Fix Python – Does pandas iterrows have performance issues?

I have noticed very poor performance when using iterrows from pandas.
Is it specific to iterrows and should this function be avoided for data of a certain size (I’m working with 2-3 million rows)?
This discussion on GitHub led me to believe it is caused when mixing dtypes in the dataframe, however the simple example below shows it is there even wh….

Fix Python – Is there a way in Pandas to use previous row value in dataframe.apply when previous value is also calculated in the apply?

I have the following dataframe:
Index_Date A B C D
================================
2015-01-31 10 10 Nan 10
2015-02-01 2 3 Nan 22
2015-02-02 10 60 Nan 280
2015-02-03 10 100 Nan 250

Require:
Index_Date A B C D
================================
2015-01-31 10 10 10 10
2015-02-01 ….

Fix Python – Python using enumerate inside list comprehension

Lets suppose I have a list like this:
mylist = [“a”,”b”,”c”,”d”]

To get the values printed along with their index I can use Python’s enumerate function like this
>>> for i,j in enumerate(mylist):
… print i,j

0 a
1 b
2 c
3 d
>>>

Now, when I try to use it inside a list comprehension it gives me this error
>>> [i,j for i,j in enumerate(my….