# MultiIndex.to_frame()

## Problem

From a MultiIndex dataframe, determine the total number of elements in the Buyer column for each Vendor.

## What I did

Let's say we have the following DataFrame:

:::python

```>> df = pd.DataFrame(data=
{'Vendor': ['A', 'A', 'B', 'C', 'C', 'C',
'D', 'D', 'E', 'E', 'F', 'G', 'G'],
'Buyer':['BU1', 'BU3', 'BU2', 'BU1', 'BU3', 'BU4',
'BU1', 'BU2', 'BU1', 'BU4', 'BU2', 'BU1', 'BU3'],
'Amount':[1, 5, 20, 103, 234, 13, 15,
23, 156, 60, 97, 23, 14]}
)

>> df
|     |   Vendor    |    Buyer     |  Amount |
|:---:|:-----------:|:------------:| -------:|
| 0   |      A      |     BU1      |      1  |
| 1   |      A      |     BU3      |      5  |
| 2   |      B      |     BU2      |     20  |
| 3   |      C      |     BU1      |    103  |
| 4   |      C      |     BU3      |    234  |
| 5   |      C      |     BU4      |     13  |
| 6   |      D      |     BU1      |     15  |
| 7   |      D      |     BU2      |     23  |
| 8   |      E      |     BU1      |    156  |
| 9   |      E      |     BU4      |     60  |
| 10  |      F      |     BU2      |     97  |
| 11  |      G      |     BU1      |     23  |
| 12  |      G      |     BU3      |     14  |
```

First, apply GroupBy and Aggregate by Vendor and Buyer:

:::python

```>> df_groupby_agg = df.groupby(
total_value=pd.NamedAgg(column='Amount', aggfunc=np.sum)
)
)

>> df_groupby_agg

|         |              | total_value  |
|:-------:|:------------:| ------------:|
| Vendor  |    Buyer     |              |
|:-------:|:------------:| ------------:|
| A       |    BU1       |        1     |
|         |    BU3       |        5     |
|:-------:|:------------:| ------------:|
| B       |    BU2       |       20     |
|:-------:|:------------:| ------------:|
| C       |    BU1       |      103     |
|         |    BU3       |      234     |
|         |    BU4       |       13     |
|:-------:|:------------:| ------------:|
| D       |    BU1       |       15     |
|         |    BU2       |       23     |
|:-------:|:------------:| ------------:|
| E       |    BU1       |      156     |
|         |    BU4       |       60     |
|:-------:|:------------:| ------------:|
| F       |    BU2       |       97     |
| G       |    BU1       |       23     |
|         |    BU3       |       14     |
```

Next, create a DataFrame with the levels of the MultiIndex as columns:

:::python

```>> df_multiindex = df_groupby_agg.index.to_frame(index=False)

>> df_multiindex

|     |   Vendor  |   Buyer  |
|:---:|:---------:|:--------:|
| 0   |       A   |    BU1   |
| 1   |       A   |    BU3   |
| 2   |       B   |    BU2   |
| 3   |       C   |    BU1   |
| 4   |       C   |    BU3   |
| 5   |       C   |    BU4   |
| 6   |       D   |    BU1   |
| 7   |       D   |    BU2   |
| 8   |       E   |    BU1   |
| 9   |       E   |    BU4   |
| 10  |       F   |    BU2   |
| 11  |       G   |    BU1   |
| 12  |       G   |    BU3   |
```

Lastly, use '.loc[]' and 'count()' to obtain Buyer count for each Vendor:

:::python

```>> df_multiindex.set_index('Vendor').loc['E'].count()

pd.DataFrame(data=...