使用 pandas 将列从较小的数据帧复制（组装）到较大的数据帧中

Question

I have a data frame with measurements for several groups of participants, and I am doing some calculations for each group. I want to add a column in a big data frame (all participants), from secondary data frames (partial list of participants).

When I do merge a couple of times (merging a new data frame to the existing one), it creates a duplicate of the column instead of one column.

As the size of the dataframes is different I can not compare them directly.

I tried

    #df1 - main bigger dataframe,  df2 - smaller dataset contains group of df1
    
    
    for i in range(len(df1)):
    # checking indeces to place the data to correct participant:
        if df1.index[i] not in df2['index']: 
            pass
        else :
            df1['rate'][i] = list(df2[rate][df2['index']==i]) 
    

It does not work properly though. Can you please help with the correct way of assembling the column? update: where the index of the initial dataframe and the "index" column of the calculation is the same, copy the rate value from the calculation into main df

main dataframe 1df

index	rate
1	0
2	0
3	0
4	0
5	0
6	0

dataframe with calculated values

index	rate
1	value
4	value
6	value

output df

index	rate
1	value
2	0
3	0
4	value
5	0
6	value

Answer 1

Try this – using .join() to merge dataframes on their indices and combining two columns using .combine_first() :

df = df1.join(df2, lsuffix="_df1", rsuffix="_df2")
df["rate"] = df["rate_df2"].combine_first(df["rate_df1"])

EDIT:

This assumes both dataframes use a matching index. If that is not the case for df2 , run this first:

df2 = df2.set_index('index')