Print value from a list (The truth value of a DataFrame is ambiguous error)
You're trying to compare a df, which is unnecessary here by the way, with a scalar value which is incorrect as it becomes ambiguous for testing a scalar value against because you may have 1 or more matches. I think you want: if all(stock['Whs']] == 'VLN'): or if you know...
Pandas speedup apply on max()
In [22]: pd.set_option('max_rows',20) In [33]: N = 10000000 In [34]: df = DataFrame({'A' : np.random.randint(0,100,size=N), 'B' : np.random.randint(0,100,size=N)}) In [35]: df[df.groupby('A')['B'].transform('max') == df['B']] Out[35]: A B 161 30 99 178 53 99 264 58 99 337 96 99 411 44 99 428 85 99 500 84 99 598 98 99...
Convert unique numbers to md5 hash using pandas
python,python-2.7,pandas,hashlib,pandasql
hashlib.md5 takes a single string as input -- you can't pass it an array of values as you can with some NumPy/Pandas functions. So instead, you could use a list comprehension to build a list of md5sums: ob['md5'] = [hashlib.md5(val).hexdigest() for val in ob['ssno']] ...