How to do an R style aggregate in Python Pandas?
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I need to do an aggregate (at least that what you would call it in R) over the mtcars data set that I have uploaded into python. The end goal is to get the average mpg for each value of cyl in the data set (There are three values for cyl, 4,6,8). Here is the R code for what I want to do
mean_each_gear <- aggregate(mtcars$mpg ~ mtcars$cyl, FUN = mean)
output:
cyl mpg
1 4 26.66364
2 6 19.74286
3 8 15.10000
The closest I've come with in Pandas is this
mtcars.agg(['mean'])
I'm not sure how I would do that in Pandas. Any help would be appreciated!
python r pandas aggregate
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up vote
0
down vote
favorite
I need to do an aggregate (at least that what you would call it in R) over the mtcars data set that I have uploaded into python. The end goal is to get the average mpg for each value of cyl in the data set (There are three values for cyl, 4,6,8). Here is the R code for what I want to do
mean_each_gear <- aggregate(mtcars$mpg ~ mtcars$cyl, FUN = mean)
output:
cyl mpg
1 4 26.66364
2 6 19.74286
3 8 15.10000
The closest I've come with in Pandas is this
mtcars.agg(['mean'])
I'm not sure how I would do that in Pandas. Any help would be appreciated!
python r pandas aggregate
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I need to do an aggregate (at least that what you would call it in R) over the mtcars data set that I have uploaded into python. The end goal is to get the average mpg for each value of cyl in the data set (There are three values for cyl, 4,6,8). Here is the R code for what I want to do
mean_each_gear <- aggregate(mtcars$mpg ~ mtcars$cyl, FUN = mean)
output:
cyl mpg
1 4 26.66364
2 6 19.74286
3 8 15.10000
The closest I've come with in Pandas is this
mtcars.agg(['mean'])
I'm not sure how I would do that in Pandas. Any help would be appreciated!
python r pandas aggregate
I need to do an aggregate (at least that what you would call it in R) over the mtcars data set that I have uploaded into python. The end goal is to get the average mpg for each value of cyl in the data set (There are three values for cyl, 4,6,8). Here is the R code for what I want to do
mean_each_gear <- aggregate(mtcars$mpg ~ mtcars$cyl, FUN = mean)
output:
cyl mpg
1 4 26.66364
2 6 19.74286
3 8 15.10000
The closest I've come with in Pandas is this
mtcars.agg(['mean'])
I'm not sure how I would do that in Pandas. Any help would be appreciated!
python r pandas aggregate
python r pandas aggregate
edited Nov 9 at 23:08
asked Nov 9 at 22:59
Tanner
104
104
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1 Answer
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You want pandas groupby()!
import pandas as pd
my_dataframe = pd.read_csv('my_input_data.csv') //insert your data here
pd.groupby(['col1'])['col2'].mean()
where 'col1' is the column you want to group by and 'col2' is the column whose mean you want to obtain. Also see here:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
You want pandas groupby()!
import pandas as pd
my_dataframe = pd.read_csv('my_input_data.csv') //insert your data here
pd.groupby(['col1'])['col2'].mean()
where 'col1' is the column you want to group by and 'col2' is the column whose mean you want to obtain. Also see here:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html
add a comment |
up vote
0
down vote
accepted
You want pandas groupby()!
import pandas as pd
my_dataframe = pd.read_csv('my_input_data.csv') //insert your data here
pd.groupby(['col1'])['col2'].mean()
where 'col1' is the column you want to group by and 'col2' is the column whose mean you want to obtain. Also see here:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
You want pandas groupby()!
import pandas as pd
my_dataframe = pd.read_csv('my_input_data.csv') //insert your data here
pd.groupby(['col1'])['col2'].mean()
where 'col1' is the column you want to group by and 'col2' is the column whose mean you want to obtain. Also see here:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html
You want pandas groupby()!
import pandas as pd
my_dataframe = pd.read_csv('my_input_data.csv') //insert your data here
pd.groupby(['col1'])['col2'].mean()
where 'col1' is the column you want to group by and 'col2' is the column whose mean you want to obtain. Also see here:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html
edited Nov 10 at 0:16
answered Nov 9 at 23:08
HappyDog
465
465
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