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beaumartinez/pandas_issue.py

Created August 8, 2012 11:54
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Pandas data issues
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pandas_issue.py
from itertools import imap, izip
import datetime
import pandas
data = (
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datetime.datetime(2012, 5, 29, 13, 26, 50, 851000),
datetime.datetime(2012, 5, 29, 13, 29, 22, 787000),
datetime.datetime(2012, 5, 29, 13, 34, 18, 383000),
datetime.datetime(2012, 5, 29, 13, 34, 35, 665000),
datetime.datetime(2012, 5, 29, 13, 35, 6, 475000),
datetime.datetime(2012, 5, 29, 13, 35, 13, 644000),
datetime.datetime(2012, 5, 29, 13, 35, 13, 807000),
datetime.datetime(2012, 5, 29, 13, 35, 36, 205000),
datetime.datetime(2012, 5, 29, 13, 35, 36, 383000),
datetime.datetime(2012, 5, 29, 13, 35, 36, 663000),
datetime.datetime(2012, 5, 29, 13, 35, 41, 20000),
datetime.datetime(2012, 5, 29, 13, 35, 44, 748000),
datetime.datetime(2012, 5, 29, 13, 35, 49, 777000),
datetime.datetime(2012, 5, 29, 14, 28, 18, 921000),
datetime.datetime(2012, 5, 29, 14, 28, 22, 348000),
datetime.datetime(2012, 5, 29, 14, 28, 26, 438000),
datetime.datetime(2012, 5, 29, 14, 28, 30, 472000),
datetime.datetime(2012, 5, 29, 18, 41, 4, 526000),
datetime.datetime(2012, 5, 30, 10, 10, 56, 987000),
datetime.datetime(2012, 5, 30, 10, 16, 55, 112000),
datetime.datetime(2012, 5, 30, 10, 17, 4, 121000),
datetime.datetime(2012, 5, 30, 10, 17, 6, 919000),
datetime.datetime(2012, 5, 30, 10, 17, 10, 279000),
datetime.datetime(2012, 5, 30, 11, 18, 16, 290000),
datetime.datetime(2012, 5, 31, 15, 47, 33, 75000),
datetime.datetime(2012, 5, 31, 15, 49, 29, 670000),
datetime.datetime(2012, 5, 31, 15, 49, 35, 790000),
datetime.datetime(2012, 5, 31, 15, 49, 45, 52000),
datetime.datetime(2012, 5, 31, 15, 50, 3, 644000),
datetime.datetime(2012, 5, 31, 15, 50, 8, 461000),
datetime.datetime(2012, 6, 11, 14, 3, 30, 917000),
datetime.datetime(2012, 6, 11, 16, 24, 55, 911000),
datetime.datetime(2012, 6, 13, 16, 30, 6, 467000),
datetime.datetime(2012, 6, 13, 16, 32, 0, 366000),
datetime.datetime(2012, 6, 13, 18, 34, 25, 825000),
datetime.datetime(2012, 6, 13, 18, 41, 39, 451000),
datetime.datetime(2012, 6, 13, 18, 42, 45, 346000),
datetime.datetime(2012, 6, 13, 18, 44, 24, 99000),
datetime.datetime(2012, 6, 13, 22, 2, 55, 25000),
datetime.datetime(2012, 6, 13, 22, 6, 33, 688000),
datetime.datetime(2012, 6, 13, 22, 11, 17, 247000),
datetime.datetime(2012, 6, 19, 15, 16, 42, 318000),
datetime.datetime(2012, 6, 19, 15, 31, 50, 579000),
datetime.datetime(2012, 6, 20, 12, 6, 27, 972000),
datetime.datetime(2012, 6, 20, 12, 38, 43, 321000),
datetime.datetime(2012, 6, 20, 12, 44, 48, 95000),
datetime.datetime(2012, 6, 22, 17, 22, 16, 407000),
datetime.datetime(2012, 6, 22, 17, 22, 20, 67000),
datetime.datetime(2012, 6, 22, 17, 22, 23, 311000),
datetime.datetime(2012, 6, 22, 17, 22, 51, 534000),
datetime.datetime(2012, 6, 22, 17, 22, 58, 834000),
datetime.datetime(2012, 6, 22, 17, 23, 2, 39000),
datetime.datetime(2012, 6, 22, 17, 23, 4, 948000),
datetime.datetime(2012, 6, 22, 17, 23, 30, 27000),
datetime.datetime(2012, 6, 22, 17, 23, 32, 690000),
datetime.datetime(2012, 6, 22, 17, 23, 36, 214000),
datetime.datetime(2012, 6, 22, 17, 24, 19, 742000),
datetime.datetime(2012, 6, 25, 12, 9, 11, 224000),
datetime.datetime(2012, 6, 25, 12, 16, 51, 666000),
datetime.datetime(2012, 6, 25, 12, 20, 37, 972000),
datetime.datetime(2012, 6, 25, 12, 24, 13, 896000),
datetime.datetime(2012, 6, 25, 12, 26, 34, 607000),
datetime.datetime(2012, 6, 25, 12, 27, 21, 332000),
datetime.datetime(2012, 6, 25, 12, 34, 2, 632000),
datetime.datetime(2012, 6, 25, 12, 40, 46, 691000),
datetime.datetime(2012, 6, 25, 12, 41, 4, 19000),
datetime.datetime(2012, 6, 25, 13, 1, 17, 900000),
datetime.datetime(2012, 6, 25, 14, 33, 8, 315000),
datetime.datetime(2012, 6, 25, 14, 33, 22, 370000),
datetime.datetime(2012, 6, 25, 16, 14, 14, 717000),
datetime.datetime(2012, 6, 25, 16, 25, 14, 321000),
datetime.datetime(2012, 6, 25, 16, 30, 32, 818000),
datetime.datetime(2012, 6, 26, 11, 6, 48, 384000),
datetime.datetime(2012, 6, 27, 15, 14, 39, 145000),
datetime.datetime(2012, 6, 29, 11, 48, 20, 572000),
datetime.datetime(2012, 6, 29, 11, 48, 53, 697000),
datetime.datetime(2012, 6, 30, 17, 20, 37, 819000),
datetime.datetime(2012, 7, 3, 14, 19, 21, 892000),
datetime.datetime(2012, 7, 3, 14, 19, 58, 702000),
datetime.datetime(2012, 7, 3, 14, 39, 6, 488000),
datetime.datetime(2012, 7, 3, 16, 7, 27, 977000),
datetime.datetime(2012, 7, 4, 9, 41, 42, 951000),
datetime.datetime(2012, 7, 5, 11, 17, 15, 491000),
datetime.datetime(2012, 7, 5, 11, 20, 25, 389000),
datetime.datetime(2012, 7, 5, 11, 24, 46, 62000),
datetime.datetime(2012, 7, 6, 11, 53, 6, 399000),
datetime.datetime(2012, 7, 6, 11, 54, 48, 872000),
datetime.datetime(2012, 7, 10, 11, 42, 13, 972000),
datetime.datetime(2012, 7, 10, 13, 4, 4, 821000),
datetime.datetime(2012, 7, 10, 15, 59, 46, 161000),
datetime.datetime(2012, 7, 11, 10, 45, 36, 625000),
datetime.datetime(2012, 7, 13, 13, 38, 4, 832000)],
u'values': [26.936,
26.936,
299.64,
134.12400000000002,
21.9,
471.41999999999996,
43.8,
43.8,
358.08,
500.58,
566.28,
682.0799999999999,
219.264,
219.264,
240.276,
156.024,
186.6,
138.00000000000003,
201.23999999999998,
219.264,
186.6,
146.376,
62.124,
197.364,
201.23999999999998,
276.624,
370.524,
219.264,
398.304,
869.7239999999999,
157.14,
314.28,
291.264,
179.04,
92.07600000000002,
156.024,
219.264,
179.04,
179.04,
470.304,
510.5279999999999,
156.024,
272.94,
131.4,
570.0,
43.8,
179.04,
219.264,
383.66400000000004,
197.364,
433.764,
455.66400000000004,
495.88800000000003,
43.092,
21.491999999999997,
48.708,
21.093999999999998,
47.806000000000004,
304.8760000000001,
111.888,
103.74,
10.347999999999999,
21.491999999999997,
119.515,
54.907999999999994,
53.872,
42.294,
73.06200000000001,
97.416,
97.416,
97.416,
121.77,
211.46999999999997,
73.06200000000001,
20.695999999999998,
48.708,
62.16,
712.5,
10.8,
7.2,
157.14,
570.0,
80.4,
0.0,
43.8,
157.14,
109.5,
855.0,
855.0,
365.64,
459.5400000000001,
157.14,
339.86400000000003,
219.264,
179.04,
87.6,
179.04,
393.53999999999996,
43.8,
146.14800000000002,
157.14,
157.14,
157.14,
157.14,
157.14,
157.14,
157.14,
157.14,
157.14,
314.28,
408.17999999999995,
550.68,
590.904,
644.5799999999999,
272.94,
430.08,
523.98,
545.88,
549.756,
219.264,
219.264,
179.04,
492.20399999999995,
219.264,
438.5279999999999,
617.5679999999999,
219.264,
156.024,
40.224000000000004,
208.5,
276.624,
142.5,
236.4,
258.3,
21.9,
62.124,
156.024,
119.676,
415.44,
313.16400000000004,
219.264,
416.62799999999993,
179.04,
276.816,
298.716,
320.61599999999993,
272.94,
366.84,
509.34,
728.6039999999999,
750.5039999999999,
907.6439999999999,
907.6439999999999,
157.14,
127.32,
17.964000000000002,
0.0,
286.74,
30.0,
129.6,
157.14,
129.6,
352.8,
30.0,
12.0,
132.0,
36.0,
270.0,
244.8,
240.0,
4.8,
6.0,
479.988,
0.0,
8.280000000000001,
2.4,
9.6,
960.0,
54.0,
14.4,
54.0,
119.97599999999998,
17.988,
5.988,
27.6,
13.188,
27.6,
25.188]}})
df1_data = {}
for datum in data:
df1_data[datum['_id']] = pandas.Series(datum['value']['values'], index=datum['value']['timestamps'])
df1 = pandas.DataFrame(df1_data)
# Completely fucked up
print df1
# Sort the data
for datum in data:
pairs = izip(datum['value']['timestamps'], datum['value']['values'])
pairs = sorted(pairs, key=lambda x: x[0])
datum['value']['timestamps'] = imap(lambda x: x[0], pairs)
datum['value']['values'] = imap(lambda x: x[1], pairs)
df2_data = {}
for datum in data:
df2_data[datum['_id']] = pandas.Series(datum['value']['values'], index=datum['value']['timestamps'])
df2 = pandas.DataFrame(df2_data)
# Fine
print df2
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