python pandas convert index to datetime

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)

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

I just give other option for this question - you need to use '.dt' in your code:

import pandas as pd

df.index = pd.to_datetime(df.index)

#for get year
df.index.dt.year

#for get month
df.index.dt.month

#for get day
df.index.dt.day

#for get hour
df.index.dt.hour

#for get minute
df.index.dt.minute