How to drop/delete/filter rows in pandas dataframe based on string pattern condition?

Question

Say there's a data frame with (4000,13) shape. Say dataframe["str_labels"] may has "|" value in it. How to sort pandas dataframe based on removing any rows (all 13 columns) consisting of string value "|". example:

list(dataframe["str_labels"])=["abcd","aaa","op|gg","iku | gv"]
filtered_out = ["abcd", "aaa"]

## example code
dataframe["|" not in dataframe["str_labels"]]
# or
dataframe[dataframe["str_Labels"].str.contains("|")]
# ........etc

Can you create minimal, complete, and verifiable example ?

jezrael
– jezrael

2020-10-28 06:23:38 +00:00
Commented Oct 28, 2020 at 6:23 — jezrael
– jezrael, Commented Oct 28, 2020 at 6:23
It means some input data, and expected output?

jezrael
– jezrael

2020-10-28 06:24:05 +00:00
Commented Oct 28, 2020 at 6:24 — jezrael
– jezrael, Commented Oct 28, 2020 at 6:24

Serge de Gosson de Varennes · Accepted Answer · 2020-10-28 06:42:30Z

2

You should make a list of characters that are the conditions for dropping rows:

list = ['<character>', '\|',....]

and then filter your df by

df = df[~df['your column'].isin(['list'])]

Note the \| for the pipe character.

edited Oct 28, 2020 at 6:42

answered Oct 28, 2020 at 5:44

Serge de Gosson de Varennes

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2 Comments

Bhuvan S Over a year ago

For any other string it's working but not for "|". why so?

Serge de Gosson de Varennes Over a year ago

Sorry for the typo. For pipe character | you need in your list to give ´\|'

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