Overview

Dataset statistics

Number of variables5
Number of observations4264
Missing cells5
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory170.9 KiB
Average record size in memory41.0 B

Variable types

Numeric1
Text3
DateTime1

Dataset

Description전북특별자치도 산업단지 입주기업 현황에 대한 데이터로 산업단지명, 업체명, 업종명, 데이터 기준일자의 데이터가 포함되어 있습니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15112035/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant

Reproduction

Analysis started2024-03-14 20:15:13.175270
Analysis finished2024-03-14 20:15:15.705837
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

Distinct4263
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2132
Minimum1
Maximum4263
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2024-03-15T05:15:16.032886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile214.1
Q11066.5
median2132
Q33197.5
95-th percentile4049.9
Maximum4263
Range4262
Interquartile range (IQR)2131

Descriptive statistics

Standard deviation1230.7664
Coefficient of variation (CV)0.57728256
Kurtosis-1.2
Mean2132
Median Absolute Deviation (MAD)1066
Skewness0
Sum9088716
Variance1514786
MonotonicityStrictly increasing
2024-03-15T05:15:16.735147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2848 1
 
< 0.1%
2834 1
 
< 0.1%
2835 1
 
< 0.1%
2836 1
 
< 0.1%
2837 1
 
< 0.1%
2838 1
 
< 0.1%
2839 1
 
< 0.1%
2840 1
 
< 0.1%
2841 1
 
< 0.1%
Other values (4253) 4253
99.7%
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 (%)
4263 1
< 0.1%
4262 1
< 0.1%
4261 1
< 0.1%
4260 1
< 0.1%
4259 1
< 0.1%
4258 1
< 0.1%
4257 1
< 0.1%
4256 1
< 0.1%
4255 1
< 0.1%
4254 1
< 0.1%

산업단지명
Text

Distinct92
Distinct (%)2.2%
Missing1
Missing (%)< 0.1%
Memory size33.4 KiB
2024-03-15T05:15:18.376277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length9.4266948
Min length6

Characters and Unicode

Total characters40186
Distinct characters130
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st row고창고수농공단지
2nd row고창고수농공단지
3rd row고창고수농공단지
4th row고창고수농공단지
5th row고창고수농공단지
ValueCountFrequency (%)
군산2국가산업단지 611
 
14.3%
익산국가산업단지 301
 
7.1%
군산국가산업단지 229
 
5.4%
전주과학산업연구단지 224
 
5.3%
익산제2일반산업단지 220
 
5.2%
국가식품클러스터국가산업단지 186
 
4.4%
완주테크노밸리일반산업단지 123
 
2.9%
완주일반산업단지 110
 
2.6%
익산제3일반산업단지 108
 
2.5%
전주제1일반산업단지 103
 
2.4%
Other values (83) 2051
48.1%
2024-03-15T05:15:19.842381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 4950
 
12.3%
단 4412
 
11.0%
지 4364
 
10.9%
업 2878
 
7.2%
국 1539
 
3.8%
가 1536
 
3.8%
농 1276
 
3.2%
공 1271
 
3.2%
반 1228
 
3.1%
일 1228
 
3.1%
Other values (120) 15504
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38569
96.0%
Decimal Number 1473
 
3.7%
Close Punctuation 69
 
0.2%
Open Punctuation 69
 
0.2%
Dash Punctuation 3
 
< 0.1%
Space Separator 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 4950
 
12.8%
단 4412
 
11.4%
지 4364
 
11.3%
업 2878
 
7.5%
국 1539
 
4.0%
가 1536
 
4.0%
농 1276
 
3.3%
공 1271
 
3.3%
반 1228
 
3.2%
일 1228
 
3.2%
Other values (112) 13887
36.0%
Decimal Number
ValueCountFrequency (%)
2 1053
71.5%
3 209
 
14.2%
1 179
 
12.2%
4 32
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38569
96.0%
Common 1617
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 4950
 
12.8%
단 4412
 
11.4%
지 4364
 
11.3%
업 2878
 
7.5%
국 1539
 
4.0%
가 1536
 
4.0%
농 1276
 
3.3%
공 1271
 
3.3%
반 1228
 
3.2%
일 1228
 
3.2%
Other values (112) 13887
36.0%
Common
ValueCountFrequency (%)
2 1053
65.1%
3 209
 
12.9%
1 179
 
11.1%
) 69
 
4.3%
( 69
 
4.3%
4 32
 
2.0%
- 3
 
0.2%
3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38569
96.0%
ASCII 1617
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 4950
 
12.8%
단 4412
 
11.4%
지 4364
 
11.3%
업 2878
 
7.5%
국 1539
 
4.0%
가 1536
 
4.0%
농 1276
 
3.3%
공 1271
 
3.3%
반 1228
 
3.2%
일 1228
 
3.2%
Other values (112) 13887
36.0%
ASCII
ValueCountFrequency (%)
2 1053
65.1%
3 209
 
12.9%
1 179
 
11.1%
) 69
 
4.3%
( 69
 
4.3%
4 32
 
2.0%
- 3
 
0.2%
3
 
0.2%

업체명
Text

Distinct3926
Distinct (%)92.1%
Missing1
Missing (%)< 0.1%
Memory size33.4 KiB
2024-03-15T05:15:20.820935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length8.0612245
Min length2

Characters and Unicode

Total characters34365
Distinct characters662
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

Unique3650 ?
Unique (%)85.6%

Sample

1st row(유)에코텍매트
2nd row(유)엘머스트
3rd row(주)동방파우텍
4th row(주)동산유지
5th row(주)리더스산업
ValueCountFrequency (%)
주식회사 479
 
9.0%
유한회사 143
 
2.7%
농업회사법인 103
 
1.9%
제2공장 20
 
0.4%
군산공장 16
 
0.3%
2공장 13
 
0.2%
익산공장 11
 
0.2%
주 10
 
0.2%
전주공장 9
 
0.2%
군산지점 8
 
0.2%
Other values (3973) 4484
84.7%
2024-03-15T05:15:22.214718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 2890
 
8.4%
) 2757
 
8.0%
( 2755
 
8.0%
1079
 
3.1%
이 1076
 
3.1%
사 926
 
2.7%
회 828
 
2.4%
스 791
 
2.3%
유 723
 
2.1%
에 616
 
1.8%
Other values (652) 19924
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27301
79.4%
Close Punctuation 2757
 
8.0%
Open Punctuation 2755
 
8.0%
Space Separator 1079
 
3.1%
Uppercase Letter 271
 
0.8%
Decimal Number 137
 
0.4%
Other Punctuation 31
 
0.1%
Lowercase Letter 28
 
0.1%
Dash Punctuation 5
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2890
 
10.6%
이 1076
 
3.9%
사 926
 
3.4%
회 828
 
3.0%
스 791
 
2.9%
유 723
 
2.6%
에 616
 
2.3%
업 604
 
2.2%
식 594
 
2.2%
산 544
 
2.0%
Other values (597) 17709
64.9%
Uppercase Letter
ValueCountFrequency (%)
C 22
 
8.1%
S 21
 
7.7%
G 21
 
7.7%
O 19
 
7.0%
E 19
 
7.0%
N 17
 
6.3%
T 16
 
5.9%
I 16
 
5.9%
H 14
 
5.2%
P 13
 
4.8%
Other values (15) 93
34.3%
Lowercase Letter
ValueCountFrequency (%)
s 6
21.4%
o 3
10.7%
h 3
10.7%
i 2
 
7.1%
a 2
 
7.1%
p 2
 
7.1%
c 2
 
7.1%
e 2
 
7.1%
t 2
 
7.1%
d 2
 
7.1%
Other values (2) 2
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 70
51.1%
1 27
 
19.7%
3 17
 
12.4%
0 9
 
6.6%
6 5
 
3.6%
8 4
 
2.9%
9 3
 
2.2%
4 2
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 19
61.3%
& 7
 
22.6%
, 3
 
9.7%
/ 1
 
3.2%
* 1
 
3.2%
Close Punctuation
ValueCountFrequency (%)
) 2757
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2755
100.0%
Space Separator
ValueCountFrequency (%)
1079
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27302
79.4%
Common 6764
 
19.7%
Latin 299
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2890
 
10.6%
이 1076
 
3.9%
사 926
 
3.4%
회 828
 
3.0%
스 791
 
2.9%
유 723
 
2.6%
에 616
 
2.3%
업 604
 
2.2%
식 594
 
2.2%
산 544
 
2.0%
Other values (598) 17710
64.9%
Latin
ValueCountFrequency (%)
C 22
 
7.4%
S 21
 
7.0%
G 21
 
7.0%
O 19
 
6.4%
E 19
 
6.4%
N 17
 
5.7%
T 16
 
5.4%
I 16
 
5.4%
H 14
 
4.7%
P 13
 
4.3%
Other values (27) 121
40.5%
Common
ValueCountFrequency (%)
) 2757
40.8%
( 2755
40.7%
1079
 
16.0%
2 70
 
1.0%
1 27
 
0.4%
. 19
 
0.3%
3 17
 
0.3%
0 9
 
0.1%
& 7
 
0.1%
- 5
 
0.1%
Other values (7) 19
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27301
79.4%
ASCII 7063
 
20.6%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 2890
 
10.6%
이 1076
 
3.9%
사 926
 
3.4%
회 828
 
3.0%
스 791
 
2.9%
유 723
 
2.6%
에 616
 
2.3%
업 604
 
2.2%
식 594
 
2.2%
산 544
 
2.0%
Other values (597) 17709
64.9%
ASCII
ValueCountFrequency (%)
) 2757
39.0%
( 2755
39.0%
1079
 
15.3%
2 70
 
1.0%
1 27
 
0.4%
C 22
 
0.3%
S 21
 
0.3%
G 21
 
0.3%
O 19
 
0.3%
E 19
 
0.3%
Other values (44) 273
 
3.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업종명
Text

Distinct1231
Distinct (%)28.9%
Missing2
Missing (%)< 0.1%
Memory size33.4 KiB
2024-03-15T05:15:23.710643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length17.673393
Min length3

Characters and Unicode

Total characters75324
Distinct characters356
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

Unique632 ?
Unique (%)14.8%

Sample

1st row부직포 및 펠트 제조업
2nd row간판 및 광고물 제조업 외 2 종
3rd row비금속광물 분쇄물 생산업
4th row식물성 유지 제조업
5th row구조용 금속 판제품 및 공작물 제조업 외 12 종
ValueCountFrequency (%)
제조업 3445
 
13.9%
외 2624
 
10.6%
종 2114
 
8.5%
및 1806
 
7.3%
기타 1046
 
4.2%
1 961
 
3.9%
그 507
 
2.0%
금속 374
 
1.5%
2 342
 
1.4%
신품 333
 
1.3%
Other values (785) 11286
45.4%
2024-03-15T05:15:25.549855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20579
27.3%
제 4728
 
6.3%
업 4455
 
5.9%
조 4218
 
5.6%
외 2681
 
3.6%
종 2154
 
2.9%
기 1957
 
2.6%
품 1870
 
2.5%
및 1813
 
2.4%
용 1287
 
1.7%
Other values (346) 29582
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52001
69.0%
Space Separator 20579
 
27.3%
Decimal Number 2244
 
3.0%
Other Punctuation 398
 
0.5%
Open Punctuation 51
 
0.1%
Close Punctuation 51
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 4728
 
9.1%
업 4455
 
8.6%
조 4218
 
8.1%
외 2681
 
5.2%
종 2154
 
4.1%
기 1957
 
3.8%
품 1870
 
3.6%
및 1813
 
3.5%
용 1287
 
2.5%
타 1077
 
2.1%
Other values (331) 25761
49.5%
Decimal Number
ValueCountFrequency (%)
1 1102
49.1%
2 363
 
16.2%
3 272
 
12.1%
4 168
 
7.5%
5 115
 
5.1%
6 74
 
3.3%
7 62
 
2.8%
8 47
 
2.1%
9 26
 
1.2%
0 15
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 363
91.2%
. 35
 
8.8%
Space Separator
ValueCountFrequency (%)
20579
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52001
69.0%
Common 23323
31.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 4728
 
9.1%
업 4455
 
8.6%
조 4218
 
8.1%
외 2681
 
5.2%
종 2154
 
4.1%
기 1957
 
3.8%
품 1870
 
3.6%
및 1813
 
3.5%
용 1287
 
2.5%
타 1077
 
2.1%
Other values (331) 25761
49.5%
Common
ValueCountFrequency (%)
20579
88.2%
1 1102
 
4.7%
2 363
 
1.6%
, 363
 
1.6%
3 272
 
1.2%
4 168
 
0.7%
5 115
 
0.5%
6 74
 
0.3%
7 62
 
0.3%
( 51
 
0.2%
Other values (5) 174
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51948
69.0%
ASCII 23323
31.0%
Compat Jamo 53
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20579
88.2%
1 1102
 
4.7%
2 363
 
1.6%
, 363
 
1.6%
3 272
 
1.2%
4 168
 
0.7%
5 115
 
0.5%
6 74
 
0.3%
7 62
 
0.3%
( 51
 
0.2%
Other values (5) 174
 
0.7%
Hangul
ValueCountFrequency (%)
제 4728
 
9.1%
업 4455
 
8.6%
조 4218
 
8.1%
외 2681
 
5.2%
종 2154
 
4.1%
기 1957
 
3.8%
품 1870
 
3.6%
및 1813
 
3.5%
용 1287
 
2.5%
타 1077
 
2.1%
Other values (330) 25708
49.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 53
100.0%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.4 KiB
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2024-03-15T05:15:25.951754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:15:26.259594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T05:15:14.223971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:15:26.462711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번산업단지명
순번1.0000.993
산업단지명0.9931.000

Missing values

2024-03-15T05:15:14.562350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:15:15.022922image/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.
2024-03-15T05:15:15.348871image/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

순번산업단지명업체명업종명데이터 기준일자
01고창고수농공단지(유)에코텍매트부직포 및 펠트 제조업2022-12-31
12고창고수농공단지(유)엘머스트간판 및 광고물 제조업 외 2 종2022-12-31
23고창고수농공단지(주)동방파우텍비금속광물 분쇄물 생산업2022-12-31
34고창고수농공단지(주)동산유지식물성 유지 제조업2022-12-31
45고창고수농공단지(주)리더스산업구조용 금속 판제품 및 공작물 제조업 외 12 종2022-12-31
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