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Neat Analytics with Pandas
A Closer Look at Pandas Indexing
Alexander C. S. Hendorf
@hendorf
Alexander C. S. Hendorf
Königsweg GmbH
Strategic data consulting for startups and the industry.
EuroPython & PyConDE 

Org...
Today
Closer Look at Indexes
- Catch up on Pandas indexing
- Accessing data using the index
- Index Types
- MultiIndex
- C...
Structure: Index
-the label of a series is usually called index
-automatically created if not given
-can be reset or repla...
Index Types
-Index
-MultiIndex
-DateTimeIndex
-TimeDelta
-IntervalIndex
-CategoricalIndex
Structure
DataFrame
2D
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1...
Axes
1 2 3
0
1
0
1
2
3
4
5
6
no match: NaN
only if index matches
MultiIndex
max value of each series (not row)
get level 0 data
get level 1 data
get level 2 data
•
•
•
•
DateTimeIndex
-index of datetime64 data
2014-09-26T03:50:00,14.0
2014-08-10T05:00:00,14
2014-08-21T22:50:00,12.0
2014-08-17T13:20:00,16.0
2014-08-06T01:20:00,14.0...
DateTime
format="%d.%m.%Y %H:%M:%S
before DateTimeIndex: unordered
Resampling
Resampling
-H hourly frequency
-T minutely frequency
-S secondly frequency
-L milliseonds
-U microseconds
-N nanoseconds
-...
Extra discounts for
students & post docs
#16
180+sessions 18free
trainings
panels open
spaces
5dtalks &
trainings
2dsprint...
25. - 27. October
ZKM, Karlsruhe
CfP is open!
Alexander C. S. Hendorf
ah@koenigsweg.com
@hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
Neat Analytics with Pandas Indexes, Alexander Hendorf
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PyParis 2017
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Neat Analytics with Pandas Indexes, Alexander Hendorf

  1. 1. Neat Analytics with Pandas A Closer Look at Pandas Indexing Alexander C. S. Hendorf @hendorf
  2. 2. Alexander C. S. Hendorf Königsweg GmbH Strategic data consulting for startups and the industry. EuroPython & PyConDE 
 Organisator + Programm Chair mongoDB master, PSF managing member Speaker mongoDB days, EuroPython, PyData… @hendorf
  3. 3. Today Closer Look at Indexes - Catch up on Pandas indexing - Accessing data using the index - Index Types - MultiIndex - Closer look at DateTimeIndex and Resampling
  4. 4. Structure: Index -the label of a series is usually called index -automatically created if not given -can be reset or replaced -immutable ndarray implementing an ordered, sliceable set -can only contain hashable objects -one or more dimensions -may contain a value more than once (NOT UNIQUE!)
  5. 5. Index Types -Index -MultiIndex -DateTimeIndex -TimeDelta -IntervalIndex -CategoricalIndex
  6. 6. Structure DataFrame 2D 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 … Panel 3DXXXXXXXXX pd.Series 1D 1 2 3 4 5 6 7 1 2 3 4 5 6 7 Index Data: Numpy array
  7. 7. Axes 1 2 3 0 1 0 1 2 3 4 5 6
  8. 8. no match: NaN only if index matches
  9. 9. MultiIndex
  10. 10. max value of each series (not row) get level 0 data get level 1 data get level 2 data • • • •
  11. 11. DateTimeIndex -index of datetime64 data
  12. 12. 2014-09-26T03:50:00,14.0 2014-08-10T05:00:00,14 2014-08-21T22:50:00,12.0 2014-08-17T13:20:00,16.0 2014-08-06T01:20:00,14.0 2014-09-27T06:50:00,11.0 2014-08-25T21:50:00,13.0 2014-08-14T05:20:00,13.0 2014-09-14T05:20:00,16.0 2014-08-03T02:50:00,21.0 2014-09-29T03:00:00,13 2014-09-06T08:20:00,16.0 2014-08-19T07:20:00,13.0 2014-09-27T22:50:00,10.0 2014-08-28T08:20:00,12.0 2014-08-17T01:00:00,14 2014-09-27T14:00:00,17 2014-09-10T18:00:00,18 2014-09-22T23:00:00,8 2014-09-20T03:00:00,9 2014-08-29T09:50:00,16.0 2014-08-16T01:50:00,13.0
  13. 13. DateTime format="%d.%m.%Y %H:%M:%S
  14. 14. before DateTimeIndex: unordered
  15. 15. Resampling
  16. 16. Resampling -H hourly frequency -T minutely frequency -S secondly frequency -L milliseonds -U microseconds -N nanoseconds -D calendar day frequency -W weekly frequency -M month end frequency -Q quarter end frequency -A year end frequency - B business day frequency - C custom business day frequency (experimenta - BM business month end frequency - CBM custom business month end frequency - MS month start frequency - BMS business month start frequency - CBMS custom business month start frequency - BQ business quarter endfrequency - QS quarter start frequency - BQS business quarter start frequency - BA business year end frequency - AS year start frequency - BAS business year start frequency - BH business hour frequency
  17. 17. Extra discounts for students & post docs #16 180+sessions 18free trainings panels open spaces 5dtalks & trainings 2dsprints beginners’ day Tickets start @ 375€ Rimini . Venice ! Bologna ! ✈ . Florence ! . # $ Rome ! . Armin Rohnacher • Katharine Jarmul • Tracy Osborn Jan Willem Tulp • Aisha Bello & Daniele Procida interactive sessions
  18. 18. 25. - 27. October ZKM, Karlsruhe CfP is open!
  19. 19. Alexander C. S. Hendorf ah@koenigsweg.com @hendorf

PyParis 2017 http://pyparis.org

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