pandas iterrows() 跳过行

Question

我使用下面的代码来迭代我的数据框数据

输入：

dataframe1 = pandas.read_csv("bday.csv")
print (dataframe1)

输出：

nombre             email  mes  dia
0      A  [email protected]   11   29
1      B  [email protected]   11   28
2      C  [email protected]   12   15
3      D  [email protected]   12   11
4      E  [email protected]   12   15
5      F  [email protected]   11   13
6      G  [email protected]    9    7
7      H  [email protected]    1   30
8      I  [email protected]    4   19`

然后我使用 python 理解来生成字典

输入：

dict_bday = {(row["mes"],row["dia"]):row for index,row in dataframe1.iterrows()}

print(dict_bday)

输出：

{(11, 29): nombre                   A
    email     [email protected]
    mes                     11
    dia                     29
    Name: 0, dtype: object, (11, 28): nombre                   B
    email     [email protected]
    mes                     11
    dia                     28
    Name: 1, dtype: object, (12, 15): nombre                   E
    email     [email protected]
    mes                     12
    dia                     15
    Name: 4, dtype: object, (12, 11): nombre                   D
    email     [email protected]
    mes                     12
    dia                     11
    Name: 3, dtype: object, (11, 13): nombre                   F
    email     [email protected]
    mes                     11
    dia                     13
    Name: 5, dtype: object, (9, 7): nombre                   G
    email     [email protected]
    mes                      9
    dia                      7
    Name: 6, dtype: object, (1, 30): nombre                   H
    email     [email protected]
    mes                      1
    dia                     30
    Name: 7, dtype: object, (4, 19): nombre                   I
    email     [email protected]
    mes                      4
    dia                     19
    Name: 8, dtype: object}

生成的词典中信息显示不正确，并且部分索引也缺失。可能是什么问题？

Answer 1

尚不清楚您期望如何形成和显示词典，但这可能更接近您想要的：

dict_bday = {(row["mes"],row["dia"]): list(row.values) for index,row in dataframe1.iterrows()}
for entry in dict_bday.items():
    print(entry[0], entry[1])

给予

(11, '29') ['A', '[email protected]', 11, '29']
(11, '28') ['B', '[email protected]', 11, '28']
(12, '15') ['E', '[email protected]', 12, '15']
(12, '11') ['D', '[email protected]', 12, '11']
(11, '13') ['F', '[email protected]', 11, '13']
(9, '7') ['G', '[email protected]', 9, '7']
(1, '30') ['H', '[email protected]', 1, '30']
(4, '19`') ['I', '[email protected]', 4, '19`']