Pandas: Counting unique values in a dataframe

Question

We have a DataFrame that looks like this:

> df.ix[:2,:10]
    0   1   2   3   4   5   6   7   8   9   10
0   NaN NaN NaN NaN  6   5  NaN NaN  4  NaN  5
1          


        

Answer 1

Not enough rep to comment, but Andy's answer:

pd.value_counts(d.values.ravel()) 

is what I have used personally, and seems to me to be by far the most versatile and easily-readable solution. Another advantage is that it is easy to use a subset of the columns:

pd.value_counts(d[[1,3,4,6,7]].values.ravel()) 

or

pd.value_counts(d[["col_title1","col_title2"]].values.ravel()) 

Is there any disadvantage to this approach, or any particular reason you want to use stack and groupby?