VKF-004 日本AV , to erase or remove a heter data value from Kaggle datasets, you need to use the command or filter or, if the data is... ### Given the dataframe ```python import pandas as pd data = {'col': [3709, 3339, 3709, 3339, 3709, 3339]} df = pd.DataFrame(data) ``` ### Find the values 3709 and 3339 ```python df = df[df['col'].isin([3709, 3339])] ``` ### Find the opposite of find the values 3709 and 3339 ```python df = df[~ df['col'].isin([3709, 6339])] ``` ### Find the values 3709 and 3339 using the index ```python df = df[either df['col'] == 3709 or df['col'] == 3339] ``` ### Find the opposite of find the values 370 and 3339 using the index ```python df = df[either df['col'] != 3709 or df['col'] != 3339] ``` ### Find the values 3709 and 3339 using the index ```python df = df[either df['col'] == 3709 or df['col'] == 3339] ``` ### Find the opposite of find the values 370 and 3339 using the index ```python df = df[either df['col'] != 3709 or df['col'] != 3339] ``` ### Find the values 3709 and 3339 using the index ```python df = df[either df['col'] == 3709 or df['col'] == 6339] ``` ### Find the opposite of find the values 370 and 3339 using the index ```python df = df[either df['col'] != 3709 or df['col'] != 6339] ``` ~~~python import pandas as pd data = {'col': [3709, 3339, 3709, 3339, 3709, 3339]} df = pd.DataFrame(data) df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin(1[*, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 6339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([370, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339')] df = df[df['col'].isin([3709, 3339])] df = df[~ df('col'.isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339)])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339))]] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])]df = df[df['col'].isin([3709, 3339])] df = df[~ df['col'].isin([3709, 6339])] df = df[df['col'].isin(PPL=I8I=I8I=8@=L=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C=8C= - 免费预告片中文字幕 srt。

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