pandas groupby column that has specific value

Question

hi im working with dataset in pandas.
lets say the dataset having
ID,
TEST_TYPE,
TEST_STATUS,
TEST_DATE,
etc

i need to group a kind of column so first i try

data_useless[['TEST_TYPE', 'TEST_STATUS']].groupby('TEST_STATUS').count_values()

and it worked : showing the result of grouped data by test_status(FAILED TEST and PASS TEST) and count value of that data on dataset

now i want to know and see the data more from the PASS TEST

so i tried

data_useless.groupby(['TEST_STATUS'] == 'PASS TEST')

and it not working.. showing error, it say KEY ERROR : FALSE

i need to do something like
in sql :

SELECT *
FROM data_useless
WHERE TEST_STATUS = "PASS TEST"
group by TEST_STATUS;

please help,,,

Asked By: Tristianto Raflesia

||

Source

Answer 1

First, why do you need to group by column when you filter it with just one item??

but if you want to do this, you should first filter the data frame and then a group by operation on the result data frame

data_useless[data_useless.TEST_STATUS == "PASS TEST"].groupby("TEST_STATUS")

Answered By: sam.Taher

Answer 2

try this

data_useless[data_useless['TEST_STATUS']=='PASS TEST'].groupby('TEST_STATUS').count()

Answered By: Abhishek Kumar

Answer 3

You can filter using:

data_useless.loc[data_useless['TEST_STATUS'] == 'PASS TEST']

Or:

data_useless.query('TEST_STATUS == "PASS TEST"')

Then, if needed, compute the groupby + aggregation:

(data_useless.loc[data_useless['TEST_STATUS'] == 'PASS TEST']
             .groupby(...).agg(...) # or any other groupby function
)

Answered By: mozway

Answer 4

If you first make a groupby object, you can pull specific groups using the get_group() method:

groups = df.groupby('TEST_STATUS')

pass_data = groups.get_group('PASS TEST')

# Now you can do whatever you want with that group:
pass_data.groupby(...).agg(...)

Answered By: BeRT2me

pandas groupby column that has specific value

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