Python 在pandas/numpy中，如何创建包含字符串项计数的数据透视表？

在python3和pandas中，我有以下数据帧：

df_selecao_atual.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 63 entries, 2 to 72
Data columns (total 24 columns):
nome                     63 non-null object
nome_completo            63 non-null object
partido                  63 non-null object
uf                       63 non-null object
cargo_parlamentar        63 non-null object
tipo                     63 non-null object
classe                   63 non-null object
numero                   63 non-null object
único                    63 non-null object
assunto                  63 non-null object
data_inicial             63 non-null object
data_final               63 non-null object
andamento                63 non-null object
link                     63 non-null object
transparencia            63 non-null object
conferencia              63 non-null object
data_conferencia         63 non-null object
resumo                   62 non-null object
observacao               60 non-null object
link_noticia_tribunal    22 non-null object
interessa                62 non-null object
ministro_relator         63 non-null object
processo_conectado       20 non-null object
situacao                 63 non-null object
dtypes: object(24)
memory usage: 12.3+ KB

但结果只计算“tipo”列中的行数

我期待这样的结果：

ARTHUR LIRA     
    INQ 9
    AP 1
BENEDITO DE LIRA
    INQ 3 
    AP 0
CÉSAR MESSIAS   
    INQ 1
    AP 1
...

也就是说，计算每个名称中存在多少类型“INQ”和“AP”

拜托，有人知道我怎么做吗

数据样本：

df_selecao_atual[['nome','tipo']]
nome    tipo
2   CÉSAR MESSIAS   INQ
3   CÉSAR MESSIAS   AP
4   FLAVIANO MELO   INQ
5   FLAVIANO MELO   INQ
6   FLAVIANO MELO   AP
7   FLAVIANO MELO   INQ
10  ROCHA   AP
13  SIBÁ MACHADO    INQ
14  GLADSON CAMELI  INQ
15  GLADSON CAMELI  INQ
16  GLADSON CAMELI  INQ
17  JORGE VIANA     INQ
18  JORGE VIANA     INQ
19  JORGE VIANA     INQ
20  JORGE VIANA     INQ
21  JORGE VIANA     INQ
22  SÉRGIO PETECÃO  INQ
23  SÉRGIO PETECÃO  INQ
...

您可以使用：

df_selecao_atual.pivot_table(index=['tipo','nome'],aggfunc='size')

或：

---

您能添加数据样本吗？非常感谢。可以点菜吗？通过名称'nome'@ReinaldoChaves-当然，只添加

。排序索引（级别=['nome']）

df_selecao_atual.pivot_table(index=['tipo','nome'],aggfunc='size')

df_selecao_atual.groupby(['tipo','nome']).size()