trying to remove rows with backslash characters with pandas but getting unwanted double quotes added-CodePudding

I need to find and then remove rows that contain a backslash in my csv file. I tried this:

   df[df["query"].str.contains("\\")==False]

but this results in the error:

    sre_constants.error: bogus escape (end of line)

The only way I can avoid this error is with,

    df[df["query"].str.contains("\\\\")==False]

but this adds an extra double quote to everything in the file and does not remove the row.

What is the expression to identify rows containing a backslash and then remove the row?

EDIT: This is an example csv file I'm reading from:

    collection,label,groups,query
    Model,general,Mob,WHERE * SAYS ("trying out app"|| "trying out app"|| "trying out app's")
    Model,general,Bun,WHERE * SAYS ("bundle"|| "bundles"|| "bundled"|| ""tv package""|| ""internet package""|| ""tv and internet package""|| "internet 2 bundle"|| "internet 2 package"|| "tv 2 bundle"|| "tv 2 package"|| "phone 2 bundle"|| "internet 2 phone"|| "internet 2 tv") AND NOT * SAYS ("\"EEOS|| Internet|| TV & Phone Solutions\""|| "\"EOOS|| Internet|| TV\""|| "\"phone solutions\"")

Per the answer below, I edited my code and now the row is removed.

    data = pd.read_csv('so.csv')
    df = pd.DataFrame(data)
    df = df[~df["query"].str.contains("\\", regex=False)]

    df.to_csv('sores.csv')

However in the result, double quotes are added:

    ,collection,label,groups,query
    0,Model,general,Mob,"WHERE * SAYS (""trying out app""|| 
    ""trying out app""|| ""trying out app's"")"

CodePudding user response：

Pandas' .str.contains uses regular expressions by default. Add regex=False to parameters:

df[~df["query"].str.contains("\\", regex=False)]

Also note that instead of comparing to False it's better to negate the result (~ in the beginning)

E.g.:

> df = pd.DataFrame({"query": ['positive: \\', 'negative']})
> df
         query
0  positive: \
1     negative

> df[~df['query'].str.contains("\\", regex=False)]
      query
1  negative