merging two dataframe using datetime index

Question

I have two data frames as blows (df5 and dfS), saving air pollution data. Their index is DateTime, as can been seen. In the DateTime index, the second reading is different. So I want to merge them when a date, hour and Minutes of their reading is the same and ignore the second. df5:

dfS:

Below is my code:

dfG=df5.merge(dfS,left_on='Min', right_on='Min' )
dfG['DATETIME'] = dfG.Date + "_" + dfG.Time
dfG.to_csv('dfG.csv')
dfG.set_index("DATETIME", inplace=True)
#correct the underscores in old datetime format
dfG.index = [" ".join(str(val).split("_")) for val in dfG.index]

as it can be seen the index is not correct because I considered 'Min' as key for joining.

DfG:

My question is: How to merge these two data frames based on DateTime index ignoring the second.

split seconds from there and merge it without seconds.

kağan hazal koçdemir
– kağan hazal koçdemir

2021-10-10 07:58:52 +00:00
Commented Oct 10, 2021 at 7:58 — kağan hazal koçdemir
– kağan hazal koçdemir, Commented Oct 10, 2021 at 7:58

merchmallow · Accepted Answer · 2021-10-10 08:02:00Z

1

if the seconds on your timestamp is not important , maybe this can help:

df5.index = df5.index.map(lambda x: x.replace(second=0))

answered Oct 10, 2021 at 8:02

merchmallow

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