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Merge 2 dataframe on index with different timestamp in python pandas

Time:10-19

I have 2 dataframes with different timestamps and different lengths.

First Dataframe,df, has 1054 rows and looks like this:

First Dataframe

Second Dataframe,df_temp, has 2629 rows and looks like this:

Second Dataframe

I have no clue where to begin. The time stamp is almost close and I know how to merge dataframes with similar index but not this one. Any help would be appreciated. Thank you!

df_merged=pd.concat([df,df_temp]).sort_index()

I tried this before as well. When I add these together the index is kind of sorted but it gives me NaN values for where the data is missing.

CodePudding user response:

Can you try this ?

pd.concat([df,df_temp]).sort_index()

or

pd.concat([df,df_temp.rename(columns=dict(zip(df_temp.columns,df.columns)))]).sort_index()
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