How to loop through all values on two tables?-CodePudding

Would you do me a favor on how to do the expected result?

Initial Table A:

Name	Score
Ken	500
John	600
Keith	700

Initial Table B:

Period
202201
202202
202203

My expected table is below

Name	Period	Score
Ken	202201	500
Ken	202202	500
Ken	202203	500
John	202201	600
John	202202	600
John	202203	600
Keith	202201	700
Keith	202202	700
Keith	202203	700

I believe the above questions should be answered before, but i have no idea on how to type my requirements in google. I have spent several hours on searching for it, but still dont know how to do.

Would someone help me on above?

Thanks!

CodePudding user response：

Here's a way to do it:

import pandas as pd
df_score = pd.DataFrame({'Name':['Ken', 'John', 'Keith'], 'Score':[500, 600, 700]})
df_period = pd.DataFrame({'Period':[202201, 202202, 202203]})
print(df_score)
print(df_period)
df_score['Period'] = [list(df_period['Period']) for _ in range(df_score.shape[0])]
df = df_score.explode('Period', ignore_index=True)
print(df)

Output:

    Name  Score
0    Ken    500
1   John    600
2  Keith    700
   Period
0  202201
1  202202
2  202203
    Name  Score  Period
0    Ken    500  202201
1    Ken    500  202202
2    Ken    500  202203
3   John    600  202201
4   John    600  202202
5   John    600  202203
6  Keith    700  202201
7  Keith    700  202202
8  Keith    700  202203

CodePudding user response：

try this it`s like join in sql https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.merge.html

import pandas as pd

df1 = pd.DataFrame({'Name': ['foo', 'bar', 'baz', 'fooz'],

                    'Score': [1, 2, 3, 5]})

df2 = pd.DataFrame({'Period': [202201, 202202, 202203]})

print(df1.merge(df2, how='cross'))