python - Pandas Data Frame filtering based off a column condition -


i trying remove rows data frame condition met in 1 column.

lets data frame this:

index  'value 1'   'grade' 1         10         2170a 2         15         2170b 3         10         ncr2170b 4         20         ncr2170a 5         30         ncr2170b

i want output after filtering this

    index  'value 1'   'grade' 2         15         2170b 3         10         ncr2170b 5         30         ncr2170b

i have tried many different variations of using list comprehension, looping through each row , evaluating. can make work when use along lines of:

data_filtered = data[data['grade'] == '2170b']

but misses entries ncr2170b.

whenever try like:

data_filtered = data['2170b' in data['grade']]

i key error: 'true'.

i feel missing obvious here.

i have tried using np.where outputs empty array.

you can use str.contains check if string column contains sub string:

df[df.grade.str.contains('2170b')]  #index  value 1    grade #1  2        15    2170b #2  3        10 ncr2170b #4  5        30 ncr2170b

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