Drop rows by string in column value

Question

I have dataframe with 2 columns and a few thousands of rows. What I need now is drop out, delete, rows which contains 'css', 'jpg', 'png', 'favicon', etc. in column values. It looks like this:

Referer      Count

favicon.ico   24
ponto.css     21
mobil/net     16
private/net   14
ort.jpg       11

The desired output is this:

   Referer      Count

    mobil/net     16
    private/net   14

I've tried with this:

df[df['Referer'].str.contains('css', 'jpg', 'png', 'favicon.ico')]

But this is what I got:

unsupported operand type(s) for &: 'str' and 'int'

jezrael · Accepted Answer · 2017-04-19 11:44:29Z

4

Need | what is or in regex and then invert boolean mask by ~.

So need css or jpg ...

df = df[~df['Referer'].str.contains('css|jpg|png|favicon.ico')]
print (df)
       Referer  Count
2    mobil/net     16
3  private/net     14

If values are in list, is possible use join with | - output is same.

L = ['css','jpg','png','favicon.ico']

df = df[~df['Referer'].str.contains('|'.join(L))]
print (df)
       Referer  Count
2    mobil/net     16
3  private/net     14

answered Apr 19, 2017 at 11:44

jezrael

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5 Comments

jezrael Over a year ago

Glad can help you! Nice day!

Praveen Over a year ago

@jezrael, you are really fast :-)

jezrael Over a year ago

@Praveen - Sometimes yes, sometimes not. But I think your solution is same, so the best is delete it. Thanks

Praveen Over a year ago

@jezrael i guess, bracket notation is better than dot notation.

jezrael Over a year ago

Yes, obviously yes. There is also problem with columns like sum, mean if use dot notation.

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