Overview

Dataset statistics

Number of variables3
Number of observations1936
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.4 KiB
Average record size in memory25.1 B

Variable types

Numeric1
Text2

Dataset

Description경남도립거창대학 학사행정시스템의 업종분류 공공데이터입니다. 분류코드, 분류명칭 및 분류명 데이터를 포함하고있습니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15097846/fileData.do

Reproduction

Analysis started2024-04-19 06:51:22.501789
Analysis finished2024-04-19 06:51:22.983180
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류코드
Real number (ℝ)

Distinct1898
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27417.497
Minimum1
Maximum99009
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2024-04-19T15:51:23.053542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile106.75
Q12658
median17126.5
Q346715
95-th percentile87121.25
Maximum99009
Range99008
Interquartile range (IQR)44057

Descriptive statistics

Standard deviation28669.222
Coefficient of variation (CV)1.0456542
Kurtosis-0.3335962
Mean27417.497
Median Absolute Deviation (MAD)16240
Skewness0.91716056
Sum53080275
Variance8.2192429 × 108
MonotonicityNot monotonic
2024-04-19T15:51:23.181335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2020 2
 
0.1%
2011 2
 
0.1%
14 2
 
0.1%
141 2
 
0.1%
1411 2
 
0.1%
1412 2
 
0.1%
142 2
 
0.1%
1420 2
 
0.1%
15 2
 
0.1%
51 2
 
0.1%
Other values (1888) 1916
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
10 1
0.1%
11 2
0.1%
12 2
0.1%
ValueCountFrequency (%)
99009 1
0.1%
99001 1
0.1%
98200 1
0.1%
98100 1
0.1%
97000 1
0.1%
96999 1
0.1%
96995 1
0.1%
96994 1
0.1%
96993 1
0.1%
96992 1
0.1%

분류 명칭
Text

Distinct1634
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
2024-04-19T15:51:23.499470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length21
Mean length10.281508
Min length1

Characters and Unicode

Total characters19905
Distinct characters426
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1380 ?
Unique (%)71.3%

Sample

1st row농업
2nd row작물 재배업
3rd row곡물 및 기타 식량작물 재배업
4th row곡물 및 기타 식량작물 재배업
5th row채소
ValueCountFrequency (%)
및 619
 
10.7%
제조업 559
 
9.6%
기타 330
 
5.7%
서비스업 120
 
2.1%
도매업 97
 
1.7%
소매업 86
 
1.5%
그외 82
 
1.4%
운영업 71
 
1.2%
운송업 46
 
0.8%
자동차 32
 
0.6%
Other values (1485) 3768
64.9%
2024-04-19T15:51:23.978785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3877
 
19.5%
업 1658
 
8.3%
제 813
 
4.1%
기 700
 
3.5%
조 700
 
3.5%
및 619
 
3.1%
타 343
 
1.7%
품 326
 
1.6%
용 307
 
1.5%
비 287
 
1.4%
Other values (416) 10275
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15989
80.3%
Space Separator 3877
 
19.5%
Other Punctuation 29
 
0.1%
Decimal Number 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1658
 
10.4%
제 813
 
5.1%
기 700
 
4.4%
조 700
 
4.4%
및 619
 
3.9%
타 343
 
2.1%
품 326
 
2.0%
용 307
 
1.9%
비 287
 
1.8%
물 251
 
1.6%
Other values (412) 9985
62.4%
Other Punctuation
ValueCountFrequency (%)
· 20
69.0%
; 9
31.0%
Space Separator
ValueCountFrequency (%)
3877
100.0%
Decimal Number
ValueCountFrequency (%)
1 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15989
80.3%
Common 3916
 
19.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1658
 
10.4%
제 813
 
5.1%
기 700
 
4.4%
조 700
 
4.4%
및 619
 
3.9%
타 343
 
2.1%
품 326
 
2.0%
용 307
 
1.9%
비 287
 
1.8%
물 251
 
1.6%
Other values (412) 9985
62.4%
Common
ValueCountFrequency (%)
3877
99.0%
· 20
 
0.5%
1 10
 
0.3%
; 9
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15989
80.3%
ASCII 3896
 
19.6%
None 20
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3877
99.5%
1 10
 
0.3%
; 9
 
0.2%
Hangul
ValueCountFrequency (%)
업 1658
 
10.4%
제 813
 
5.1%
기 700
 
4.4%
조 700
 
4.4%
및 619
 
3.9%
타 343
 
2.1%
품 326
 
2.0%
용 307
 
1.9%
비 287
 
1.8%
물 251
 
1.6%
Other values (412) 9985
62.4%
None
ValueCountFrequency (%)
· 20
100.0%

분류명
Text

Distinct184
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
2024-04-19T15:51:24.222161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length6.178719
Min length2

Characters and Unicode

Total characters11962
Distinct characters259
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)7.2%

Sample

1st row농업·입업·어업
2nd row농업·입업·어업
3rd row농업·입업·어업
4th row농업·입업·어업
5th row 화훼작물 및 종묘 재배업
ValueCountFrequency (%)
제조업 725
19.3%
및 685
18.2%
소매업 225
 
6.0%
도매 217
 
5.8%
서비스업 149
 
4.0%
운수업 79
 
2.1%
전문 74
 
2.0%
출판 70
 
1.9%
협회 66
 
1.8%
단체 66
 
1.8%
Other values (327) 1399
37.3%
2024-04-19T15:51:24.611428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2012
16.8%
업 1821
 
15.2%
제 766
 
6.4%
조 737
 
6.2%
및 685
 
5.7%
매 457
 
3.8%
소 246
 
2.1%
도 240
 
2.0%
비 179
 
1.5%
스 165
 
1.4%
Other values (249) 4654
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9792
81.9%
Space Separator 2012
 
16.8%
Other Punctuation 158
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1821
18.6%
제 766
 
7.8%
조 737
 
7.5%
및 685
 
7.0%
매 457
 
4.7%
소 246
 
2.5%
도 240
 
2.5%
비 179
 
1.8%
스 165
 
1.7%
사 155
 
1.6%
Other values (247) 4341
44.3%
Space Separator
ValueCountFrequency (%)
2012
100.0%
Other Punctuation
ValueCountFrequency (%)
· 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9792
81.9%
Common 2170
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1821
18.6%
제 766
 
7.8%
조 737
 
7.5%
및 685
 
7.0%
매 457
 
4.7%
소 246
 
2.5%
도 240
 
2.5%
비 179
 
1.8%
스 165
 
1.7%
사 155
 
1.6%
Other values (247) 4341
44.3%
Common
ValueCountFrequency (%)
2012
92.7%
· 158
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9792
81.9%
ASCII 2012
 
16.8%
None 158
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2012
100.0%
Hangul
ValueCountFrequency (%)
업 1821
18.6%
제 766
 
7.8%
조 737
 
7.5%
및 685
 
7.0%
매 457
 
4.7%
소 246
 
2.5%
도 240
 
2.5%
비 179
 
1.8%
스 165
 
1.7%
사 155
 
1.6%
Other values (247) 4341
44.3%
None
ValueCountFrequency (%)
· 158
100.0%

Interactions

2024-04-19T15:51:22.794544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-19T15:51:22.890848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T15:51:22.954761image/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

분류코드분류 명칭분류명
01농업농업·입업·어업
111작물 재배업농업·입업·어업
2111곡물 및 기타 식량작물 재배업농업·입업·어업
31110곡물 및 기타 식량작물 재배업농업·입업·어업
4112채소화훼작물 및 종묘 재배업
51121채소작물 재배업농업·입업·어업
61122화훼작물 재배업농업·입업·어업
71123종자 및 묘목 생산업농업·입업·어업
8113과실음료용 및 향신용 작물 재배업
91131과실작물 재배업농업·입업·어업
분류코드분류 명칭분류명
19269810자가 소비를 위한 가사 생산 활동가구내 고용활동 및 달리 분류되지 않은 자가소비 생산활동
192798100자가 소비를 위한 가사 생산 활동가구내 고용활동 및 달리 분류되지 않은 자가소비 생산활동
1928982자가 소비를 위한 가사 서비스 활동가구내 고용활동 및 달리 분류되지 않은 자가소비 생산활동
19299820자가 소비를 위한 가사 서비스 활동가구내 고용활동 및 달리 분류되지 않은 자가소비 생산활동
193098200자가 소비를 위한 가사 서비스 활동가구내 고용활동 및 달리 분류되지 않은 자가소비 생산활동
193199국제 및 외국기관국제 및 외국기관
1932990국제 및 외국기관국제 및 외국기관
19339900국제 및 외국기관국제 및 외국기관
193499001주한 외국공관국제 및 외국기관
193599009기타 국제 및 외국기관국제 및 외국기관