Changing time frequency in Pandas Dataframe

I have a Pandas DataFrame as below.

df
                              A           B
date_time                                    
2014-07-01 06:03:59.614000  62.1250       NaN
2014-07-01 06:03:59.692000  62.2500       NaN
2014-07-01 06:13:34.524000  62.2500  241.0625
2014-07-01 06:13:34.602000  62.2500  241.5000
2014-07-01 06:15:05.399000  62.2500  241.3750
2014-07-01 06:15:05.399000  62.2500  241.2500
2014-07-01 06:15:42.004000  62.2375  241.2500
2014-07-01 06:15:42.082000  62.2375  241.3750
2014-07-01 06:15:42.082000  62.2375  240.2500

I want to change the frequency of this to regular 1 minute intervals. But get the error below:

new = df.asfreq('1Min')
>>error: cannot reindex from a duplicate axis

Now, I understand why this is happening. Since my time granularity is high (in milliseconds) but irregular, I get multiple readings per minute, even per second. So I tried to combine these millisecond readings to minutes and get rid of duplicates as below.

# try to convert the index to minutes and drop duplicates
df['index'] = df.index
df['minute_index']= df['index'].apply( lambda x: x.strftime('%Y-%m-%d %H:%M'))
df.drop_duplicates(cols = 'minute_index', inplace = True, take_last = True)
df_by_minute = df.set_index('minute_index')
df_by_minute
                        A                B               index
minute_index                                                     
2014-07-01 06:03    62.2500        NaN 2014-07-01 06:03:59.692000
2014-07-01 06:13    62.2500     241.50 2014-07-01 06:13:34.602000
2014-07-01 06:15    62.2375     240.25 2014-07-01 06:15:42.082000

# now change the frequency to 1 minute but I just get NaNs (!)
df_by_minute.asfreq('1Min')
                            A          B   index
2014-07-01 06:03:00        NaN        NaN   NaT
2014-07-01 06:04:00        NaN        NaN   NaT
2014-07-01 06:05:00        NaN        NaN   NaT
2014-07-01 06:06:00        NaN        NaN   NaT
2014-07-01 06:07:00        NaN        NaN   NaT
2014-07-01 06:08:00        NaN        NaN   NaT
2014-07-01 06:09:00        NaN        NaN   NaT
2014-07-01 06:10:00        NaN        NaN   NaT
2014-07-01 06:11:00        NaN        NaN   NaT
2014-07-01 06:12:00        NaN        NaN   NaT
2014-07-01 06:13:00        NaN        NaN   NaT
2014-07-01 06:14:00        NaN        NaN   NaT
2014-07-01 06:15:00        NaN        NaN   NaT

As you see it does not work.. Can someone help? What I am trying to achieve is to get a function that returns A or B as of DateTime and DateTime would be in 1Min increments.


I think, not asfreq but resample fits your needs:

new = df.resample('T', how='mean')

For how option, you can also use 'last' or 'first'.

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