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How to exclude rows if any of the columns in a dataframe contains non-binary (0 or 1) numbers. Not to exclude based on a specific column, but for all of the columns.

For example, we have a dataframe like this, and we want to delete row number 0, 2 and 4.

array = [[1, 0, 0, 0, 0, 0, 2],
         [1, 0, 0, 1, 0, 0, 0],
         [2, 0, 0, 1, 0, 0, 0],
         [0, 0, 0, 0, 0, 1, 0],
         [1, 0, 0, 3, 0, 0, 0]]
df = pd.DataFrame(array, columns = ['AB','AC','CB','DE','FA','CD','AF'] )

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Trenton McKinney
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Jiamei
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2 Answers2

2
df = df[df.isin([1, 0])].dropna()

# display(df)
    AB  AC  CB   DE  FA  CD   AF
1  1.0   0   0  1.0   0   0  0.0
3  0.0   0   0  0.0   0   1  0.0
Trenton McKinney
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0
  • Another Method is
df = df[~df.isin([0, 1])]
  • where ~ means not
  • Also we can use .dropna() at the end of the code, Instead of ~

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Vikas Ukani
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