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Description
Code Sample, a copy-pastable example if possible
import pandas as pd
d = {'start_date': ['37:04.0', '55:20.0', '44:05.3', '43:41.7', '40:35.0', '26:14.4', '57:00.7', '18:53.8', '12:23.2', '48:33.2', '36:38.1', '29:35.7', '56:02.4', '27:41.4', '11:49.9', '17:36.6', '50:44.2', '36:36.1', '21:14.7']}
data = pd.DataFrame(data=d)
data['customer_created_at'] = pd.to_datetime(data['start_date'], errors='coerce')
print (data['customer_created_at'])
Problem description
When coercing the list of time values I expect all of them to return NaT. However, a few of these come back with today's date. I tried yesterday and the returned value was:
0 NaT
1 NaT
2 NaT
3 NaT
4 NaT
5 NaT
6 NaT
7 2018-10-31 18:53:48
8 2018-10-31 12:23:12
9 NaT
10 NaT
11 NaT
12 NaT
13 NaT
14 2018-10-31 11:49:54
15 2018-10-31 17:36:36
16 NaT
17 NaT
18 2018-10-31 21:14:42
Today I get:
0 NaT
1 NaT
2 NaT
3 NaT
4 NaT
5 NaT
6 NaT
7 2018-11-01 18:53:48
8 2018-11-01 12:23:12
9 NaT
10 NaT
11 NaT
12 NaT
13 NaT
14 2018-11-01 11:49:54
15 2018-11-01 17:36:36
16 NaT
17 NaT
18 2018-11-01 21:14:42
Expected Output
All time values should return NaT when coerced
Output of pd.show_versions()
pandas: 0.23.4
pytest: 3.5.1
pip: 18.0
setuptools: 39.1.0
Cython: 0.28.2
numpy: 1.14.3
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: 1.7.4
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.3
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
openpyxl: 2.5.3
xlrd: 1.1.0
xlwt: 1.2.0
xlsxwriter: 1.0.4
lxml: 4.2.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.7
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
None