Overview

Dataset statistics

Number of variables4
Number of observations1637
Missing cells4
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory52.9 KiB
Average record size in memory33.1 B

Variable types

Numeric1
Text3

Dataset

Description인천 부평구에 등록된 생산, 가공, 산업단지 공장등록현황입니다(순번,회사명,공장주소,업종명,생산품)ex) 1,비아이유에스,인천광역시 부평구 부평대로 283, B동 5층 510 (청천동, 부평 우림라이온스밸리),기타 구조용 금속제품 제조업,초음파용착기 등
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15034999&srcSe=7661IVAWM27C61E190

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 08:02:05.576412
Analysis finished2024-01-28 08:02:06.354639
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct1637
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean819
Minimum1
Maximum1637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2024-01-28T17:02:06.413607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile82.8
Q1410
median819
Q31228
95-th percentile1555.2
Maximum1637
Range1636
Interquartile range (IQR)818

Descriptive statistics

Standard deviation472.70551
Coefficient of variation (CV)0.57717401
Kurtosis-1.2
Mean819
Median Absolute Deviation (MAD)409
Skewness0
Sum1340703
Variance223450.5
MonotonicityStrictly increasing
2024-01-28T17:02:06.527173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1089 1
 
0.1%
1099 1
 
0.1%
1098 1
 
0.1%
1097 1
 
0.1%
1096 1
 
0.1%
1095 1
 
0.1%
1094 1
 
0.1%
1093 1
 
0.1%
1092 1
 
0.1%
Other values (1627) 1627
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1637 1
0.1%
1636 1
0.1%
1635 1
0.1%
1634 1
0.1%
1633 1
0.1%
1632 1
0.1%
1631 1
0.1%
1630 1
0.1%
1629 1
0.1%
1628 1
0.1%
Distinct1558
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2024-01-28T17:02:06.737970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length20
Mean length6.8430055
Min length2

Characters and Unicode

Total characters11202
Distinct characters525
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1488 ?
Unique (%)90.9%

Sample

1st row 비아이유에스
2nd row(사)한국척수장애인협회 피복사업소
3rd row(유)애드게이트
4th row(유)웰스코리아
5th row(주)3R GLOBAL
ValueCountFrequency (%)
주식회사 55
 
3.1%
2공장 8
 
0.5%
부평지점 5
 
0.3%
동서식품(주 4
 
0.2%
펌텍코리아(주 4
 
0.2%
피티프라스(주 4
 
0.2%
tech 3
 
0.2%
주)비바 3
 
0.2%
서울기공 3
 
0.2%
주)인찬 3
 
0.2%
Other values (1587) 1673
94.8%
2024-01-28T17:02:07.071796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
920
 
8.2%
( 869
 
7.8%
) 869
 
7.8%
474
 
4.2%
359
 
3.2%
228
 
2.0%
183
 
1.6%
176
 
1.6%
157
 
1.4%
156
 
1.4%
Other values (515) 6811
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9000
80.3%
Open Punctuation 869
 
7.8%
Close Punctuation 869
 
7.8%
Uppercase Letter 223
 
2.0%
Space Separator 134
 
1.2%
Lowercase Letter 44
 
0.4%
Decimal Number 25
 
0.2%
Other Symbol 21
 
0.2%
Other Punctuation 12
 
0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
920
 
10.2%
474
 
5.3%
359
 
4.0%
228
 
2.5%
183
 
2.0%
176
 
2.0%
157
 
1.7%
156
 
1.7%
151
 
1.7%
121
 
1.3%
Other values (461) 6075
67.5%
Uppercase Letter
ValueCountFrequency (%)
S 25
 
11.2%
C 22
 
9.9%
N 21
 
9.4%
E 19
 
8.5%
O 16
 
7.2%
T 14
 
6.3%
G 14
 
6.3%
M 13
 
5.8%
D 8
 
3.6%
A 8
 
3.6%
Other values (15) 63
28.3%
Lowercase Letter
ValueCountFrequency (%)
e 13
29.5%
c 4
 
9.1%
h 3
 
6.8%
r 3
 
6.8%
s 3
 
6.8%
t 3
 
6.8%
i 2
 
4.5%
p 2
 
4.5%
n 2
 
4.5%
a 2
 
4.5%
Other values (7) 7
15.9%
Decimal Number
ValueCountFrequency (%)
2 15
60.0%
1 4
 
16.0%
0 3
 
12.0%
3 3
 
12.0%
Other Punctuation
ValueCountFrequency (%)
. 6
50.0%
& 5
41.7%
, 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 869
100.0%
Close Punctuation
ValueCountFrequency (%)
) 869
100.0%
Space Separator
ValueCountFrequency (%)
134
100.0%
Other Symbol
ValueCountFrequency (%)
21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9021
80.5%
Common 1914
 
17.1%
Latin 267
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
920
 
10.2%
474
 
5.3%
359
 
4.0%
228
 
2.5%
183
 
2.0%
176
 
2.0%
157
 
1.7%
156
 
1.7%
151
 
1.7%
121
 
1.3%
Other values (462) 6096
67.6%
Latin
ValueCountFrequency (%)
S 25
 
9.4%
C 22
 
8.2%
N 21
 
7.9%
E 19
 
7.1%
O 16
 
6.0%
T 14
 
5.2%
G 14
 
5.2%
e 13
 
4.9%
M 13
 
4.9%
D 8
 
3.0%
Other values (32) 102
38.2%
Common
ValueCountFrequency (%)
( 869
45.4%
) 869
45.4%
134
 
7.0%
2 15
 
0.8%
. 6
 
0.3%
- 5
 
0.3%
& 5
 
0.3%
1 4
 
0.2%
0 3
 
0.2%
3 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9000
80.3%
ASCII 2181
 
19.5%
None 21
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
920
 
10.2%
474
 
5.3%
359
 
4.0%
228
 
2.5%
183
 
2.0%
176
 
2.0%
157
 
1.7%
156
 
1.7%
151
 
1.7%
121
 
1.3%
Other values (461) 6075
67.5%
ASCII
ValueCountFrequency (%)
( 869
39.8%
) 869
39.8%
134
 
6.1%
S 25
 
1.1%
C 22
 
1.0%
N 21
 
1.0%
E 19
 
0.9%
O 16
 
0.7%
2 15
 
0.7%
T 14
 
0.6%
Other values (43) 177
 
8.1%
None
ValueCountFrequency (%)
21
100.0%
Distinct1361
Distinct (%)83.2%
Missing2
Missing (%)0.1%
Memory size12.9 KiB
2024-01-28T17:02:07.366897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length89
Median length61
Mean length35.911315
Min length17

Characters and Unicode

Total characters58715
Distinct characters206
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1253 ?
Unique (%)76.6%

Sample

1st row인천광역시 부평구 부평대로 283, B동 5층 510 (청천동, 부평 우림라이온스밸리)
2nd row인천광역시 부평구 마장로426번길 33, 301호(청천동)
3rd row인천광역시 부평구 충선로 102, 2층 (부개동)
4th row인천광역시 부평구 주부토로 236, 제비동 b117호(갈산동)
5th row인천광역시 부평구 새벌로 14, 424-13 (청천동)
ValueCountFrequency (%)
인천광역시 1635
 
14.8%
부평구 1635
 
14.8%
청천동 948
 
8.6%
부평대로 615
 
5.6%
부평 336
 
3.0%
283 268
 
2.4%
337 193
 
1.7%
우림라이온스밸리 177
 
1.6%
제이타워3차 176
 
1.6%
지식산업센터 176
 
1.6%
Other values (1278) 4876
44.2%
2024-01-28T17:02:07.829309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9488
 
16.2%
3117
 
5.3%
3041
 
5.2%
3029
 
5.2%
2031
 
3.5%
3 1890
 
3.2%
1759
 
3.0%
1740
 
3.0%
, 1716
 
2.9%
1669
 
2.8%
Other values (196) 29235
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33837
57.6%
Decimal Number 9751
 
16.6%
Space Separator 9488
 
16.2%
Other Punctuation 1720
 
2.9%
Close Punctuation 1655
 
2.8%
Open Punctuation 1655
 
2.8%
Uppercase Letter 440
 
0.7%
Dash Punctuation 148
 
0.3%
Math Symbol 9
 
< 0.1%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3117
 
9.2%
3041
 
9.0%
3029
 
9.0%
2031
 
6.0%
1759
 
5.2%
1740
 
5.1%
1669
 
4.9%
1654
 
4.9%
1637
 
4.8%
1615
 
4.8%
Other values (166) 12545
37.1%
Decimal Number
ValueCountFrequency (%)
3 1890
19.4%
1 1538
15.8%
2 1469
15.1%
0 958
9.8%
7 770
7.9%
4 702
 
7.2%
8 692
 
7.1%
5 653
 
6.7%
9 565
 
5.8%
6 514
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 260
59.1%
C 107
24.3%
A 45
 
10.2%
U 22
 
5.0%
I 2
 
0.5%
F 2
 
0.5%
K 1
 
0.2%
H 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 1716
99.8%
. 4
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1654
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1654
99.9%
[ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
c 3
60.0%
b 2
40.0%
Space Separator
ValueCountFrequency (%)
9488
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Letter Number
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33837
57.6%
Common 24426
41.6%
Latin 452
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3117
 
9.2%
3041
 
9.0%
3029
 
9.0%
2031
 
6.0%
1759
 
5.2%
1740
 
5.1%
1669
 
4.9%
1654
 
4.9%
1637
 
4.8%
1615
 
4.8%
Other values (166) 12545
37.1%
Common
ValueCountFrequency (%)
9488
38.8%
3 1890
 
7.7%
, 1716
 
7.0%
) 1654
 
6.8%
( 1654
 
6.8%
1 1538
 
6.3%
2 1469
 
6.0%
0 958
 
3.9%
7 770
 
3.2%
4 702
 
2.9%
Other values (9) 2587
 
10.6%
Latin
ValueCountFrequency (%)
B 260
57.5%
C 107
23.7%
A 45
 
10.0%
U 22
 
4.9%
7
 
1.5%
c 3
 
0.7%
I 2
 
0.4%
b 2
 
0.4%
F 2
 
0.4%
K 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33837
57.6%
ASCII 24871
42.4%
Number Forms 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9488
38.1%
3 1890
 
7.6%
, 1716
 
6.9%
) 1654
 
6.7%
( 1654
 
6.7%
1 1538
 
6.2%
2 1469
 
5.9%
0 958
 
3.9%
7 770
 
3.1%
4 702
 
2.8%
Other values (19) 3032
 
12.2%
Hangul
ValueCountFrequency (%)
3117
 
9.2%
3041
 
9.0%
3029
 
9.0%
2031
 
6.0%
1759
 
5.2%
1740
 
5.1%
1669
 
4.9%
1654
 
4.9%
1637
 
4.8%
1615
 
4.8%
Other values (166) 12545
37.1%
Number Forms
ValueCountFrequency (%)
7
100.0%
Distinct561
Distinct (%)34.3%
Missing2
Missing (%)0.1%
Memory size12.9 KiB
2024-01-28T17:02:08.099184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length16.2
Min length3

Characters and Unicode

Total characters26487
Distinct characters312
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)18.3%

Sample

1st row기타 구조용 금속제품 제조업
2nd row가죽의복 제조업 외 14종
3rd row간판 및 광고물 제조업 외 8종
4th row그 외 기타 의료용 기기 제조업
5th row비디오 및 기타 영상기기 제조업 외 1종
ValueCountFrequency (%)
제조업 1486
18.3%
876
 
10.8%
624
 
7.7%
기타 520
 
6.4%
1종 346
 
4.3%
259
 
3.2%
전기 140
 
1.7%
2종 97
 
1.2%
플라스틱 94
 
1.2%
제품 81
 
1.0%
Other values (499) 3590
44.2%
2024-01-28T17:02:08.486929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6482
24.5%
1881
 
7.1%
1688
 
6.4%
1664
 
6.3%
1384
 
5.2%
887
 
3.3%
625
 
2.4%
624
 
2.4%
521
 
2.0%
472
 
1.8%
Other values (302) 10259
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19168
72.4%
Space Separator 6482
 
24.5%
Decimal Number 652
 
2.5%
Other Punctuation 169
 
0.6%
Close Punctuation 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1881
 
9.8%
1688
 
8.8%
1664
 
8.7%
1384
 
7.2%
887
 
4.6%
625
 
3.3%
624
 
3.3%
521
 
2.7%
472
 
2.5%
449
 
2.3%
Other values (286) 8973
46.8%
Decimal Number
ValueCountFrequency (%)
1 377
57.8%
2 106
 
16.3%
3 62
 
9.5%
4 37
 
5.7%
6 21
 
3.2%
5 18
 
2.8%
7 12
 
1.8%
8 7
 
1.1%
9 7
 
1.1%
0 5
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 156
92.3%
. 12
 
7.1%
· 1
 
0.6%
Space Separator
ValueCountFrequency (%)
6482
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19168
72.4%
Common 7319
 
27.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1881
 
9.8%
1688
 
8.8%
1664
 
8.7%
1384
 
7.2%
887
 
4.6%
625
 
3.3%
624
 
3.3%
521
 
2.7%
472
 
2.5%
449
 
2.3%
Other values (286) 8973
46.8%
Common
ValueCountFrequency (%)
6482
88.6%
1 377
 
5.2%
, 156
 
2.1%
2 106
 
1.4%
3 62
 
0.8%
4 37
 
0.5%
6 21
 
0.3%
5 18
 
0.2%
7 12
 
0.2%
. 12
 
0.2%
Other values (6) 36
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19167
72.4%
ASCII 7318
 
27.6%
None 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6482
88.6%
1 377
 
5.2%
, 156
 
2.1%
2 106
 
1.4%
3 62
 
0.8%
4 37
 
0.5%
6 21
 
0.3%
5 18
 
0.2%
7 12
 
0.2%
. 12
 
0.2%
Other values (5) 35
 
0.5%
Hangul
ValueCountFrequency (%)
1881
 
9.8%
1688
 
8.8%
1664
 
8.7%
1384
 
7.2%
887
 
4.6%
625
 
3.3%
624
 
3.3%
521
 
2.7%
472
 
2.5%
449
 
2.3%
Other values (285) 8972
46.8%
None
ValueCountFrequency (%)
· 1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

Interactions

2024-01-28T17:02:06.077287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-01-28T17:02:06.182987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:02:06.248709image/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.
2024-01-28T17:02:06.315855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번회사명공장주소업종명
01비아이유에스인천광역시 부평구 부평대로 283, B동 5층 510 (청천동, 부평 우림라이온스밸리)기타 구조용 금속제품 제조업
12(사)한국척수장애인협회 피복사업소인천광역시 부평구 마장로426번길 33, 301호(청천동)가죽의복 제조업 외 14종
23(유)애드게이트인천광역시 부평구 충선로 102, 2층 (부개동)간판 및 광고물 제조업 외 8종
34(유)웰스코리아인천광역시 부평구 주부토로 236, 제비동 b117호(갈산동)그 외 기타 의료용 기기 제조업
45(주)3R GLOBAL인천광역시 부평구 새벌로 14, 424-13 (청천동)비디오 및 기타 영상기기 제조업 외 1종
56(주)JCG(제이씨지)인천광역시 부평구 부평대로 337, 740호(청천동, 부평 제이타워3차 지식산업센터)그 외 기타 특수목적용 기계 제조업
67(주)SIMPAC인천광역시 부평구 부평북로 127 (청천동)디지털 적층 성형기계 제조업 외 1종
78(주)SRC인천광역시 부평구 부평대로 283, A동 4층 508B호,509호 (청천동, 부평 우림라이온스밸리)빵류 제조업
89(주)가온테크놀로지인천광역시 부평구 안남로434번길 57 (청천동)자동차용 신품 전기장치 제조업
910(주)가현테크인천광역시 부평구 안남로418번길 10(청천동)기체 여과기 제조업
순번회사명공장주소업종명
16271628화창산업인천광역시 부평구 평천로141번길 45 (청천동)주형 및 금형 제조업
16281629화창산업인천광역시 부평구 부평대로 301, B1층 112-1 (청천동, 남광센트렉스)그 외 기타 플라스틱 제품 제조업
16291630화창산업인천광역시 부평구 부평북로 247 (청천동)그 외 기타 의복액세서리 제조업
16301631효성산업인천광역시 부평구 부평대로 337, 8층 849호,850호,851호,852호(청천동, 부평 제이타워3차 지식산업센터)주방용 및 음식점용 목재가구 제조업 외 1종
16311632효성전자인천광역시 부평구 부평대로 301, 7층 713호(청천동, 남광센트렉스)기타 가정용 전기기기 제조업 외 1종
16321633흥진산업인천광역시 부평구 청안로 17 (청천동)절연 코드세트 및 기타 도체 제조업 외 1종
16331634흥창기업인천광역시 부평구 구산로 24 (일신동)그 외 기타 전자부품 제조업 외 1종
16341635희림상사인천광역시 부평구 새벌로 56 (청천동)침구 및 관련제품 제조업 외 16종
16351636희성테크놀로지인천광역시 부평구 부평대로 301, 9층 914 (청천동, 남광센트렉스)응용 소프트웨어 개발 및 공급업
16361637히어로 엔터테인먼트인천광역시 부평구 부평대로 337, 315호(청천동, 부평 제이타워3차 지식산업센터)인형 및 장난감 제조업