space after 'Safety ' that was causing the problem
– Mitesh
Nov 26 '18 at 23:29
@Mitesh you're welcome and happy to your success.
– Geeocode
Nov 26 '18 at 23:58
add a comment |
Some of you string you passed to replace with an (int)value, actually is an ndarray of int64 values.
You only have int64( here actually ndarray(dtype=int64)) type data in this column.
See document pandas.Dataframe.replace().
replace() try to seek and compare them with the str values you passed.
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
find all "vhigh" value and compare with the value currently contains, the replace it with 4.
At the comparing it fails as try to compare str data with int64 ('ndarray(dtype=int64)')
A brief example to simulate this:
import pandas as pd
import numpy as np
a = np.array([1])
df = pd.DataFrame({"Maintanance_price": a})
df["Maintanance_price"] = df["Maintanance_price"].replace({"a":1})
print(df)
Out:
TypeError: Cannot compare types 'ndarray(dtype=int64)' and 'str'
answered Nov 26 '18 at 10:32
GeeocodeGeeocode
2,41011021
found my problem, my code works fine and Thanks for the brief explanation .. The dataset has a space after 'Safety ' that was causing the problem
– Mitesh
Nov 26 '18 at 23:29
@Mitesh you're welcome and happy to your success.
– Geeocode
Nov 26 '18 at 23:58
add a comment |
Some of you string you passed to replace with an (int)value, actually is an ndarray of int64 values.
You only have int64( here actually ndarray(dtype=int64)) type data in this column.
See document pandas.Dataframe.replace().
replace() try to seek and compare them with the str values you passed.
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
find all "vhigh" value and compare with the value currently contains, the replace it with 4.
At the comparing it fails as try to compare str data with int64 ('ndarray(dtype=int64)')
A brief example to simulate this:
import pandas as pd
import numpy as np
a = np.array([1])
df = pd.DataFrame({"Maintanance_price": a})
df["Maintanance_price"] = df["Maintanance_price"].replace({"a":1})
print(df)
Out:
TypeError: Cannot compare types 'ndarray(dtype=int64)' and 'str'
answered Nov 26 '18 at 10:32
GeeocodeGeeocode
2,41011021
Some of you string you passed to replace with an (int)value, actually is an ndarray of int64 values.
You only have int64( here actually ndarray(dtype=int64)) type data in this column.
See document pandas.Dataframe.replace().
replace() try to seek and compare them with the str values you passed.
df["Buying_Price"]=df["Buying_Price"].replace({"vhigh":4})
find all "vhigh" value and compare with the value currently contains, the replace it with 4.
At the comparing it fails as try to compare str data with int64 ('ndarray(dtype=int64)')
A brief example to simulate this:
import pandas as pd
import numpy as np
a = np.array([1])
df = pd.DataFrame({"Maintanance_price": a})
df["Maintanance_price"] = df["Maintanance_price"].replace({"a":1})
print(df)
Out:
TypeError: Cannot compare types 'ndarray(dtype=int64)' and 'str'
answered Nov 26 '18 at 10:32
GeeocodeGeeocode
2,41011021
edited Nov 26 '18 at 10:49
answered Nov 26 '18 at 10:32
GeeocodeGeeocode
2,41011021
answered Nov 26 '18 at 10:32
GeeocodeGeeocode
2,41011021
answered Nov 26 '18 at 10:32
GeeocodeGeeocode
2,41011021
2,41011021
found my problem, my code works fine and Thanks for the brief explanation .. The dataset has a space after 'Safety ' that was causing the problem
– Mitesh
Nov 26 '18 at 23:29
@Mitesh you're welcome and happy to your success.
– Geeocode
Nov 26 '18 at 23:58
add a comment |
found my problem, my code works fine and Thanks for the brief explanation .. The dataset has a space after 'Safety ' that was causing the problem
– Mitesh
Nov 26 '18 at 23:29
@Mitesh you're welcome and happy to your success.
– Geeocode
Nov 26 '18 at 23:58
found my problem, my code works fine and Thanks for the brief explanation .. The dataset has a space after 'Safety ' that was causing the problem
– Mitesh
Nov 26 '18 at 23:29
found my problem, my code works fine and Thanks for the brief explanation .. The dataset has a space after 'Safety ' that was causing the problem
– Mitesh
Nov 26 '18 at 23:29
@Mitesh you're welcome and happy to your success.
– Geeocode
Nov 26 '18 at 23:58
@Mitesh you're welcome and happy to your success.
– Geeocode
Nov 26 '18 at 23:58
add a comment |
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df.headdoesn't do any computations on your data. Are you sure your error isn't some other line? Please provide full traceback.– jpp
Nov 26 '18 at 10:19
Echo jpp's comment. Also you can considerably tidy your code by doing your replaces all at once using a dictionary:
replace_all_these = {'low' : 1, 'med' : 2, 'high' : 3, 'vhigh' : 4 }; df['col'] = df['col'].replace(replace_all_these)– T Burgis
Nov 26 '18 at 10:22