Python Pandas-使用第一数据从第二数据框中获取位置

Question

Very basic user of Pandas but I am coming against a brick wall here.

So I have one dataframe called dg has a column called 'user_id', and two other columns which aren't needed at the moment. I also have two more dataframes(data_conv and data_retargeting) with includes the same column name and a column called 'timestamp' in it however there is multiple timestamps for each 'user_id'.

What I need to create new columns in dg for the minimum and maximum 'timestamp' found.

I am currently able to do this through some very long-winded method with iterrow rows however for a dataframe of ~16000, it took 45minutes and I would like to cut it down because I have larger dataframes to run this one.

  for index,row in dg.iterrows(): user_id=row['pdp_id'] n_audft=data_retargeting[data_retargeting.pdp_id == user_id].index.min() n_audlt=data_retargeting[data_retargeting.pdp_id == user_id].index.max() n_convft=data_conv[data_conv.pdp_id == user_id].index.min() n_convlt=data_conv[data_conv.pdp_id == user_id].index.max() dg[index,'first_retargeting']=data_retargeting.loc[n_audft, 'raw_time'] dg[index,'last_retargeting']=data_retargeting.loc[n_audlt, 'raw_time'] dg[index,'first_conversion']=data_conv.loc[n_convft, 'raw_time'] dg[index,'last_conversion']=data_conv.loc[n_convlt, 'raw_time'] 

Answer 1

without going into specific code, is every user_id in dg found in data_conv and data_retargeting? if so, you can merge ( http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.merge.html ) them into a new dataframe first, and then compute the max/min, and extract the desired columns. i suspect that might run a little bit faster.