Overview

Dataset statistics

Number of variables11
Number of observations1066
Missing cells196
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory95.9 KiB
Average record size in memory92.1 B

Variable types

Numeric4
Categorical1
Text6

Dataset

Description영천시에 등록된 공장 현황과 관련하여 농공단지명, 회사명, 대표자명, 주소, 업종명, 전화번호 등을 포함한 자료입니다.공장 현황 데이터로 참고하시기 바랍니다.
Author경상북도 영천시
URLhttps://www.data.go.kr/data/15004652/fileData.do

Alerts

용지면적 is highly overall correlated with 건축면적High correlation
건축면적 is highly overall correlated with 용지면적High correlation
단지명 is highly imbalanced (80.4%)Imbalance
전화번호 has 195 (18.3%) missing valuesMissing
순번 has unique valuesUnique
용지면적 has 71 (6.7%) zerosZeros

Reproduction

Analysis started2024-03-16 04:15:49.503911
Analysis finished2024-03-16 04:15:55.378236
Duration5.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct1066
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean533.5
Minimum1
Maximum1066
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.5 KiB
2024-03-16T13:15:55.475303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile54.25
Q1267.25
median533.5
Q3799.75
95-th percentile1012.75
Maximum1066
Range1065
Interquartile range (IQR)532.5

Descriptive statistics

Standard deviation307.872
Coefficient of variation (CV)0.57707966
Kurtosis-1.2
Mean533.5
Median Absolute Deviation (MAD)266.5
Skewness0
Sum568711
Variance94785.167
MonotonicityStrictly increasing
2024-03-16T13:15:55.664653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
717 1
 
0.1%
703 1
 
0.1%
704 1
 
0.1%
705 1
 
0.1%
706 1
 
0.1%
707 1
 
0.1%
708 1
 
0.1%
709 1
 
0.1%
710 1
 
0.1%
Other values (1056) 1056
99.1%
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 (%)
1066 1
0.1%
1065 1
0.1%
1064 1
0.1%
1063 1
0.1%
1062 1
0.1%
1061 1
0.1%
1060 1
0.1%
1059 1
0.1%
1058 1
0.1%
1057 1
0.1%

단지명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
<NA>
995 
영천화산농공단지
 
17
영천북안농공단지
 
15
영천도남농공단지
 
15
영천본촌농공단지
 
13

Length

Max length8
Median length4
Mean length4.2664165
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 995
93.3%
영천화산농공단지 17
 
1.6%
영천북안농공단지 15
 
1.4%
영천도남농공단지 15
 
1.4%
영천본촌농공단지 13
 
1.2%
영천고경농공단지 11
 
1.0%

Length

2024-03-16T13:15:55.854836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:15:56.044002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 995
93.3%
영천화산농공단지 17
 
1.6%
영천북안농공단지 15
 
1.4%
영천도남농공단지 15
 
1.4%
영천본촌농공단지 13
 
1.2%
영천고경농공단지 11
 
1.0%

회사명
Text

Distinct1029
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2024-03-16T13:15:56.470844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length7.2345216
Min length2

Characters and Unicode

Total characters7712
Distinct characters408
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique996 ?
Unique (%)93.4%

Sample

1st row (주)대영공업
2nd row(주) 아름
3rd row(주) 엘앤피 농업회사법인
4th row(주)갓바위
5th row(주)강산
ValueCountFrequency (%)
주식회사 66
 
5.4%
농업회사법인 31
 
2.5%
제2공장 7
 
0.6%
주)신영 5
 
0.4%
영천지점 5
 
0.4%
2공장 5
 
0.4%
영천공장 4
 
0.3%
화진 3
 
0.2%
제3공장 3
 
0.2%
지점 3
 
0.2%
Other values (1038) 1095
89.2%
2024-03-16T13:15:57.215813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 661
 
8.6%
( 598
 
7.8%
) 598
 
7.8%
업 237
 
3.1%
산 198
 
2.6%
이 172
 
2.2%
사 165
 
2.1%
164
 
2.1%
스 150
 
1.9%
회 135
 
1.8%
Other values (398) 4634
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6236
80.9%
Open Punctuation 598
 
7.8%
Close Punctuation 598
 
7.8%
Space Separator 164
 
2.1%
Uppercase Letter 62
 
0.8%
Decimal Number 43
 
0.6%
Other Punctuation 10
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 661
 
10.6%
업 237
 
3.8%
산 198
 
3.2%
이 172
 
2.8%
사 165
 
2.6%
스 150
 
2.4%
회 135
 
2.2%
영 120
 
1.9%
농 106
 
1.7%
인 105
 
1.7%
Other values (366) 4187
67.1%
Uppercase Letter
ValueCountFrequency (%)
E 10
16.1%
N 7
11.3%
G 6
9.7%
T 5
 
8.1%
C 4
 
6.5%
K 4
 
6.5%
I 3
 
4.8%
D 3
 
4.8%
H 3
 
4.8%
M 3
 
4.8%
Other values (10) 14
22.6%
Decimal Number
ValueCountFrequency (%)
2 29
67.4%
1 7
 
16.3%
3 5
 
11.6%
6 1
 
2.3%
5 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 8
80.0%
& 1
 
10.0%
· 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 598
100.0%
Close Punctuation
ValueCountFrequency (%)
) 598
100.0%
Space Separator
ValueCountFrequency (%)
164
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6237
80.9%
Common 1413
 
18.3%
Latin 62
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 661
 
10.6%
업 237
 
3.8%
산 198
 
3.2%
이 172
 
2.8%
사 165
 
2.6%
스 150
 
2.4%
회 135
 
2.2%
영 120
 
1.9%
농 106
 
1.7%
인 105
 
1.7%
Other values (367) 4188
67.1%
Latin
ValueCountFrequency (%)
E 10
16.1%
N 7
11.3%
G 6
9.7%
T 5
 
8.1%
C 4
 
6.5%
K 4
 
6.5%
I 3
 
4.8%
D 3
 
4.8%
H 3
 
4.8%
M 3
 
4.8%
Other values (10) 14
22.6%
Common
ValueCountFrequency (%)
( 598
42.3%
) 598
42.3%
164
 
11.6%
2 29
 
2.1%
. 8
 
0.6%
1 7
 
0.5%
3 5
 
0.4%
6 1
 
0.1%
5 1
 
0.1%
& 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6236
80.9%
ASCII 1474
 
19.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 661
 
10.6%
업 237
 
3.8%
산 198
 
3.2%
이 172
 
2.8%
사 165
 
2.6%
스 150
 
2.4%
회 135
 
2.2%
영 120
 
1.9%
농 106
 
1.7%
인 105
 
1.7%
Other values (366) 4187
67.1%
ASCII
ValueCountFrequency (%)
( 598
40.6%
) 598
40.6%
164
 
11.1%
2 29
 
2.0%
E 10
 
0.7%
. 8
 
0.5%
N 7
 
0.5%
1 7
 
0.5%
G 6
 
0.4%
3 5
 
0.3%
Other values (20) 42
 
2.8%
None
ValueCountFrequency (%)
㈜ 1
50.0%
· 1
50.0%

대표자명
Text

Distinct945
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2024-03-16T13:15:57.795467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.1801126
Min length2

Characters and Unicode

Total characters3390
Distinct characters219
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique847 ?
Unique (%)79.5%

Sample

1st row유성동
2nd row신동혁
3rd row박은호
4th row이현준
5th row이수진
ValueCountFrequency (%)
강호갑 5
 
0.5%
이정남 3
 
0.3%
이희화 3
 
0.3%
최익구 3
 
0.3%
곽경동 3
 
0.3%
오길봉 3
 
0.3%
정서진 3
 
0.3%
고운정 3
 
0.3%
이은숙 3
 
0.3%
김성곤 3
 
0.3%
Other values (960) 1061
97.1%
2024-03-16T13:15:58.523394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 209
 
6.2%
이 169
 
5.0%
정 122
 
3.6%
박 91
 
2.7%
영 89
 
2.6%
진 66
 
1.9%
성 60
 
1.8%
태 59
 
1.7%
수 59
 
1.7%
호 58
 
1.7%
Other values (209) 2408
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3322
98.0%
Other Punctuation 38
 
1.1%
Space Separator 27
 
0.8%
Decimal Number 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 209
 
6.3%
이 169
 
5.1%
정 122
 
3.7%
박 91
 
2.7%
영 89
 
2.7%
진 66
 
2.0%
성 60
 
1.8%
태 59
 
1.8%
수 59
 
1.8%
호 58
 
1.7%
Other values (205) 2340
70.4%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3322
98.0%
Common 68
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 209
 
6.3%
이 169
 
5.1%
정 122
 
3.7%
박 91
 
2.7%
영 89
 
2.7%
진 66
 
2.0%
성 60
 
1.8%
태 59
 
1.8%
수 59
 
1.8%
호 58
 
1.7%
Other values (205) 2340
70.4%
Common
ValueCountFrequency (%)
, 38
55.9%
27
39.7%
1 2
 
2.9%
2 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3322
98.0%
ASCII 68
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 209
 
6.3%
이 169
 
5.1%
정 122
 
3.7%
박 91
 
2.7%
영 89
 
2.7%
진 66
 
2.0%
성 60
 
1.8%
태 59
 
1.8%
수 59
 
1.8%
호 58
 
1.7%
Other values (205) 2340
70.4%
ASCII
ValueCountFrequency (%)
, 38
55.9%
27
39.7%
1 2
 
2.9%
2 1
 
1.5%

공장대표주소(지번)
Text

Distinct1041
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2024-03-16T13:15:58.972353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length44
Mean length24.479362
Min length13

Characters and Unicode

Total characters26095
Distinct characters180
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

Unique1019 ?
Unique (%)95.6%

Sample

1st row경상북도 영천시 대창면 대창리 1001번지
2nd row경상북도 영천시 대창면 구지리 207-1번지
3rd row경상북도 영천시 대창면 사리리 594-2 외 1필지
4th row경상북도 영천시 청통면 애련리 385번지
5th row경상북도 영천시 북안면 옥천리 102-7번지
ValueCountFrequency (%)
경상북도 1065
17.9%
영천시 1065
17.9%
외 381
 
6.4%
1필지 190
 
3.2%
대창면 173
 
2.9%
금호읍 154
 
2.6%
청통면 146
 
2.5%
사리리 104
 
1.8%
고경면 83
 
1.4%
2필지 80
 
1.3%
Other values (1173) 2495
42.0%
2024-03-16T13:15:59.692644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4904
18.8%
지 1243
 
4.8%
경 1151
 
4.4%
도 1149
 
4.4%
북 1148
 
4.4%
천 1145
 
4.4%
상 1088
 
4.2%
영 1066
 
4.1%
시 1065
 
4.1%
1 955
 
3.7%
Other values (170) 11181
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16122
61.8%
Space Separator 4904
 
18.8%
Decimal Number 4319
 
16.6%
Dash Punctuation 700
 
2.7%
Open Punctuation 19
 
0.1%
Close Punctuation 19
 
0.1%
Uppercase Letter 9
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1243
 
7.7%
경 1151
 
7.1%
도 1149
 
7.1%
북 1148
 
7.1%
천 1145
 
7.1%
상 1088
 
6.7%
영 1066
 
6.6%
시 1065
 
6.6%
리 927
 
5.7%
번 834
 
5.2%
Other values (148) 5306
32.9%
Decimal Number
ValueCountFrequency (%)
1 955
22.1%
2 552
12.8%
4 455
10.5%
3 441
10.2%
5 436
10.1%
0 350
 
8.1%
6 326
 
7.5%
7 283
 
6.6%
8 279
 
6.5%
9 242
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
22.2%
N 2
22.2%
G 2
22.2%
B 1
11.1%
A 1
11.1%
F 1
11.1%
Space Separator
ValueCountFrequency (%)
4904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 700
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16122
61.8%
Common 9963
38.2%
Latin 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1243
 
7.7%
경 1151
 
7.1%
도 1149
 
7.1%
북 1148
 
7.1%
천 1145
 
7.1%
상 1088
 
6.7%
영 1066
 
6.6%
시 1065
 
6.6%
리 927
 
5.7%
번 834
 
5.2%
Other values (148) 5306
32.9%
Common
ValueCountFrequency (%)
4904
49.2%
1 955
 
9.6%
- 700
 
7.0%
2 552
 
5.5%
4 455
 
4.6%
3 441
 
4.4%
5 436
 
4.4%
0 350
 
3.5%
6 326
 
3.3%
7 283
 
2.8%
Other values (5) 561
 
5.6%
Latin
ValueCountFrequency (%)
C 2
20.0%
N 2
20.0%
G 2
20.0%
B 1
10.0%
c 1
10.0%
A 1
10.0%
F 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16122
61.8%
ASCII 9973
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4904
49.2%
1 955
 
9.6%
- 700
 
7.0%
2 552
 
5.5%
4 455
 
4.6%
3 441
 
4.4%
5 436
 
4.4%
0 350
 
3.5%
6 326
 
3.3%
7 283
 
2.8%
Other values (12) 571
 
5.7%
Hangul
ValueCountFrequency (%)
지 1243
 
7.7%
경 1151
 
7.1%
도 1149
 
7.1%
북 1148
 
7.1%
천 1145
 
7.1%
상 1088
 
6.7%
영 1066
 
6.6%
시 1065
 
6.6%
리 927
 
5.7%
번 834
 
5.2%
Other values (148) 5306
32.9%

대표업종번호
Real number (ℝ)

Distinct244
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21666.459
Minimum10121
Maximum38322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.5 KiB
2024-03-16T13:15:59.910877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10121
5-th percentile10309
Q113229
median23129
Q327199
95-th percentile30399
Maximum38322
Range28201
Interquartile range (IQR)13970

Descriptive statistics

Standard deviation7165.4997
Coefficient of variation (CV)0.33071854
Kurtosis-1.019566
Mean21666.459
Median Absolute Deviation (MAD)6043
Skewness-0.20036206
Sum23096445
Variance51344386
MonotonicityNot monotonic
2024-03-16T13:16:00.109841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30399 61
 
5.7%
13104 51
 
4.8%
10309 44
 
4.1%
25113 39
 
3.7%
30320 27
 
2.5%
20203 23
 
2.2%
13213 22
 
2.1%
22299 21
 
2.0%
25112 20
 
1.9%
20312 19
 
1.8%
Other values (234) 739
69.3%
ValueCountFrequency (%)
10121 2
 
0.2%
10122 3
 
0.3%
10129 5
 
0.5%
10211 2
 
0.2%
10212 1
 
0.1%
10220 3
 
0.3%
10301 2
 
0.2%
10302 1
 
0.1%
10309 44
4.1%
10401 2
 
0.2%
ValueCountFrequency (%)
38322 2
 
0.2%
38321 10
0.9%
38311 2
 
0.2%
34011 1
 
0.1%
33920 1
 
0.1%
33910 3
 
0.3%
33209 1
 
0.1%
32099 1
 
0.1%
32091 4
 
0.4%
32029 7
0.7%

업종명
Text

Distinct404
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2024-03-16T13:16:00.630028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length17.711069
Min length6

Characters and Unicode

Total characters18880
Distinct characters284
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)21.7%

Sample

1st row그 외 자동차용 신품 부품 제조업 외 3 종
2nd row그 외 기타 나무제품 제조업 외 1 종
3rd row기기용 자동측정 및 제어장치 제조업 외 1 종
4th row기타 발효주 제조업
5th row콘크리트 관 및 기타 구조용 콘크리트 제품 제조업
ValueCountFrequency (%)
제조업 884
 
14.2%
외 581
 
9.3%
및 504
 
8.1%
종 425
 
6.8%
기타 304
 
4.9%
1 250
 
4.0%
그 156
 
2.5%
금속 107
 
1.7%
신품 101
 
1.6%
부품 92
 
1.5%
Other values (453) 2823
45.3%
2024-03-16T13:16:01.730593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5161
27.3%
제 1161
 
6.1%
업 1121
 
5.9%
조 1108
 
5.9%
외 589
 
3.1%
및 504
 
2.7%
기 473
 
2.5%
품 465
 
2.5%
종 440
 
2.3%
타 309
 
1.6%
Other values (274) 7549
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13151
69.7%
Space Separator 5161
 
27.3%
Decimal Number 442
 
2.3%
Other Punctuation 110
 
0.6%
Close Punctuation 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1161
 
8.8%
업 1121
 
8.5%
조 1108
 
8.4%
외 589
 
4.5%
및 504
 
3.8%
기 473
 
3.6%
품 465
 
3.5%
종 440
 
3.3%
타 309
 
2.3%
용 292
 
2.2%
Other values (260) 6689
50.9%
Decimal Number
ValueCountFrequency (%)
1 268
60.6%
3 59
 
13.3%
2 58
 
13.1%
4 24
 
5.4%
5 13
 
2.9%
6 10
 
2.3%
9 4
 
0.9%
8 3
 
0.7%
7 3
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 108
98.2%
. 2
 
1.8%
Space Separator
ValueCountFrequency (%)
5161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13151
69.7%
Common 5729
30.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1161
 
8.8%
업 1121
 
8.5%
조 1108
 
8.4%
외 589
 
4.5%
및 504
 
3.8%
기 473
 
3.6%
품 465
 
3.5%
종 440
 
3.3%
타 309
 
2.3%
용 292
 
2.2%
Other values (260) 6689
50.9%
Common
ValueCountFrequency (%)
5161
90.1%
1 268
 
4.7%
, 108
 
1.9%
3 59
 
1.0%
2 58
 
1.0%
4 24
 
0.4%
5 13
 
0.2%
6 10
 
0.2%
) 8
 
0.1%
( 8
 
0.1%
Other values (4) 12
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13104
69.4%
ASCII 5729
30.3%
Compat Jamo 47
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5161
90.1%
1 268
 
4.7%
, 108
 
1.9%
3 59
 
1.0%
2 58
 
1.0%
4 24
 
0.4%
5 13
 
0.2%
6 10
 
0.2%
) 8
 
0.1%
( 8
 
0.1%
Other values (4) 12
 
0.2%
Hangul
ValueCountFrequency (%)
제 1161
 
8.9%
업 1121
 
8.6%
조 1108
 
8.5%
외 589
 
4.5%
및 504
 
3.8%
기 473
 
3.6%
품 465
 
3.5%
종 440
 
3.4%
타 309
 
2.4%
용 292
 
2.2%
Other values (259) 6642
50.7%
Compat Jamo
ValueCountFrequency (%)
ㆍ 47
100.0%

전화번호
Text

MISSING 

Distinct787
Distinct (%)90.4%
Missing195
Missing (%)18.3%
Memory size8.5 KiB
2024-03-16T13:16:02.143682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008037
Min length8

Characters and Unicode

Total characters10459
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique718 ?
Unique (%)82.4%

Sample

1st row054-335-2555
2nd row054-337-3399
3rd row053-856-0916
4th row054-336-8997
5th row054-331-7301
ValueCountFrequency (%)
054-335-3000 5
 
0.6%
054-336-1212 4
 
0.5%
054-331-4700 4
 
0.5%
054-337-3314 3
 
0.3%
054-336-5678 3
 
0.3%
054-336-4030 3
 
0.3%
054-336-9551 3
 
0.3%
054-334-9192 3
 
0.3%
054-333-1767 3
 
0.3%
054-331-2641 3
 
0.3%
Other values (777) 837
96.1%
2024-03-16T13:16:02.734821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1992
19.0%
- 1738
16.6%
0 1503
14.4%
5 1376
13.2%
4 1070
10.2%
6 563
 
5.4%
1 551
 
5.3%
8 495
 
4.7%
7 468
 
4.5%
2 384
 
3.7%
Other values (4) 319
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8718
83.4%
Dash Punctuation 1738
 
16.6%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1992
22.8%
0 1503
17.2%
5 1376
15.8%
4 1070
12.3%
6 563
 
6.5%
1 551
 
6.3%
8 495
 
5.7%
7 468
 
5.4%
2 384
 
4.4%
9 316
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
R 1
33.3%
S 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1738
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10456
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1992
19.1%
- 1738
16.6%
0 1503
14.4%
5 1376
13.2%
4 1070
10.2%
6 563
 
5.4%
1 551
 
5.3%
8 495
 
4.7%
7 468
 
4.5%
2 384
 
3.7%
Latin
ValueCountFrequency (%)
A 1
33.3%
R 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1992
19.0%
- 1738
16.6%
0 1503
14.4%
5 1376
13.2%
4 1070
10.2%
6 563
 
5.4%
1 551
 
5.3%
8 495
 
4.7%
7 468
 
4.5%
2 384
 
3.7%
Other values (4) 319
 
3.1%

생산품
Text

Distinct933
Distinct (%)87.6%
Missing1
Missing (%)0.1%
Memory size8.5 KiB
2024-03-16T13:16:03.198113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length39
Mean length9.5323944
Min length1

Characters and Unicode

Total characters10152
Distinct characters587
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique876 ?
Unique (%)82.3%

Sample

1st row자동차공구
2nd row각종시설물,조경물,인테리어등의 목제품제조, 운동시설물,퍼걸러,조경시설물
3rd rowLED조명장치, 제어시스템
4th row생약주
5th row식생옹벽, 호안블럭
ValueCountFrequency (%)
및 65
 
3.4%
등 46
 
2.4%
연사 24
 
1.3%
자동차부품 21
 
1.1%
플라스틱 18
 
0.9%
인조잔디 14
 
0.7%
자동차 13
 
0.7%
창호 11
 
0.6%
부품 11
 
0.6%
알루미늄 9
 
0.5%
Other values (1323) 1664
87.8%
2024-03-16T13:16:03.968745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
838
 
8.3%
, 530
 
5.2%
품 244
 
2.4%
기 206
 
2.0%
스 184
 
1.8%
자 172
 
1.7%
제 160
 
1.6%
조 158
 
1.6%
용 152
 
1.5%
재 151
 
1.5%
Other values (577) 7357
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8163
80.4%
Space Separator 838
 
8.3%
Other Punctuation 545
 
5.4%
Uppercase Letter 206
 
2.0%
Open Punctuation 139
 
1.4%
Close Punctuation 138
 
1.4%
Lowercase Letter 101
 
1.0%
Decimal Number 19
 
0.2%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 244
 
3.0%
기 206
 
2.5%
스 184
 
2.3%
자 172
 
2.1%
제 160
 
2.0%
조 158
 
1.9%
용 152
 
1.9%
재 151
 
1.8%
부 138
 
1.7%
차 137
 
1.7%
Other values (516) 6461
79.1%
Uppercase Letter
ValueCountFrequency (%)
P 41
19.9%
E 24
11.7%
C 22
10.7%
L 13
 
6.3%
D 13
 
6.3%
M 10
 
4.9%
A 9
 
4.4%
R 8
 
3.9%
S 8
 
3.9%
F 8
 
3.9%
Other values (12) 50
24.3%
Lowercase Letter
ValueCountFrequency (%)
e 15
14.9%
i 9
 
8.9%
p 9
 
8.9%
c 7
 
6.9%
g 7
 
6.9%
t 7
 
6.9%
r 6
 
5.9%
s 5
 
5.0%
h 5
 
5.0%
m 4
 
4.0%
Other values (12) 27
26.7%
Decimal Number
ValueCountFrequency (%)
1 8
42.1%
2 5
26.3%
9 2
 
10.5%
7 1
 
5.3%
3 1
 
5.3%
8 1
 
5.3%
4 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 530
97.2%
. 7
 
1.3%
/ 5
 
0.9%
？ 1
 
0.2%
· 1
 
0.2%
% 1
 
0.2%
Space Separator
ValueCountFrequency (%)
838
100.0%
Open Punctuation
ValueCountFrequency (%)
( 139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8163
80.4%
Common 1682
 
16.6%
Latin 307
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 244
 
3.0%
기 206
 
2.5%
스 184
 
2.3%
자 172
 
2.1%
제 160
 
2.0%
조 158
 
1.9%
용 152
 
1.9%
재 151
 
1.8%
부 138
 
1.7%
차 137
 
1.7%
Other values (516) 6461
79.1%
Latin
ValueCountFrequency (%)
P 41
 
13.4%
E 24
 
7.8%
C 22
 
7.2%
e 15
 
4.9%
L 13
 
4.2%
D 13
 
4.2%
M 10
 
3.3%
A 9
 
2.9%
i 9
 
2.9%
p 9
 
2.9%
Other values (34) 142
46.3%
Common
ValueCountFrequency (%)
838
49.8%
, 530
31.5%
( 139
 
8.3%
) 138
 
8.2%
1 8
 
0.5%
. 7
 
0.4%
/ 5
 
0.3%
2 5
 
0.3%
- 3
 
0.2%
9 2
 
0.1%
Other values (7) 7
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8163
80.4%
ASCII 1987
 
19.6%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
838
42.2%
, 530
26.7%
( 139
 
7.0%
) 138
 
6.9%
P 41
 
2.1%
E 24
 
1.2%
C 22
 
1.1%
e 15
 
0.8%
L 13
 
0.7%
D 13
 
0.7%
Other values (49) 214
 
10.8%
Hangul
ValueCountFrequency (%)
품 244
 
3.0%
기 206
 
2.5%
스 184
 
2.3%
자 172
 
2.1%
제 160
 
2.0%
조 158
 
1.9%
용 152
 
1.9%
재 151
 
1.8%
부 138
 
1.7%
차 137
 
1.7%
Other values (516) 6461
79.1%
None
ValueCountFrequency (%)
？ 1
50.0%
· 1
50.0%

용지면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct911
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5035.1986
Minimum0
Maximum67282
Zeros71
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size9.5 KiB
2024-03-16T13:16:04.213463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11762
median3279.15
Q35938.25
95-th percentile15530.75
Maximum67282
Range67282
Interquartile range (IQR)4176.25

Descriptive statistics

Standard deviation6147.7526
Coefficient of variation (CV)1.2209553
Kurtosis25.33376
Mean5035.1986
Median Absolute Deviation (MAD)1703.65
Skewness4.0358449
Sum5367521.7
Variance37794862
MonotonicityNot monotonic
2024-03-16T13:16:04.466872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 71
 
6.7%
1653.0 9
 
0.8%
800.0 5
 
0.5%
1983.0 4
 
0.4%
5100.0 3
 
0.3%
992.0 3
 
0.3%
3629.0 3
 
0.3%
3191.0 3
 
0.3%
2314.0 3
 
0.3%
3306.0 3
 
0.3%
Other values (901) 959
90.0%
ValueCountFrequency (%)
0.0 71
6.7%
183.0 1
 
0.1%
201.48 1
 
0.1%
203.0 1
 
0.1%
208.0 1
 
0.1%
265.0 1
 
0.1%
300.0 1
 
0.1%
303.6 1
 
0.1%
310.0 1
 
0.1%
317.0 1
 
0.1%
ValueCountFrequency (%)
67282.0 1
0.1%
59402.0 1
0.1%
52506.0 1
0.1%
48389.8 1
0.1%
42938.94 1
0.1%
40340.0 1
0.1%
39503.0 1
0.1%
29995.0 1
0.1%
29890.0 1
0.1%
29677.0 1
0.1%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct1027
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1981.3922
Minimum16.5
Maximum34157.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.5 KiB
2024-03-16T13:16:05.147612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16.5
5-th percentile280
Q1593.435
median1171.465
Q32162.66
95-th percentile6334.7875
Maximum34157.01
Range34140.51
Interquartile range (IQR)1569.225

Descriptive statistics

Standard deviation2782.3094
Coefficient of variation (CV)1.4042195
Kurtosis42.706871
Mean1981.3922
Median Absolute Deviation (MAD)672.455
Skewness5.3185874
Sum2112164
Variance7741245.8
MonotonicityNot monotonic
2024-03-16T13:16:05.451918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330.0 7
 
0.7%
324.0 5
 
0.5%
490.0 4
 
0.4%
49.338 4
 
0.4%
493.5 4
 
0.4%
480.0 3
 
0.3%
66.138 3
 
0.3%
390.0 3
 
0.3%
280.0 2
 
0.2%
996.0 2
 
0.2%
Other values (1017) 1029
96.5%
ValueCountFrequency (%)
16.5 1
 
0.1%
41.31 1
 
0.1%
43.9 1
 
0.1%
49.33 1
 
0.1%
49.338 4
0.4%
49.34 1
 
0.1%
53.2 1
 
0.1%
66.138 3
0.3%
68.2 1
 
0.1%
69.42 1
 
0.1%
ValueCountFrequency (%)
34157.01 1
0.1%
29919.72 1
0.1%
28018.07 1
0.1%
26610.96 1
0.1%
18914.78 1
0.1%
17466.32 1
0.1%
15931.22 1
0.1%
14803.14 1
0.1%
13791.33 1
0.1%
13631.43 1
0.1%

Interactions

2024-03-16T13:15:53.744047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:51.166204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:52.399009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:53.164141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:53.911614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:51.751913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:52.590335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:53.311802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:54.105309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:51.942129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:52.735430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:53.457806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:54.301730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:52.150825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:52.987003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:53.589766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:16:05.616327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단지명대표업종번호용지면적건축면적
순번1.0000.4500.4050.1880.118
단지명0.4501.0000.3840.1460.000
대표업종번호0.4050.3841.0000.0000.023
용지면적0.1880.1460.0001.0000.882
건축면적0.1180.0000.0230.8821.000
2024-03-16T13:16:05.765237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번대표업종번호용지면적건축면적단지명
순번1.000-0.035-0.191-0.1850.190
대표업종번호-0.0351.0000.0600.0210.223
용지면적-0.1910.0601.0000.8200.085
건축면적-0.1850.0210.8201.0000.000
단지명0.1900.2230.0850.0001.000

Missing values

2024-03-16T13:15:54.635926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:15:55.077229image/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.
2024-03-16T13:15:55.301409image/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

순번단지명회사명대표자명공장대표주소(지번)대표업종번호업종명전화번호생산품용지면적건축면적
01<NA>(주)대영공업유성동경상북도 영천시 대창면 대창리 1001번지30399그 외 자동차용 신품 부품 제조업 외 3 종054-335-2555자동차공구6024.02281.16
12<NA>(주) 아름신동혁경상북도 영천시 대창면 구지리 207-1번지16299그 외 기타 나무제품 제조업 외 1 종054-337-3399각종시설물,조경물,인테리어등의 목제품제조, 운동시설물,퍼걸러,조경시설물19924.03087.36
23<NA>(주) 엘앤피 농업회사법인박은호경상북도 영천시 대창면 사리리 594-2 외 1필지27215기기용 자동측정 및 제어장치 제조업 외 1 종053-856-0916LED조명장치, 제어시스템1708.0536.56
34<NA>(주)갓바위이현준경상북도 영천시 청통면 애련리 385번지11119기타 발효주 제조업054-336-8997생약주1630.0958.5
45<NA>(주)강산이수진경상북도 영천시 북안면 옥천리 102-7번지23325콘크리트 관 및 기타 구조용 콘크리트 제품 제조업054-331-7301식생옹벽, 호안블럭4932.0950.63
56<NA>(주)거성피엔피변재수경상북도 영천시 청통면 신학리 631-1번지22212플라스틱 필름 제조업 외 1 종054-336-0479PP평판시트3306.01289.48
67영천화산농공단지(주)거평그린윤태순경상북도 영천시 화산면 유성리 200-2번지 외 1필지13104연사 및 가공사 제조업053-852-5674인조잔디 연사12130.04576.52
78<NA>(주)건우금속백승엽경상북도 영천시 채신동 658번지25912금속 단조제품 제조업054-336-0117금속단조부품8162.02714.61
89<NA>(주)건우환경박중삼경상북도 영천시 녹전동 124번지16300코르크 및 조물제품 제조업054-335-3131해충포집기3140.01212.4
910<NA>(주)경림장근호경상북도 영천시 금호읍 냉천리 88-4번지 외 1필지10611곡물 도정업 외 1 종054-331-5246도정,정미곡물3811.0495.0
순번단지명회사명대표자명공장대표주소(지번)대표업종번호업종명전화번호생산품용지면적건축면적
10561057영천화산농공단지화산비닐정문혁경상북도 영천시 화산면 유성리 200-1222231플라스틱 포대, 봉투 및 유사제품 제조업<NA>비닐5100.0784.4
10571058<NA>화산석재이재호경상북도 영천시 화산면 용평리 75-3번지23919기타 석제품 제조업054-335-1150석재제조1291.0224.38
10581059<NA>화산약초영농조합법인이상원경상북도 영천시 청통면 우천리 95번지 외 2필지10309기타 과실ㆍ채소 가공 및 저장 처리업054-337-0091한약재(가공)5020.01977.03
10591060<NA>화산약초영농조합법인이상원경상북도 영천시 청통면 우천리 93-1번지10309기타 과실ㆍ채소 가공 및 저장 처리업054-337-0091가공식품(농축원액 등)1814.0324.0
10601061<NA>화성가구이주형경상북도 영천시 대창면 대창리 203번지32029기타 목재가구 제조업<NA>가구제조(목재)1251.0390.0
10611062<NA>화영테크류해량경상북도 영천시 대창면 사리리 52-12번지 외 1필지22192산업용 그 외 비경화 고무제품 제조업053-583-3688자동차부품3073.01386.83
10621063<NA>황금석재황세진경상북도 영천시 도동 585-10번지23911건설용 석제품 제조업 외 1 종054-333-8564석재가공품1653.0313.4
10631064<NA>효성화학박광석경상북도 영천시 오미동 1129번지22212플라스틱 필름 제조업 외 1 종054-333-7110농사용,공업용 필름1946.01270.15
10641065<NA>효원개발김정호경상북도 영천시 고경면 덕암리 23-1번지 외 3필지22223플라스틱 창호 제조업054-338-8800플라스틱창문, 플라스틱문7010.02062.19
10651066<NA>효창산업(주)박효정경상북도 영천시 금호읍 원제리 95-3번지23991아스팔트 콘크리트 및 혼합제품 제조업054-333-3796아스콘7920.0906.76