pandas groupby column that has spesific value-CodePudding

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,,,

CodePudding user response：

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")

CodePudding user response：

try this

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

CodePudding user response：

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
)

CodePudding user response：

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(...)