Overview

Dataset statistics

Number of variables4
Number of observations657
Missing cells445
Missing cells (%)16.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.7 KiB
Average record size in memory32.2 B

Variable types

Categorical1
Text3

Dataset

Description인천광역시 교통행정종합관리시스템 시스템 관련 코드 데이터로 (상세코드, 상세코드명1, 상세코드명2)로 구성되어 있습니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15049214&srcSe=7661IVAWM27C61E190

Alerts

상세코드명2 has 445 (67.7%) missing valuesMissing

Reproduction

Analysis started2024-01-28 09:42:53.176100
Analysis finished2024-01-28 09:42:53.591813
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

마스터코드
Categorical

Distinct47
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
TFA005
47 
COM021
 
44
TFA028
 
44
TFA022
 
44
TFA023
 
38
Other values (42)
440 

Length

Max length6
Median length6
Mean length5.9939117
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTFA026
2nd rowTFA006
3rd rowCOM015
4th rowCOM015
5th rowTFA005

Common Values

ValueCountFrequency (%)
TFA005 47
 
7.2%
COM021 44
 
6.7%
TFA028 44
 
6.7%
TFA022 44
 
6.7%
TFA023 38
 
5.8%
TFA031 30
 
4.6%
TFA006 28
 
4.3%
COM027 21
 
3.2%
NIS002 20
 
3.0%
TFA024 20
 
3.0%
Other values (37) 321
48.9%

Length

2024-01-28T18:42:53.647277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tfa005 47
 
7.2%
tfa022 44
 
6.7%
com021 44
 
6.7%
tfa028 44
 
6.7%
tfa023 38
 
5.8%
tfa031 30
 
4.6%
tfa006 28
 
4.3%
com027 21
 
3.2%
nis002 20
 
3.0%
tfa024 20
 
3.0%
Other values (37) 321
48.9%

상세코드
Text

Distinct202
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-01-28T18:42:53.894539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length2.1933029
Min length1

Characters and Unicode

Total characters1441
Distinct characters39
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)18.1%

Sample

1st row5
2nd row21
3rd row1
4th row2
5th row1
ValueCountFrequency (%)
2 24
 
3.7%
1 23
 
3.5%
5 22
 
3.3%
3 20
 
3.0%
4 20
 
3.0%
6 20
 
3.0%
11 17
 
2.6%
12 16
 
2.4%
7 16
 
2.4%
8 14
 
2.1%
Other values (192) 465
70.8%
2024-01-28T18:42:54.259862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 277
19.2%
1 235
16.3%
2 218
15.1%
3 131
9.1%
5 108
 
7.5%
4 95
 
6.6%
9 88
 
6.1%
6 81
 
5.6%
8 80
 
5.6%
7 61
 
4.2%
Other values (29) 67
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1374
95.4%
Uppercase Letter 55
 
3.8%
Other Letter 8
 
0.6%
Connector Punctuation 4
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 8
14.5%
C 5
 
9.1%
F 4
 
7.3%
P 3
 
5.5%
N 3
 
5.5%
I 3
 
5.5%
T 3
 
5.5%
B 3
 
5.5%
V 3
 
5.5%
M 3
 
5.5%
Other values (10) 17
30.9%
Decimal Number
ValueCountFrequency (%)
0 277
20.2%
1 235
17.1%
2 218
15.9%
3 131
9.5%
5 108
 
7.9%
4 95
 
6.9%
9 88
 
6.4%
6 81
 
5.9%
8 80
 
5.8%
7 61
 
4.4%
Other Letter
ValueCountFrequency (%)
체 1
12.5%
코 1
12.5%
분 1
12.5%
구 1
12.5%
자 1
12.5%
단 1
12.5%
치 1
12.5%
드 1
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1378
95.6%
Latin 55
 
3.8%
Hangul 8
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 8
14.5%
C 5
 
9.1%
F 4
 
7.3%
P 3
 
5.5%
N 3
 
5.5%
I 3
 
5.5%
T 3
 
5.5%
B 3
 
5.5%
V 3
 
5.5%
M 3
 
5.5%
Other values (10) 17
30.9%
Common
ValueCountFrequency (%)
0 277
20.1%
1 235
17.1%
2 218
15.8%
3 131
9.5%
5 108
 
7.8%
4 95
 
6.9%
9 88
 
6.4%
6 81
 
5.9%
8 80
 
5.8%
7 61
 
4.4%
Hangul
ValueCountFrequency (%)
체 1
12.5%
코 1
12.5%
분 1
12.5%
구 1
12.5%
자 1
12.5%
단 1
12.5%
치 1
12.5%
드 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1433
99.4%
Hangul 8
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 277
19.3%
1 235
16.4%
2 218
15.2%
3 131
9.1%
5 108
 
7.5%
4 95
 
6.6%
9 88
 
6.1%
6 81
 
5.7%
8 80
 
5.6%
7 61
 
4.3%
Other values (21) 59
 
4.1%
Hangul
ValueCountFrequency (%)
체 1
12.5%
코 1
12.5%
분 1
12.5%
구 1
12.5%
자 1
12.5%
단 1
12.5%
치 1
12.5%
드 1
12.5%

상세코드명1
Text

Distinct500
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-01-28T18:42:54.476329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length25
Mean length6.8980213
Min length1

Characters and Unicode

Total characters4532
Distinct characters372
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique416 ?
Unique (%)63.3%

Sample

1st row의견진술가결
2nd row36인승이상승합
3rd rowFORM
4th rowJSP
5th row횡단보도
ValueCountFrequency (%)
인천광역시 28
 
3.4%
기타 14
 
1.7%
9 12
 
1.5%
총무과 12
 
1.5%
세무과 12
 
1.5%
과오납 11
 
1.4%
교통행정과 10
 
1.2%
부과취소 6
 
0.7%
수납(이중수납포함 5
 
0.6%
완납 5
 
0.6%
Other values (545) 699
85.9%
2024-01-28T18:42:54.831229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
161
 
3.6%
과 125
 
2.8%
납 111
 
2.4%
수 104
 
2.3%
( 92
 
2.0%
) 92
 
2.0%
인 67
 
1.5%
이 62
 
1.4%
소 61
 
1.3%
차 61
 
1.3%
Other values (362) 3596
79.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3399
75.0%
Uppercase Letter 278
 
6.1%
Lowercase Letter 241
 
5.3%
Decimal Number 213
 
4.7%
Space Separator 161
 
3.6%
Open Punctuation 92
 
2.0%
Close Punctuation 92
 
2.0%
Other Punctuation 41
 
0.9%
Dash Punctuation 8
 
0.2%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 125
 
3.7%
납 111
 
3.3%
수 104
 
3.1%
인 67
 
2.0%
이 62
 
1.8%
소 61
 
1.8%
차 61
 
1.8%
자 61
 
1.8%
부 59
 
1.7%
시 56
 
1.6%
Other values (290) 2632
77.4%
Uppercase Letter
ValueCountFrequency (%)
B 28
 
10.1%
D 23
 
8.3%
C 21
 
7.6%
T 16
 
5.8%
E 15
 
5.4%
F 14
 
5.0%
X 13
 
4.7%
P 13
 
4.7%
Y 11
 
4.0%
L 11
 
4.0%
Other values (16) 113
40.6%
Lowercase Letter
ValueCountFrequency (%)
e 27
 
11.2%
w 14
 
5.8%
y 11
 
4.6%
k 11
 
4.6%
g 11
 
4.6%
r 11
 
4.6%
t 10
 
4.1%
f 10
 
4.1%
i 10
 
4.1%
q 9
 
3.7%
Other values (16) 117
48.5%
Decimal Number
ValueCountFrequency (%)
2 43
20.2%
3 31
14.6%
1 30
14.1%
9 28
13.1%
4 22
10.3%
5 16
 
7.5%
0 15
 
7.0%
6 13
 
6.1%
7 8
 
3.8%
8 7
 
3.3%
Other Punctuation
ValueCountFrequency (%)
% 30
73.2%
, 9
 
22.0%
/ 2
 
4.9%
Math Symbol
ValueCountFrequency (%)
> 2
50.0%
< 2
50.0%
Space Separator
ValueCountFrequency (%)
161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3399
75.0%
Common 614
 
13.5%
Latin 519
 
11.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 125
 
3.7%
납 111
 
3.3%
수 104
 
3.1%
인 67
 
2.0%
이 62
 
1.8%
소 61
 
1.8%
차 61
 
1.8%
자 61
 
1.8%
부 59
 
1.7%
시 56
 
1.6%
Other values (290) 2632
77.4%
Latin
ValueCountFrequency (%)
B 28
 
5.4%
e 27
 
5.2%
D 23
 
4.4%
C 21
 
4.0%
T 16
 
3.1%
E 15
 
2.9%
F 14
 
2.7%
w 14
 
2.7%
X 13
 
2.5%
P 13
 
2.5%
Other values (42) 335
64.5%
Common
ValueCountFrequency (%)
161
26.2%
( 92
15.0%
) 92
15.0%
2 43
 
7.0%
3 31
 
5.0%
% 30
 
4.9%
1 30
 
4.9%
9 28
 
4.6%
4 22
 
3.6%
5 16
 
2.6%
Other values (10) 69
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3399
75.0%
ASCII 1133
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
161
 
14.2%
( 92
 
8.1%
) 92
 
8.1%
2 43
 
3.8%
3 31
 
2.7%
% 30
 
2.6%
1 30
 
2.6%
B 28
 
2.5%
9 28
 
2.5%
e 27
 
2.4%
Other values (62) 571
50.4%
Hangul
ValueCountFrequency (%)
과 125
 
3.7%
납 111
 
3.3%
수 104
 
3.1%
인 67
 
2.0%
이 62
 
1.8%
소 61
 
1.8%
차 61
 
1.8%
자 61
 
1.8%
부 59
 
1.7%
시 56
 
1.6%
Other values (290) 2632
77.4%

상세코드명2
Text

MISSING 

Distinct84
Distinct (%)39.6%
Missing445
Missing (%)67.7%
Memory size5.3 KiB
2024-01-28T18:42:55.128183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length5.5518868
Min length1

Characters and Unicode

Total characters1177
Distinct characters158
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)27.4%

Sample

1st row2
2nd row0
3rd row20091111
4th row20091111
5th row20091111
ValueCountFrequency (%)
cr 28
 
10.7%
dr 16
 
6.1%
기타사유 10
 
3.8%
인천광역시 10
 
3.8%
20091111 10
 
3.8%
0 6
 
2.3%
300010 5
 
1.9%
300003 5
 
1.9%
300006 5
 
1.9%
300002 5
 
1.9%
Other values (97) 161
61.7%
2024-01-28T18:42:55.573969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 348
29.6%
3 79
 
6.7%
1 77
 
6.5%
49
 
4.2%
R 44
 
3.7%
2 32
 
2.7%
C 28
 
2.4%
9 24
 
2.0%
시 18
 
1.5%
D 17
 
1.4%
Other values (148) 461
39.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 626
53.2%
Other Letter 398
33.8%
Uppercase Letter 93
 
7.9%
Space Separator 49
 
4.2%
Dash Punctuation 4
 
0.3%
Other Punctuation 3
 
0.3%
Math Symbol 2
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 18
 
4.5%
기 14
 
3.5%
타 13
 
3.3%
통 12
 
3.0%
과 12
 
3.0%
사 12
 
3.0%
교 11
 
2.8%
유 10
 
2.5%
인 10
 
2.5%
천 10
 
2.5%
Other values (125) 276
69.3%
Decimal Number
ValueCountFrequency (%)
0 348
55.6%
3 79
 
12.6%
1 77
 
12.3%
2 32
 
5.1%
9 24
 
3.8%
6 15
 
2.4%
7 15
 
2.4%
4 15
 
2.4%
5 14
 
2.2%
8 7
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
R 44
47.3%
C 28
30.1%
D 17
 
18.3%
E 2
 
2.2%
A 1
 
1.1%
P 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 686
58.3%
Hangul 398
33.8%
Latin 93
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 18
 
4.5%
기 14
 
3.5%
타 13
 
3.3%
통 12
 
3.0%
과 12
 
3.0%
사 12
 
3.0%
교 11
 
2.8%
유 10
 
2.5%
인 10
 
2.5%
천 10
 
2.5%
Other values (125) 276
69.3%
Common
ValueCountFrequency (%)
0 348
50.7%
3 79
 
11.5%
1 77
 
11.2%
49
 
7.1%
2 32
 
4.7%
9 24
 
3.5%
6 15
 
2.2%
7 15
 
2.2%
4 15
 
2.2%
5 14
 
2.0%
Other values (7) 18
 
2.6%
Latin
ValueCountFrequency (%)
R 44
47.3%
C 28
30.1%
D 17
 
18.3%
E 2
 
2.2%
A 1
 
1.1%
P 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 779
66.2%
Hangul 398
33.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 348
44.7%
3 79
 
10.1%
1 77
 
9.9%
49
 
6.3%
R 44
 
5.6%
2 32
 
4.1%
C 28
 
3.6%
9 24
 
3.1%
D 17
 
2.2%
6 15
 
1.9%
Other values (13) 66
 
8.5%
Hangul
ValueCountFrequency (%)
시 18
 
4.5%
기 14
 
3.5%
타 13
 
3.3%
통 12
 
3.0%
과 12
 
3.0%
사 12
 
3.0%
교 11
 
2.8%
유 10
 
2.5%
인 10
 
2.5%
천 10
 
2.5%
Other values (125) 276
69.3%

Correlations

2024-01-28T18:42:55.683594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
마스터코드상세코드명2
마스터코드1.0000.991
상세코드명20.9911.000

Missing values

2024-01-28T18:42:53.498486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:42:53.565506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

마스터코드상세코드상세코드명1상세코드명2
0TFA0265의견진술가결<NA>
1TFA0062136인승이상승합<NA>
2COM0151FORM<NA>
3COM0152JSP<NA>
4TFA0051횡단보도<NA>
5TFA0052보도주차<NA>
6TFA0053모퉁이<NA>
7TFA0054버스정류장<NA>
8TFA0055이중주차<NA>
9TFA0056소화전<NA>
마스터코드상세코드상세코드명1상세코드명2
647TFA00540적색노면표시 소화전<NA>
648COM000S안전신문고(24시)<NA>
649TFA0038이륜차40000
650TFA02512상호금융압류<NA>
651TFA02513증권압류<NA>
652TFA03113분납대상자<NA>
653TFA037W소화전<NA>
654TFA03628000신한은행1.00E+11
655TFA03628260신한은행1.00E+11
656NDG00128245W%2BBIWe%2BULr1WSKTZEbYotxptG7Sks4ktjlWedke6YBufwokVyHMxPe9wq4Ys0%2BX%2BBDrDFSkcQpyCE1qbihEjIA%3D%3D<NA>