How to calculate differences between consecutive rows in pandas data frame?

Question

I\'ve got a data frame, df, with three columns: count_a, count_b and date; the counts are floats, and the dates are conse

Answer 1

You can using the .rolling_apply(…) method:

diffs_a = pd.rolling_apply(df['count_a'], 2, lambda x: x[0] - x[1])

Alternatively, if it's easier, you can operate on the arrays directly:

count_a_vals = df['count_a'].values
diffs_a = count_a_vals[:-1] - count_a_vals[1:]

Answer 2

diff should give the desired result:

>>> df.diff()
count_a  count_b
2015-01-01      NaN      NaN
2015-01-02    38465      NaN
2015-01-03    36714      NaN
2015-01-04    35137      NaN
2015-01-05    35864      NaN
....
2015-02-07   142390    25552
2015-02-08   126768    22835
2015-02-09   122324    21485