[FIXED] pandas iterrows() skip rows

Issue

I am using this code below to iterate over my dataframe data

Input:

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

Output:

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`

then i use python comprehension for generate a dictionary

Input:

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

print(dict_bday)

Output:

{(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}

In the generated dictionary the information is not displayed correctly, and some indexes are also missing.What could be the problem?

Solution

It is not clear how you expect the Dictionary to be formed and displayed, but this might be nearer what you want:

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])

gives

(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`']

If you want to see all Entries including duplicates then don't use a Dictionary using mes dia as keys because repeated keys are not allowed. For example you could use:

df1 = dateframe1.set_index(['mes', 'dia'])

print(df1)

which gives:

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

Answered By - user19077881