合并/加入Pandas数据框

Question

I have two data frames, the first on is from a scooter renting company in an island it includes data about the scooter type, duration, starting and ending time and many others fields, the second one includes meteorological data from this island.

Because the meteorological data for each day have 8 records/measures every 3 hours (eg at 01.00am , at 04:00am till 22:00pm) I transformed/cut the starting time in the first data frame to 8 bins in order to combine for each record the corresponding weather conditions.

how can I combine these two frames in order for each rent to have the corresponding weather conditions?

Suppose that I have the fields df1.rent_id, df1.rent_day, df1.starting hour(from 1 to 8) and df2.day, df2.hour(from 1 to 8), df2.temp and so on

How can combine/join these two dataframe to get what I want?

As it sees, each record in the second data frame have many records in the first but each record in the first data frame relates to only one record to the second.

I have confused with the join types (inner, outer, left, right) what I need?

Thanks

Answer 1

First you need to set a reference column to sort the merged dataframe eg you can use starting time for df1 and time for df2

df1['reference_time']=df1['starting time']
df2['reference_time']=df2.['time']

Then set index and join them according to the order of reference time

df1.set_index('reference time').join(df2.set_index('reference_time'))

as for join mode option, you can have a look at the documentation here

how : {'left', 'right', 'outer', 'inner'}, default 'left' How to handle the operation of the two objects.

left: use calling frame's index (or column if on is specified) right: use other's index. outer: form union of calling frame's index (or column if on is specified) with other's index, and sort it. lexicographically. inner: form intersection of calling frame's index (or column if on is specified) with other's index, preserving the order of the calling's one.

The default mode is left