Python: Pandas - Divide Dataframe based on column value
Suppose I have a dataframe like below:
in:
mydata = [{'subid' : 'B14-111', 'age': 75, 'fdg':1.78},
{'subid' : 'B14-112', 'age': 22, 'fdg':1.56},]
df = pd.DataFrame(mydata)
out:
age fdg subid
0 75 1.78 B14-111
1 22 1.56 B14-112
I want to split the data file into two different data frames based on the "age" column as shown below:
out:
df1:
age fdg subid
0 75 1.78 B14-111
df2:
age fdg subid
1 22 1.56 B14-112
How can I achieve this?
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1 answer
We can do this directly by using a boolean condition as a filter:
In [5]:
df1 = df[df.age == 75]
df2 = df[df.age == 22]
print(df1)
print(df2)
age fdg subid
0 75 1.78 B14-111
age fdg subid
1 22 1.56 B14-112
but if you have more age values, you can group them:
In [13]:
# group by the age column
gp = df.groupby('age')
# we can get the unique age values as a dict where the values are the key values
print(gp.groups)
# we can get a specific value passing the key value for the name
gp.get_group(name=75)
{75: [0], 22: [1]}
Out[13]:
age fdg subid
0 75 1.78 B14-111
We can also get unique values and use that again to filter the df:
In [15]:
ages = df.age.unique()
for age in ages:
print(df[df.age == age])
age fdg subid
0 75 1.78 B14-111
age fdg subid
1 22 1.56 B14-112
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