Overview

Dataset statistics

Number of variables4
Number of observations99
Missing cells12
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory34.3 B

Variable types

Text3
Numeric1

Dataset

Description서울특별시 광진구 소재 직업소개소에 대한 데이터로 상호명, 주소, 연락처 등 광진구 직업소개사업소에 관한 내용을 제공하는 데이터입니다.
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15041528/fileData.do

Alerts

전화번호 has 12 (12.1%) missing valuesMissing
상호 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 08:35:04.359832
Analysis finished2024-03-14 08:35:05.542875
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size920.0 B
2024-03-14T17:35:06.232730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length7.1616162
Min length2

Characters and Unicode

Total characters709
Distinct characters191
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st row주식회사 비포유컨설팅
2nd row㈜아스트로스인터내셔널
3rd row㈜한울에이치엠
4th row피플뱅크코리아 주식회사
5th row㈜코니언정보
ValueCountFrequency (%)
주식회사 8
 
6.7%
비포유컨설팅 1
 
0.8%
주)해피케어 1
 
0.8%
파출부 1
 
0.8%
스타 1
 
0.8%
돌보미사업단 1
 
0.8%
부설 1
 
0.8%
아차산노인복지센터 1
 
0.8%
주)잡플러스 1
 
0.8%
미래건설인력 1
 
0.8%
Other values (102) 102
85.7%
2024-03-14T17:35:07.603111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 42
 
5.9%
력 33
 
4.7%
소 32
 
4.5%
주 21
 
3.0%
사 20
 
2.8%
20
 
2.8%
회 17
 
2.4%
개 17
 
2.4%
업 16
 
2.3%
) 15
 
2.1%
Other values (181) 476
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 652
92.0%
Space Separator 20
 
2.8%
Close Punctuation 15
 
2.1%
Open Punctuation 14
 
2.0%
Uppercase Letter 4
 
0.6%
Other Symbol 3
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 42
 
6.4%
력 33
 
5.1%
소 32
 
4.9%
주 21
 
3.2%
사 20
 
3.1%
회 17
 
2.6%
개 17
 
2.6%
업 16
 
2.5%
직 13
 
2.0%
리 13
 
2.0%
Other values (172) 428
65.6%
Uppercase Letter
ValueCountFrequency (%)
K 1
25.0%
P 1
25.0%
A 1
25.0%
R 1
25.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 655
92.4%
Common 50
 
7.1%
Latin 4
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 42
 
6.4%
력 33
 
5.0%
소 32
 
4.9%
주 21
 
3.2%
사 20
 
3.1%
회 17
 
2.6%
개 17
 
2.6%
업 16
 
2.4%
직 13
 
2.0%
리 13
 
2.0%
Other values (173) 431
65.8%
Common
ValueCountFrequency (%)
20
40.0%
) 15
30.0%
( 14
28.0%
& 1
 
2.0%
Latin
ValueCountFrequency (%)
K 1
25.0%
P 1
25.0%
A 1
25.0%
R 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 652
92.0%
ASCII 54
 
7.6%
None 3
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 42
 
6.4%
력 33
 
5.1%
소 32
 
4.9%
주 21
 
3.2%
사 20
 
3.1%
회 17
 
2.6%
개 17
 
2.6%
업 16
 
2.5%
직 13
 
2.0%
리 13
 
2.0%
Other values (172) 428
65.6%
ASCII
ValueCountFrequency (%)
20
37.0%
) 15
27.8%
( 14
25.9%
K 1
 
1.9%
P 1
 
1.9%
A 1
 
1.9%
& 1
 
1.9%
R 1
 
1.9%
None
ValueCountFrequency (%)
㈜ 3
100.0%

우편번호
Real number (ℝ)

Distinct59
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4998.303
Minimum4903
Maximum5119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1019.0 B
2024-03-14T17:35:07.892881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4903
5-th percentile4918
Q14931.5
median4996
Q35045
95-th percentile5078.2
Maximum5119
Range216
Interquartile range (IQR)113.5

Descriptive statistics

Standard deviation58.444366
Coefficient of variation (CV)0.011692842
Kurtosis-1.2339794
Mean4998.303
Median Absolute Deviation (MAD)55
Skewness0.092000707
Sum494832
Variance3415.744
MonotonicityNot monotonic
2024-03-14T17:35:08.140150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4929 10
 
10.1%
5044 10
 
10.1%
4931 3
 
3.0%
4930 3
 
3.0%
5073 3
 
3.0%
4985 3
 
3.0%
5072 3
 
3.0%
4969 3
 
3.0%
4945 2
 
2.0%
5056 2
 
2.0%
Other values (49) 57
57.6%
ValueCountFrequency (%)
4903 1
 
1.0%
4910 1
 
1.0%
4912 1
 
1.0%
4917 1
 
1.0%
4918 2
 
2.0%
4919 1
 
1.0%
4927 1
 
1.0%
4928 1
 
1.0%
4929 10
10.1%
4930 3
 
3.0%
ValueCountFrequency (%)
5119 1
 
1.0%
5116 1
 
1.0%
5103 1
 
1.0%
5099 1
 
1.0%
5080 1
 
1.0%
5078 1
 
1.0%
5076 1
 
1.0%
5075 1
 
1.0%
5074 1
 
1.0%
5073 3
3.0%

주소
Text

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size920.0 B
2024-03-14T17:35:09.361705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length31.010101
Min length22

Characters and Unicode

Total characters3070
Distinct characters124
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st row서울특별시 광진구 광나루로56길 63, 프라임프라자 지하1층 113호 (구의동)
2nd row서울특별시 광진구 능동로 278-1, 3층 (능동)
3rd row서울특별시 광진구 능동로 352-1, 장안빌딩 5층 2호 (중곡동)
4th row서울특별시 광진구 광나루로 430, 청산빌딩 502호 (화양동)
5th row서울특별시 광진구 아차산로78길 44, 크레스코빌딩 814호 (광장동)
ValueCountFrequency (%)
서울특별시 99
 
15.8%
광진구 99
 
15.8%
중곡동 32
 
5.1%
자양동 23
 
3.7%
아차산로 17
 
2.7%
구의동 16
 
2.6%
2층 15
 
2.4%
천호대로 14
 
2.2%
3층 13
 
2.1%
능동로 10
 
1.6%
Other values (197) 289
46.1%
2024-03-14T17:35:10.921845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
528
 
17.2%
동 123
 
4.0%
구 115
 
3.7%
광 114
 
3.7%
진 103
 
3.4%
서 100
 
3.3%
울 99
 
3.2%
특 99
 
3.2%
별 99
 
3.2%
시 99
 
3.2%
Other values (114) 1591
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1745
56.8%
Space Separator 528
 
17.2%
Decimal Number 502
 
16.4%
Close Punctuation 99
 
3.2%
Open Punctuation 99
 
3.2%
Other Punctuation 80
 
2.6%
Dash Punctuation 11
 
0.4%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 123
 
7.0%
구 115
 
6.6%
광 114
 
6.5%
진 103
 
5.9%
서 100
 
5.7%
울 99
 
5.7%
특 99
 
5.7%
별 99
 
5.7%
시 99
 
5.7%
로 99
 
5.7%
Other values (94) 695
39.8%
Decimal Number
ValueCountFrequency (%)
1 84
16.7%
3 84
16.7%
2 70
13.9%
0 61
12.2%
4 46
9.2%
5 45
9.0%
6 37
7.4%
7 30
 
6.0%
8 30
 
6.0%
9 15
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
33.3%
B 2
33.3%
N 1
16.7%
U 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 59
73.8%
, 21
 
26.2%
Space Separator
ValueCountFrequency (%)
528
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1745
56.8%
Common 1319
43.0%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 123
 
7.0%
구 115
 
6.6%
광 114
 
6.5%
진 103
 
5.9%
서 100
 
5.7%
울 99
 
5.7%
특 99
 
5.7%
별 99
 
5.7%
시 99
 
5.7%
로 99
 
5.7%
Other values (94) 695
39.8%
Common
ValueCountFrequency (%)
528
40.0%
) 99
 
7.5%
( 99
 
7.5%
1 84
 
6.4%
3 84
 
6.4%
2 70
 
5.3%
0 61
 
4.6%
. 59
 
4.5%
4 46
 
3.5%
5 45
 
3.4%
Other values (6) 144
 
10.9%
Latin
ValueCountFrequency (%)
S 2
33.3%
B 2
33.3%
N 1
16.7%
U 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1745
56.8%
ASCII 1325
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
528
39.8%
) 99
 
7.5%
( 99
 
7.5%
1 84
 
6.3%
3 84
 
6.3%
2 70
 
5.3%
0 61
 
4.6%
. 59
 
4.5%
4 46
 
3.5%
5 45
 
3.4%
Other values (10) 150
 
11.3%
Hangul
ValueCountFrequency (%)
동 123
 
7.0%
구 115
 
6.6%
광 114
 
6.5%
진 103
 
5.9%
서 100
 
5.7%
울 99
 
5.7%
특 99
 
5.7%
별 99
 
5.7%
시 99
 
5.7%
로 99
 
5.7%
Other values (94) 695
39.8%

전화번호
Text

MISSING 

Distinct87
Distinct (%)100.0%
Missing12
Missing (%)12.1%
Memory size920.0 B
2024-03-14T17:35:12.018500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.252874
Min length11

Characters and Unicode

Total characters979
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)100.0%

Sample

1st row02-6953-5613
2nd row02-446-4344
3rd row02-565-6708
4th row02-713-8801
5th row02-515-2196
ValueCountFrequency (%)
02-6953-5613 1
 
1.1%
02-522-1411 1
 
1.1%
02-2242-6072 1
 
1.1%
02-447-0026 1
 
1.1%
02-461-9004 1
 
1.1%
02-2237-3579 1
 
1.1%
02-462-5008 1
 
1.1%
02-444-2280 1
 
1.1%
02-830-1190 1
 
1.1%
02-455-5333 1
 
1.1%
Other values (77) 77
88.5%
2024-03-14T17:35:13.370512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 174
17.8%
0 148
15.1%
2 146
14.9%
4 124
12.7%
5 77
7.9%
6 68
 
6.9%
7 55
 
5.6%
1 54
 
5.5%
3 46
 
4.7%
8 46
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 805
82.2%
Dash Punctuation 174
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 148
18.4%
2 146
18.1%
4 124
15.4%
5 77
9.6%
6 68
8.4%
7 55
 
6.8%
1 54
 
6.7%
3 46
 
5.7%
8 46
 
5.7%
9 41
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 979
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 174
17.8%
0 148
15.1%
2 146
14.9%
4 124
12.7%
5 77
7.9%
6 68
 
6.9%
7 55
 
5.6%
1 54
 
5.5%
3 46
 
4.7%
8 46
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 979
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 174
17.8%
0 148
15.1%
2 146
14.9%
4 124
12.7%
5 77
7.9%
6 68
 
6.9%
7 55
 
5.6%
1 54
 
5.5%
3 46
 
4.7%
8 46
 
4.7%

Interactions

2024-03-14T17:35:04.822656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T17:35:13.530941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호우편번호주소전화번호
상호1.0001.0001.0001.000
우편번호1.0001.0001.0001.000
주소1.0001.0001.0001.000
전화번호1.0001.0001.0001.000

Missing values

2024-03-14T17:35:05.158560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:35:05.434539image/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

상호우편번호주소전화번호
0주식회사 비포유컨설팅5119서울특별시 광진구 광나루로56길 63, 프라임프라자 지하1층 113호 (구의동)<NA>
1㈜아스트로스인터내셔널4989서울특별시 광진구 능동로 278-1, 3층 (능동)02-6953-5613
2㈜한울에이치엠4927서울특별시 광진구 능동로 352-1, 장안빌딩 5층 2호 (중곡동)02-446-4344
3피플뱅크코리아 주식회사5022서울특별시 광진구 광나루로 430, 청산빌딩 502호 (화양동)02-565-6708
4㈜코니언정보4969서울특별시 광진구 아차산로78길 44, 크레스코빌딩 814호 (광장동)02-713-8801
5청년인력4964서울특별시 광진구 아차산로 635, 워커힐아파트 216호 (광장동)<NA>
6팔도인력4945서울특별시 광진구 용마산로 60, 3층 (중곡동)<NA>
7드림간병협회4931서울특별시 광진구 천호대로 619, 2층 203호 (중곡동)<NA>
8엔젤 직업소개소5099서울특별시 광진구 뚝섬로50길 7-17, 1층 (자양동)02-515-2196
9비전서치5070서울특별시 광진구 뚝섬로 541 4층 402호 (자양동)070-8244-3270
상호우편번호주소전화번호
89금성인력5005서울특별시 광진구 광나루로17길 13-1 (군자동)02-462-7600
90(주)효플러스5044서울특별시 광진구 아차산로 415. 장안빌딩 201호 (구의동)02-453-2921
91KARP대한은퇴자협회4968서울특별시 광진구 아차산로 589 (광장동)02-456-0308
92한강직업소개소5072서울특별시 광진구 아차산로 218 (자양동)02-463-7700
93명성직업소개소5021서울특별시 광진구 능동로 183 (화양동)02-466-4422
94동성직업소개소5005서울특별시 광진구 광나루로 369. 광진두산위브파크 126호 (군자동)02-458-5544
95이화파출부4929서울특별시 광진구 천호대로 557. 풍국빌딩 401호 (중곡동)02-444-7400
96소망5080서울특별시 광진구 동일로10길 30, 205호 (자양동)<NA>
97광진직업소개소5073서울특별시 광진구 동일로20길 113 (자양동)02-462-9393
98(주)한일케어5044서울특별시 광진구 아차산로 403, 경암빌딩 303호 (구의동)02-423-6624