The DF looks something like this and extends for thousands of rows (i.e every combination of 'Type' & 'Name' possible)
| total | big | med | small| Type | Name |
|:-----:|:-----:|:-----:|:----:|:--------:|:--------:|
| 5 | 4 | 0 | 1 | Pig | John |
| 6 | 0 | 3 | 3 | Horse | Mike |
| 5 | 2 | 3 | 0 | Cow | Rick |
| 5 | 2 | 3 | 0 | Horse | Rick |
| 5 | 2 | 3 | 0 | Cow | John |
| 5 | 2 | 3 | 0 | Pig | Mike |
I have grouped the dataframe by 'Type' and 'Name'.
| total | big | med | small| Type | Name |
|:-----:|:-----:|:-----:|:----:|:--------:|:--------:|
| 5 | 4 | 0 | 1 | Pig | John |
| 6 | 0 | 3 | 3 | Pig | John |
| 5 | 2 | 3 | 0 | Pig | John |
| 5 | 2 | 3 | 0 | Pig | John |
Then run functions on each grouped dataframe respectively.
for idx, df in data.groupby(['Type', 'Name']):
function_1(df)
function_2(df)
with pd.ExcelWriter(f"{'_'.join(idx)}.xlsx") as writer:
table_1.to_excel(writer, sheet_name='Table 1', index=False)
table_2.to_excel(writer, sheet_name='Table 2', index=False)
The resulting file name comes out:
"Pig_John.xlsx"
I'd like to add aliases to replace each 'Type' and 'Name' respectively as seen below.
Aliases:
Pig = Type1
Horse = Type2
Cow = Type3
John = Name1
Mike = Name2
Rick = Name3
Example Result:
Pig_John.xlsx = Type1_Name1.xlsx
Horse_Rick.xlsx = Type2_Name3.xlsx
You can create a dictionary, and then call the keys and values of the dictionary, creating a new idx with each loop with idx = (dct[idx[0]], dct[idx[1]]):
dct = {'Pig' : 'Type1',
'Horse' : 'Type2',
'Cow' : 'Type3',
'John' : 'Name1',
'Mike' : 'Name2',
'Rick' : 'Name3'}
df=d.copy()
for idx, d in df.groupby(['Type', 'Name']):
idx = (dct[idx[0]], dct[idx[1]])
print(f"{'_'.join(idx)}.xlsx")
Out[1]:
Type3_Name1.xlsx
Type3_Name3.xlsx
Type2_Name2.xlsx
Type2_Name3.xlsx
Type1_Name1.xlsx
Type1_Name2.xlsx