Filter multiple dataframes with criteria from list using loop

You can reference a variable in a query by using @

df_dict[i]=dfsource.query('COL1==@x')

So the total code looks like this

import pandas as pd

report=['A','B','C']
suffix='_US'

report2=[s + suffix for s in report]
print (report2) #result: ['A_US', 'B_US', 'C_US']

source = {'COL1': ['A','B','C'], 'COL2': ['D','E','F']}
dfsource=pd.DataFrame(source)
print(dfsource)

df_dict = {}
for i in report2:
    df_dict[i]=pd.DataFrame()


    for x in report:
      df_dict[i]=dfsource.query('COL1==@x')
      #df_dict[i]=dfsource.query('COL1=="A"') #Example, this works filtering for value A but not what I need.

print(df_dict['A_US'])
print(df_dict['B_US'])
print(df_dict['C_US'])

which outputs

  COL1 COL2
0    A    D
1    B    E
2    C    F
  COL1 COL2
2    C    F
  COL1 COL2
2    C    F
  COL1 COL2
2    C    F

However, I think you want to create a new dictionary based on the i and x of each list, then you can move the creation of the dataframe to the second for loop and then create a new key for each iteration.

import pandas as pd

report=['A','B','C']
suffix='_US'

report2=[s + suffix for s in report]
print (report2) #result: ['A_US', 'B_US', 'C_US']

source = {'COL1': ['A','B','C'], 'COL2': ['D','E','F']}
dfsource=pd.DataFrame(source)
print(dfsource)

df_dict = {}
for i in report2:
    for x in report:
      new_key = x + i
      df_dict[new_key]=pd.DataFrame()
      df_dict[new_key]=dfsource.query('COL1==@x')

for item in df_dict.items():
    print(item)

Outputs 9 unique dataframes which are filtered based on whatever x value was passed.

('AA_US',   COL1 COL2
0    A    D)
('BA_US',   COL1 COL2
1    B    E)
('CA_US',   COL1 COL2
2    C    F)
('AB_US',   COL1 COL2
0    A    D)
('BB_US',   COL1 COL2
1    B    E)
('CB_US',   COL1 COL2
2    C    F)
('AC_US',   COL1 COL2
0    A    D)
('BC_US',   COL1 COL2
1    B    E)
('CC_US',   COL1 COL2
2    C    F)