如何在pandas.DataFrame中插入满足条件的行值

Question

I'm starting to learn Python and I've run into the following problem: I'm trying to join two dataframes below so that there are multiple rows containing the same names and parameters but for the entire range of temperatures.

    import pandas as pd
    frame1 = pd.DataFrame({'names':['bb1', 'bb2', 'bb3', 'bb4', 'bb5'],
                  'parameter1':['1', '2', '3', '4', '5'],
                  'parameter2':['0.1', '0.2', '0.3', '0.4', '0.5']})
    frame2 = pd.DataFrame({'names':['bb1', 'bb2', 'bb3', 'bb4', 'bb5'],
                  'temperature':['300', '400', '500', '600', '700']})

The output should look something like this

        names  parameter1    parameter2    temperature
    0   bb1    1             0.1           300
    1   bb1    1             0.1           400
    ...
    5   bb2    2             0.2           300
    6   bb2    2             0.2           400
    ...

It feels like there should be built-in tools in pandas or itertools for that but I just can't figure it out.

I attempted using itertools.product:

    pd.DataFrame(list(itertools.product(parameters,temperature)))

but I can't think of a way to insert columns with parameters1 and parameters2 to match the entries in the names column. Help appreciated.

(edit) Fixed example frame1

Answer 1

You should first create a data frame that links every name to multiple temperatures and then merge it to frame1 using merge function.

import pandas as pd
from itertools import product
frame1 = pd.DataFrame({'names':['bb1', 'bb2', 'bb3', 'bb4', 'bb5'],
                  'parameter1':['1', '2', '3', '4', '5'],
                  'parameter2':['0.1', '0.2', '0.3', '0.4', '0.5']})
names = ['bb1', 'bb2', 'bb3', 'bb4', 'bb5']
temperatures = ['300', '400', '500', '600', '700']
frame2 = pd.DataFrame.from_records(list(product(names, temperatures)),
                                   columns=['names', 'temperatures'])
df = frame1.merge(frame2)

Answer 2

You can use pd.merge take inner join on 'names'.

>>> pd.merge(frame1, frame2, how='inner', on = 'names')


  names parameter1 parameter2 temperature
0   bb1          1        0.1         300
1   bb1          1        0.1         121
2   bb2          2        0.2         400
3   bb3          3        0.3         500
4   bb4          4        0.4         600
5   bb5          5        0.5         700