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Pandas: How to sum a variable by group?
The Next CEO of Stack OverflowPandas group-by and sumHow to merge two dictionaries in a single expression?How do I check if a list is empty?How do I check whether a file exists without exceptions?Using global variables in a functionHow do I pass a variable by reference?How do I list all files of a directory?Renaming columns in pandas“Large data” work flows using pandasHow to iterate over rows in a DataFrame in Pandas?Why is “1000000000000000 in range(1000000000000001)” so fast in Python 3?
I would like to sum multiple values to one in python.
See the picture below of my data. I want to sum all the values of AGE for each year for each country.
Instead of having this:
country TIME AGE Value
A 2017 20-60 200
A 2017 60-80 100
A 2016 20-60 200
A 2016 60-80 200
B 2017 20-60 300
B 2017 60-80 300
B 2016 20-60 400
B 2016 60-80 400
I would like to have this:
country TIME Value
A 2017 300
A 2016 400
B 2017 600
B 2016 800
The types of data:
df4types
AGE object
Value object
dtype: object
The data has a multi index by country and TIME.
If have tried this:
df=df.groupby(by=["TIME","GEO"])['Value'].sum()
and this:
df=df.groupby(by=["TIME","GEO"]).sum()['Value']
Both "worked" but result in an enormous value. Like it doesn't sum but paste the numbers behind each other. I have tried to change the variable type to numeric by using:
by df.Value.astype(float) & df.Value.astype(int)
Unfortunately this didn't solve the problem. Does someone have an idea how to sum the values by group and time correctly? I have also uploaded a picture of the real dataset.
python pandas pandas-groupby
edited Mar 21 at 20:13
petezurich
3,76581936
asked Mar 21 at 19:59
PatPat
82
add a comment |
I would like to sum multiple values to one in python.
See the picture below of my data. I want to sum all the values of AGE for each year for each country.
Instead of having this:
country TIME AGE Value
A 2017 20-60 200
A 2017 60-80 100
A 2016 20-60 200
A 2016 60-80 200
B 2017 20-60 300
B 2017 60-80 300
B 2016 20-60 400
B 2016 60-80 400
I would like to have this:
country TIME Value
A 2017 300
A 2016 400
B 2017 600
B 2016 800
The types of data:
df4types
AGE object
Value object
dtype: object
The data has a multi index by country and TIME.
If have tried this:
df=df.groupby(by=["TIME","GEO"])['Value'].sum()
and this:
df=df.groupby(by=["TIME","GEO"]).sum()['Value']
Both "worked" but result in an enormous value. Like it doesn't sum but paste the numbers behind each other. I have tried to change the variable type to numeric by using:
by df.Value.astype(float) & df.Value.astype(int)
Unfortunately this didn't solve the problem. Does someone have an idea how to sum the values by group and time correctly? I have also uploaded a picture of the real dataset.
python pandas pandas-groupby
edited Mar 21 at 20:13
petezurich
3,76581936
asked Mar 21 at 19:59
PatPat
82
Related: stackoverflow.com/questions/39922986/pandas-group-by-and-sum
– Leonid
Mar 21 at 20:05
1
df.Value = df.Value.astype(int)then run your code again
– RafaelC
Mar 21 at 20:06
1
You have strings and not numbers. When yousum, you concatenate the strings. Notice that you have to assign back the result ofdf.Value.astype(int)
– RafaelC
Mar 21 at 20:07
What is GEO is groupby?
– Rarblack
Mar 21 at 20:10
add a comment |
I would like to sum multiple values to one in python.
See the picture below of my data. I want to sum all the values of AGE for each year for each country.
Instead of having this:
country TIME AGE Value
A 2017 20-60 200
A 2017 60-80 100
A 2016 20-60 200
A 2016 60-80 200
B 2017 20-60 300
B 2017 60-80 300
B 2016 20-60 400
B 2016 60-80 400
I would like to have this:
country TIME Value
A 2017 300
A 2016 400
B 2017 600
B 2016 800
The types of data:
df4types
AGE object
Value object
dtype: object
The data has a multi index by country and TIME.
If have tried this:
df=df.groupby(by=["TIME","GEO"])['Value'].sum()
and this:
df=df.groupby(by=["TIME","GEO"]).sum()['Value']
Both "worked" but result in an enormous value. Like it doesn't sum but paste the numbers behind each other. I have tried to change the variable type to numeric by using:
by df.Value.astype(float) & df.Value.astype(int)
Unfortunately this didn't solve the problem. Does someone have an idea how to sum the values by group and time correctly? I have also uploaded a picture of the real dataset.
python pandas pandas-groupby
edited Mar 21 at 20:13
petezurich
3,76581936
asked Mar 21 at 19:59
PatPat
82
I would like to sum multiple values to one in python.
See the picture below of my data. I want to sum all the values of AGE for each year for each country.
Instead of having this:
country TIME AGE Value
A 2017 20-60 200
A 2017 60-80 100
A 2016 20-60 200
A 2016 60-80 200
B 2017 20-60 300
B 2017 60-80 300
B 2016 20-60 400
B 2016 60-80 400
I would like to have this:
country TIME Value
A 2017 300
A 2016 400
B 2017 600
B 2016 800
The types of data:
df4types
AGE object
Value object
dtype: object
The data has a multi index by country and TIME.
If have tried this:
df=df.groupby(by=["TIME","GEO"])['Value'].sum()
and this:
df=df.groupby(by=["TIME","GEO"]).sum()['Value']
Both "worked" but result in an enormous value. Like it doesn't sum but paste the numbers behind each other. I have tried to change the variable type to numeric by using:
by df.Value.astype(float) & df.Value.astype(int)
Unfortunately this didn't solve the problem. Does someone have an idea how to sum the values by group and time correctly? I have also uploaded a picture of the real dataset.
python pandas pandas-groupby
python pandas pandas-groupby
edited Mar 21 at 20:13
petezurich
3,76581936
asked Mar 21 at 19:59
PatPat
82
edited Mar 21 at 20:13
petezurich
3,76581936
asked Mar 21 at 19:59
PatPat
82
edited Mar 21 at 20:13
petezurich
3,76581936
edited Mar 21 at 20:13
petezurich
3,76581936
edited Mar 21 at 20:13
petezurich
3,76581936
3,76581936
asked Mar 21 at 19:59
PatPat
82
asked Mar 21 at 19:59
PatPat
82
asked Mar 21 at 19:59
PatPat
82
82
Related: stackoverflow.com/questions/39922986/pandas-group-by-and-sum
– Leonid
Mar 21 at 20:05
1
df.Value = df.Value.astype(int)then run your code again
– RafaelC
Mar 21 at 20:06
1
You have strings and not numbers. When yousum, you concatenate the strings. Notice that you have to assign back the result ofdf.Value.astype(int)
– RafaelC
Mar 21 at 20:07
What is GEO is groupby?
– Rarblack
Mar 21 at 20:10
add a comment |
Related: stackoverflow.com/questions/39922986/pandas-group-by-and-sum
– Leonid
Mar 21 at 20:05
1
df.Value = df.Value.astype(int)then run your code again
– RafaelC
Mar 21 at 20:06
1
You have strings and not numbers. When yousum, you concatenate the strings. Notice that you have to assign back the result ofdf.Value.astype(int)
– RafaelC
Mar 21 at 20:07
What is GEO is groupby?
– Rarblack
Mar 21 at 20:10
Related: stackoverflow.com/questions/39922986/pandas-group-by-and-sum
– Leonid
Mar 21 at 20:05
Related: stackoverflow.com/questions/39922986/pandas-group-by-and-sum
– Leonid
Mar 21 at 20:05
1
1
df.Value = df.Value.astype(int) then run your code again– RafaelC
Mar 21 at 20:06
df.Value = df.Value.astype(int) then run your code again– RafaelC
Mar 21 at 20:06
1
1
You have strings and not numbers. When you
sum, you concatenate the strings. Notice that you have to assign back the result of df.Value.astype(int)– RafaelC
Mar 21 at 20:07
You have strings and not numbers. When you
sum, you concatenate the strings. Notice that you have to assign back the result of df.Value.astype(int)– RafaelC
Mar 21 at 20:07
What is GEO is groupby?
– Rarblack
Mar 21 at 20:10
What is GEO is groupby?
– Rarblack
Mar 21 at 20:10
add a comment |
1 Answer
1
active
oldest
votes
- The age column doesn't seem to play a role in the data you want.
- The "Value" shouldn't be a dtype=object. If you try
df.Value = df.Value.astype(int)ordf.Value=pd.to_numeric(df.Value)and it doesn't work then I'm betting there is some data you will need to clean up in that column) - You shouldn't need to mess with the multi index
After you do the above then try this code.
import pandas as pd
df = pd.DataFrame(<your data here>)
result = df.groupby(by=['country','TIME']).sum()
answered Mar 21 at 20:16
Back2BasicsBack2Basics
4,63311936
add a comment |
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1 Answer
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oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
- The age column doesn't seem to play a role in the data you want.
- The "Value" shouldn't be a dtype=object. If you try
df.Value = df.Value.astype(int)ordf.Value=pd.to_numeric(df.Value)and it doesn't work then I'm betting there is some data you will need to clean up in that column) - You shouldn't need to mess with the multi index
After you do the above then try this code.
import pandas as pd
df = pd.DataFrame(<your data here>)
result = df.groupby(by=['country','TIME']).sum()
answered Mar 21 at 20:16
Back2BasicsBack2Basics
4,63311936
add a comment |
- The age column doesn't seem to play a role in the data you want.
- The "Value" shouldn't be a dtype=object. If you try
df.Value = df.Value.astype(int)ordf.Value=pd.to_numeric(df.Value)and it doesn't work then I'm betting there is some data you will need to clean up in that column) - You shouldn't need to mess with the multi index
After you do the above then try this code.
import pandas as pd
df = pd.DataFrame(<your data here>)
result = df.groupby(by=['country','TIME']).sum()
answered Mar 21 at 20:16
Back2BasicsBack2Basics
4,63311936
add a comment |
- The age column doesn't seem to play a role in the data you want.
- The "Value" shouldn't be a dtype=object. If you try
df.Value = df.Value.astype(int)ordf.Value=pd.to_numeric(df.Value)and it doesn't work then I'm betting there is some data you will need to clean up in that column) - You shouldn't need to mess with the multi index
After you do the above then try this code.
import pandas as pd
df = pd.DataFrame(<your data here>)
result = df.groupby(by=['country','TIME']).sum()
answered Mar 21 at 20:16
Back2BasicsBack2Basics
4,63311936
- The age column doesn't seem to play a role in the data you want.
- The "Value" shouldn't be a dtype=object. If you try
df.Value = df.Value.astype(int)ordf.Value=pd.to_numeric(df.Value)and it doesn't work then I'm betting there is some data you will need to clean up in that column) - You shouldn't need to mess with the multi index
After you do the above then try this code.
import pandas as pd
df = pd.DataFrame(<your data here>)
result = df.groupby(by=['country','TIME']).sum()
answered Mar 21 at 20:16
Back2BasicsBack2Basics
4,63311936
answered Mar 21 at 20:16
Back2BasicsBack2Basics
4,63311936
answered Mar 21 at 20:16
Back2BasicsBack2Basics
4,63311936
answered Mar 21 at 20:16
Back2BasicsBack2Basics
4,63311936
4,63311936
add a comment |
add a comment |
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Related: stackoverflow.com/questions/39922986/pandas-group-by-and-sum
– Leonid
Mar 21 at 20:05
1
df.Value = df.Value.astype(int)then run your code again– RafaelC
Mar 21 at 20:06
1
You have strings and not numbers. When you
sum, you concatenate the strings. Notice that you have to assign back the result ofdf.Value.astype(int)– RafaelC
Mar 21 at 20:07
What is GEO is groupby?
– Rarblack
Mar 21 at 20:10