CODEWITHSUNDEEP
pythonpandasseries
BLL27
BLL27

Reputation: 951

Finding the first non zero value in a Pandas Series

I have a number Pandas Series with 601 rows indexed by date as seen below. The values are zero up until a point where some non zero values are introduced. This point varies with each Series so I would like to find a way to find the index of the first non zero value and plot from that point onwards.

Name: users, dtype: float64 dates
2015-08-17 14:29:59-04:00    18
2015-08-16 14:29:59-04:00     3
2015-08-15 14:29:59-04:00    11
2015-08-14 14:29:59-04:00    12
2015-08-13 14:29:59-04:00     8
2015-08-12 14:29:59-04:00    10
2015-08-11 14:29:59-04:00     6
2015-08-10 14:29:59-04:00     6
2015-08-09 14:29:59-04:00     7
2015-08-08 14:29:59-04:00     7
2015-08-07 14:29:59-04:00    13
2015-08-06 14:29:59-04:00    16
2015-08-05 14:29:59-04:00    12
2015-08-04 14:29:59-04:00    14
2015-08-03 14:29:59-04:00     5
2015-08-02 14:29:59-04:00     5
2015-08-01 14:29:59-04:00     8
2015-07-31 14:29:59-04:00     6
2015-07-30 14:29:59-04:00     7
2015-07-29 14:29:59-04:00     9
2015-07-28 14:29:59-04:00     7
2015-07-27 14:29:59-04:00     5
2015-07-26 14:29:59-04:00     4
2015-07-25 14:29:59-04:00     8
2015-07-24 14:29:59-04:00     8
2015-07-23 14:29:59-04:00     8
2015-07-22 14:29:59-04:00     9
2015-07-21 14:29:59-04:00     5
2015-07-20 14:29:59-04:00     7
2015-07-19 14:29:59-04:00     6
                             ..
2014-01-23 13:29:59-05:00     0
2014-01-22 13:29:59-05:00     0
2014-01-21 13:29:59-05:00     0
2014-01-20 13:29:59-05:00     0
2014-01-19 13:29:59-05:00     0
2014-01-18 13:29:59-05:00     0
2014-01-17 13:29:59-05:00     0
2014-01-16 13:29:59-05:00     0
2014-01-15 13:29:59-05:00     0
2014-01-14 13:29:59-05:00     0
2014-01-13 13:29:59-05:00     0
2014-01-12 13:29:59-05:00     0
2014-01-11 13:29:59-05:00     0
2014-01-10 13:29:59-05:00     0
2014-01-09 13:29:59-05:00     0
2014-01-08 13:29:59-05:00     0
2014-01-07 13:29:59-05:00     0
2014-01-06 13:29:59-05:00     0
2014-01-05 13:29:59-05:00     0
2014-01-04 13:29:59-05:00     0
2014-01-03 13:29:59-05:00     0
2014-01-02 13:29:59-05:00     0
2014-01-01 13:29:59-05:00     0
2013-12-31 13:29:59-05:00     0
2013-12-30 13:29:59-05:00     0
2013-12-29 13:29:59-05:00     0
2013-12-28 13:29:59-05:00     0
2013-12-27 13:29:59-05:00     0
2013-12-26 13:29:59-05:00     0
2013-12-25 13:29:59-05:00     0

Upvotes: 2

Views: 4896

Answers (1)

Alexander
Alexander

Reputation: 109626

Assuming your Series is named s:

s = s.sort_index()
start = s.loc[s != 0].index
if len(start) > 0:
    filtered_series = s.ix[start[0]:]

Your data appears to be sorted backwards in time (i.e. most recent first), so I first sorted the index.

Then I use loc to get the index values of non-negative values in the series. If this list returns anything (it could be an empty list), then I use .ix to index the series from the first non-zero index value calculated above through the end of the series.

Upvotes: 6

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