PandasDataframe to_datetime error
Multi tool use
Clash Royale CLAN TAG#URR8PPPPandasDataframe to_datetime error
I have got the following indices on a dataframe:
data extracted Index(['2014-06-30 00:00:00.0', '2014-07-07 00:00:00.0',
'2014-08-11 00:00:00.0', '2014-08-18 00:00:00.0',
'2014-08-25 00:00:00.0', '2014-09-08 00:00:00.0',
'2014-09-22 00:00:00.0', '2014-09-29 00:00:00.0',
'2014-10-06 00:00:00.0', '2014-10-27 00:00:00.0',
'2014-11-24 00:00:00.0', '2014-12-15 00:00:00.0',
'2014-12-29 00:00:00.0', '2015-01-05 00:00:00.0',
'2015-01-19 00:00:00.0', '2015-01-26 00:00:00.0',
'2015-02-02 00:00:00.0', '2015-02-16 00:00:00.0',
'2015-02-23 00:00:00.0', '2015-04-13 00:00:00.0',
'2015-04-20 00:00:00.0', '2015-05-04 00:00:00.0',
'2015-05-25 00:00:00.0', '2015-06-01 00:00:00.0',
'2015-06-15 00:00:00.0', '2015-06-22 00:00:00.0',
'2015-06-29 00:00:00.0', '2015-07-13 00:00:00.0',
'2015-07-20 00:00:00.0', '2015-08-17 00:00:00.0',
'2015-08-24 00:00:00.0', '2015-08-31 00:00:00.0',
'2015-09-07 00:00:00.0', '2015-10-05 00:00:00.0',
'2015-10-12 00:00:00.0', '2015-10-19 00:00:00.0',
'2015-11-09 00:00:00.0', '2015-11-16 00:00:00.0',
'2015-11-30 00:00:00.0', '2016-01-18 00:00:00.0',
'2016-02-01 00:00:00.0', '2016-02-15 00:00:00.0',
'2016-02-29 00:00:00.0', '2016-03-14 00:00:00.0',
'2016-04-04 00:00:00.0', '2016-04-11 00:00:00.0',
'2016-04-25 00:00:00.0', '2016-05-16 00:00:00.0',
'2016-05-30 00:00:00.0', '2016-06-20 00:00:00.0',
'2016-06-27 00:00:00.0', '2016-07-18 00:00:00.0',
'2016-08-01 00:00:00.0', '2016-08-15 00:00:00.0',
'2016-08-22 00:00:00.0', '2016-09-12 00:00:00.0',
'2016-10-03 00:00:00.0', '2016-11-07 00:00:00.0',
'2016-11-14 00:00:00.0', '2016-11-21 00:00:00.0',
'2016-12-05 00:00:00.0', '2016-12-19 00:00:00.0', 'DATE'],
dtype='object', name='DATE')
I want to do a weekly resampling on monday on this dataframe indices, so i need to convert them to a datetime index:
data = pd.read_csv('statistic.csv',
parse_dates=True, index_col=['DATE'], low_memory=False)
data[['QUANTITY']] = data[['QUANTITY']].apply(pd.to_numeric, errors='coerce')
data_extracted = data.groupby(['DATE','ARTICLENO'])
['QUANTITY'].sum().unstack()
data_extracted = data_extracted.fillna(value=np.nan)
data_extracted.index = pd.to_datetime(data_extracted.index)
When i try to convert the index like above, i get an error:
ValueError: Unknown string format
I think it is the last entry ('DATE'). How can i remove this?data_extracted.index[:-1]?
How to convert to a weekly series? I know the .resample('W-MON') but read about some bugs and unexpected behaviour. Additionally, my data is not in regular distance, there is data every monday but not every seven days.
data_extracted.index[:-1]
.resample('W-MON')
1 Answer
1
You can use:
data_extracted.index = pd.to_datetime(data_extracted.index.str[:-2], errors='coerce')
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