python - Replacing values greater than a number in pandas dataframe

Question

I have a large dataframe which looks as:

df1['A'].ix[1:3]
2017-01-01 02:00:00    [33, 34, 39]
2017-01-01 03:00:00    [3, 43, 9]

I want to replace each element greater than 9 with 11.

So, the desired output for above example is:

df1['A'].ix[1:3]
2017-01-01 02:00:00    [11, 11, 11]
2017-01-01 03:00:00    [3, 11, 9]

Edit:

My actual dataframe has about 20,000 rows and each row has list of size 2000.

Is there a way to use numpy.minimum function for each row? I assume that it will be faster than list comprehension method?

question from:https://stackoverflow.com/questions/43757977/replacing-values-greater-than-a-number-in-pandas-dataframe

Answer 1

Very simply : df[df > 9] = 11