python pandas convert index to datetime

Question

How do i convert a pandas index of strings to datetime format

my dataframe 'df' is like this

                     value           2015-09-25 00:46    71.925000 2015-09-25 00:47    71.625000 2015-09-25 00:48    71.333333 2015-09-25 00:49    64.571429 2015-09-25 00:50    72.285714 

but the index is of type string, but i need it a datetime format because i get the error

'Index' object has no attribute 'hour' 

when using

 df['A'] = df.index.hour 

Answer 1

It should work as expected. Try to run the following example.

import pandas as pd import io  data = """value           "2015-09-25 00:46"    71.925000 "2015-09-25 00:47"    71.625000 "2015-09-25 00:48"    71.333333 "2015-09-25 00:49"    64.571429 "2015-09-25 00:50"    72.285714"""  df = pd.read_table(io.StringIO(data), delim_whitespace=True)  # Converting the index as date df.index = pd.to_datetime(df.index)  # Extracting hour & minute df['A'] = df.index.hour df['B'] = df.index.minute df  #                          value  A   B # 2015-09-25 00:46:00  71.925000  0  46 # 2015-09-25 00:47:00  71.625000  0  47 # 2015-09-25 00:48:00  71.333333  0  48 # 2015-09-25 00:49:00  64.571429  0  49 # 2015-09-25 00:50:00  72.285714  0  50 

Answer 2

You could explicitly create a DatetimeIndex when initializing the dataframe. Assuming your data is in string format

data = [     ('2015-09-25 00:46', '71.925000'),     ('2015-09-25 00:47', '71.625000'),     ('2015-09-25 00:48', '71.333333'),     ('2015-09-25 00:49', '64.571429'),     ('2015-09-25 00:50', '72.285714'), ]  index, values = zip(*data)  frame = pd.DataFrame({     'values': values }, index=pd.DatetimeIndex(index))  print(frame.index.minute)