添加新列，根据多个条件进行分类

Question

I have a DataFrame (df) and i'm trying to assing Classes DataFrames A, B and, C to the first one in order to create a new column with the name Str2. The df actually has 1 million rows. What is the most efficient way to merge them considering the classes and the stratus? I´ve being trying with the if function, but i couldn´t do it.

df = pd.DataFrame(data={'Class': ["A", "B", "C", "A", "B", "C", "A", "B", "C"], 'Stra': [1,1,1,2,2,2,3,3,3], 'Energy':[41,3,22,21,32,2,23,2,6]})

df

  Class Stra    Energy
0   A   1       41
1   B   1       3
2   C   1       22
3   A   2       21
4   B   2       32
5   C   2       2
6   A   3       23
7   B   3       2
8   C   3       6

Classes DataFrames:

A = pd.DataFrame(data={'Stra': [1,2,3], 'Str2':["INT1","INT2","INT2"]})

B = pd.DataFrame(data={'Stra': [1,2,3], 'Str2':["INT1","INT3","INT4"]})

C = pd.DataFrame(data={'Stra': [1,2,3], 'Str2':["INT2","INT5","INT6"]})

Then, the expected result is something like this:

   Class      Stra  Energy  Str2
0   A          1    41      INT1
1   B          1    3       INT1
2   C          1    22      INT2
3   A          2    21      INT2
4   B          2    32      INT3
5   C          2    2       INT5
6   A          3    23      INT2
7   B          3    2       INT4
8   C          3    6       INT6

Answer 1

Try the Below code snippet,

df = pd.DataFrame(data={'Class': ["A", "B", "C", "A", "B", "C", "A", "B", "C"], 'Stra': [1,1,1,2,2,2,3,3,3], 'Energy':[41,3,22,21,32,2,23,2,6]})

A = pd.DataFrame(data={'Stra': [1,2,3], 'Str2':["INT1","INT2","INT2"]})

B = pd.DataFrame(data={'Stra': [1,2,3], 'Str2':["INT1","INT3","INT4"]})

C = pd.DataFrame(data={'Stra': [1,2,3], 'Str2':["INT2","INT5","INT6"]})


# Store the Classes Dataframes in class object

class Vars:
    pass

setattr(Vars,"A",A)
setattr(Vars,"B",B)
setattr(Vars,"C",C)

# Write a function to return the Str2 value

def ret_str2(val,val2):
    df = getattr(Vars,val)
    str2 = df[df['Stra']==val2]['Str2'].values[0]
    return str2

# Apply ret_str2 function in df

df["Str2"] = df[["Class","Stra"]].apply(lambda x : ret_str2(x["Class"],x["Stra"]),axis=1)

print(df)

    Class   Stra    Energy  Str2
0   A       1       41      INT1
1   B       1       3       INT1
2   C       1       22      INT2
3   A       2       21      INT2
4   B       2       32      INT3
5   C       2       2       INT5
6   A       3       23      INT2
7   B       3       2       INT4
8   C       3       6       INT6