# Python Pandas <pandas.core.groupby.DataFrameGroupBy对象在...>。[英] Python Pandas ＜pandas.core.groupby.DataFrameGroupBy object at ...＞

### 问题描述

```#Functions

def postal_saude ():
global df, lista_solic

#List of solicitantes in Postal Saude
list_sol = [lista_solic["name1"], lista_solic["name2"]]

#filter Postal Saude Solicitantes
df = df[(df['Cliente']==lista_clientes["6"])
& (df['Nome do solicitante'].isin(list_sol))]

#Alphabetical order
df = df.sort_index(by=['Nome do solicitante', 'nomeCorrespondente'])

#Grouping data of column
grouping = df.groupby('Tipo do serviços');

print (grouping)

postal_saude()
```

## 推荐答案

```df = pd.DataFrame({'a':[1,1,1,2,2,2,3,3,3,3],'b':np.random.randn(10)})

df
a         b
0  1  1.048099
1  1 -0.830804
2  1  1.007282
3  2 -0.470914
4  2  1.948448
5  2 -0.144317
6  3 -0.645503
7  3 -1.694219
8  3  0.375280
9  3 -0.065624

groups = df.groupby('a')

groups # Tells you what "df.groupby('a')" is, not an error
<pandas.core.groupby.DataFrameGroupBy object at 0x00000000097EEB38>

groups.count() # count the number of 1 present in the 'a' column
b
a
1  3
2  3
3  4

groups.sum() # sums the 'b' column values based on 'a' grouping

b
a
1  1.224577
2  1.333217
3 -2.030066
```

```df_count = groups.count()

df_count
b
a
1  3
2  3
3  4

type(df_count) # assigning the `.count()` output to a variable create a new df
pandas.core.frame.DataFrame
```

### 问题描述

I am trying to group and count the same info in a row:

```#Functions

def postal_saude ():
global df, lista_solic

#List of solicitantes in Postal Saude
list_sol = [lista_solic["name1"], lista_solic["name2"]]

#filter Postal Saude Solicitantes
df = df[(df['Cliente']==lista_clientes["6"])
& (df['Nome do solicitante'].isin(list_sol))]

#Alphabetical order
df = df.sort_index(by=['Nome do solicitante', 'nomeCorrespondente'])

#Grouping data of column
grouping = df.groupby('Tipo do serviços');

print (grouping)

postal_saude()
```

When it gets to the df.groupby it raises an error

I have tried searching this same error but I have not found a valid answer to help me fix my problem.

## 推荐答案

Take a look at this documentation about Group By

Group series using mapper (dict or key function, apply given function to group, return result as series) or by a series of columns

The previous is taken from here

Here's a quick example:

```df = pd.DataFrame({'a':[1,1,1,2,2,2,3,3,3,3],'b':np.random.randn(10)})

df
a         b
0  1  1.048099
1  1 -0.830804
2  1  1.007282
3  2 -0.470914
4  2  1.948448
5  2 -0.144317
6  3 -0.645503
7  3 -1.694219
8  3  0.375280
9  3 -0.065624

groups = df.groupby('a')

groups # Tells you what "df.groupby('a')" is, not an error
<pandas.core.groupby.DataFrameGroupBy object at 0x00000000097EEB38>

groups.count() # count the number of 1 present in the 'a' column
b
a
1  3
2  3
3  4

groups.sum() # sums the 'b' column values based on 'a' grouping

b
a
1  1.224577
2  1.333217
3 -2.030066
```

You get the idea, you can build from here using the first link I provided.

```df_count = groups.count()

df_count
b
a
1  3
2  3
3  4

type(df_count) # assigning the `.count()` output to a variable create a new df
pandas.core.frame.DataFrame
```