Python crashes after string strip

[yarivm]

This minimal code crashes my Python. (Setting: pandas 0.13.0, python 2.7.3 AMD64, Win7.)

    import pandas as pd
    input_file = r"c3.csv"
    input_df = pd.read_csv(input_file)
    for col in input_df.columns:  # strip whitespaces from string values
        if input_df[col].dtype == object:
            input_df[col] = input_df[col].apply(lambda x: x.strip())
    print 'start'
    for idx in range(len(input_df)):
        input_df['LL'].iloc[idx] = 3
        print idx
    print 'finished'

Output:

start
0

Process finished with exit code -1073741819

What prevents the crash:

1. Removing lines from c3.csv.
2. Removing .strip() from the code.
3. Changing c3.csv changes the amount of for iterations until the crash in unexpected ways.

Contents of c3.csv:

Size , B/S , Symbol , Type , BN , Duration , VR , Time , SR ,LL, 0, xxxx , xxxx0 , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 00, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 ,

[jreback]

This looks the same as just fixed in master, can you try on master:

The chained indexing with object type is the problem

#6031

what version of numpy?

[jreback]

I updated your SO issue

closing as already fixed