我怎样才能在空场统计数据帧

Question

我有一个数据帧：

| city | field2 | field3 | field4 | field5 | 
| 1 | a |  | b | b | 
| 2 |  |  | c |  | 
| 3 |  | a |  |  | 
| 4 | a |  |  |  | 
| 1 |  | a |  | b | 
| 2 | b |  | c |  | 
| 4 |  | a |  |  | 
| 3 |  |  | a |  | 
| 2 | b |  |  |  | 
| 1 |  | a |  | b | 
| 2 |  |  | a |  | 
| 3 | a |  |  | b | 
| 1 |  |  | b |  | 
| 1 | b | a |  |  | 
| 2 |  |  | b | b | 
| 1 | b | a |  | b | 

我需要在这里是统计上的场“城市”群空白字段的列表。

| city | field2 | field3 | field4 | field5 | 
| 1 | 3 | 2 | 4 | 2 | 
| 2 | 3 | 5 | 1 | 4 | 
| 3 | 2 | 2 | 2 | 2 | 
| 4 | 1 | 1 | 2 | 2 | 

我该如何用python熊猫做到这一点？

Answer 1

import pandas as pd 
import numpy as np 

df = pd.DataFrame({ 
    "city": [1,2,1,2,1,2], 
    "field2": [np.nan, "a", np.nan, np.nan, "b", np.nan], 
    "field3": [np.nan, np.nan, np.nan, "b", "a", "b"], 
    }) 
df 

这是我的示例数据：

city field2 field3 
0 1 NaN NaN 
1 2 a NaN 
2 1 NaN NaN 
3 2 NaN b 
4 1 b a 
5 2 NaN b 

现在的逻辑：

# define a function that counts the number of `nan` in a series. 
def count_nan(col): 
    return col.isnull().sum() 

# group by city and count the number of `nan` per city 
df.groupby("city").agg({"field2": count_nan, "field3": count_nan}) 

这是输出：

field2 field3 
city   
1 2 2 
2 2 1