Overview

Dataset statistics

Number of variables25
Number of observations30
Missing cells16
Missing cells (%)2.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory212.4 B

Variable types

Categorical9
Text9
Numeric7

Dataset

Description샘플 데이터
Author한국평가데이터㈜
URLhttps://bigdata-region.kr/#/dataset/9f97f7f1-ec82-472e-96aa-03556bedabaf

Alerts

기준년월 has constant value ""Constant
등록일자 has constant value ""Constant
작업자명 has constant value ""Constant
매출액 has 10 (33.3%) missing valuesMissing
위도 has 3 (10.0%) missing valuesMissing
경도 has 3 (10.0%) missing valuesMissing
소속기업순번 has unique valuesUnique
소속기업명 has unique valuesUnique
종업원수 has 2 (6.7%) zerosZeros

Reproduction

Analysis started2023-12-10 14:13:16.270236
Analysis finished2023-12-10 14:13:17.063242
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2013-10
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013-10
2nd row2013-10
3rd row2013-10
4th row2013-10
5th row2013-10

Common Values

ValueCountFrequency (%)
2013-10 30
100.0%

Length

2023-12-10T23:13:17.191371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:17.363075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013-10 30
100.0%

그룹명
Text

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:17.610187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.6333333
Min length2

Characters and Unicode

Total characters109
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)53.3%

Sample

1st row삼성
2nd row오씨아이
3rd row대성
4th row한진
5th row동양
ValueCountFrequency (%)
대성 3
 
10.0%
현대백화점 3
 
10.0%
삼성 2
 
6.7%
디비 2
 
6.7%
에스케이 2
 
6.7%
대우조선해양 2
 
6.7%
케이티 1
 
3.3%
코오롱 1
 
3.3%
한국전력공사 1
 
3.3%
현대자동차 1
 
3.3%
Other values (12) 12
40.0%
2023-12-10T23:13:18.170523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 9
 
8.3%
이 7
 
6.4%
성 6
 
5.5%
한 5
 
4.6%
에 5
 
4.6%
현 4
 
3.7%
스 3
 
2.8%
씨 3
 
2.8%
양 3
 
2.8%
케 3
 
2.8%
Other values (39) 61
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 9
 
8.3%
이 7
 
6.4%
성 6
 
5.5%
한 5
 
4.6%
에 5
 
4.6%
현 4
 
3.7%
스 3
 
2.8%
씨 3
 
2.8%
양 3
 
2.8%
케 3
 
2.8%
Other values (39) 61
56.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 9
 
8.3%
이 7
 
6.4%
성 6
 
5.5%
한 5
 
4.6%
에 5
 
4.6%
현 4
 
3.7%
스 3
 
2.8%
씨 3
 
2.8%
양 3
 
2.8%
케 3
 
2.8%
Other values (39) 61
56.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 9
 
8.3%
이 7
 
6.4%
성 6
 
5.5%
한 5
 
4.6%
에 5
 
4.6%
현 4
 
3.7%
스 3
 
2.8%
씨 3
 
2.8%
양 3
 
2.8%
케 3
 
2.8%
Other values (39) 61
56.0%

설립일자
Real number (ℝ)

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19739703
Minimum19470510
Maximum20040707
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:13:18.438625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19470510
5-th percentile19470510
Q119582960
median19690118
Q319970926
95-th percentile20026057
Maximum20040707
Range570197
Interquartile range (IQR)387966

Descriptive statistics

Standard deviation196990.99
Coefficient of variation (CV)0.0099794305
Kurtosis-1.3116958
Mean19739703
Median Absolute Deviation (MAD)130203
Skewness0.39089175
Sum5.9219109 × 108
Variance3.8805451 × 1010
MonotonicityNot monotonic
2023-12-10T23:13:18.695255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
19470510 3
 
10.0%
20021102 3
 
10.0%
19690113 2
 
6.7%
19690124 2
 
6.7%
19621013 2
 
6.7%
20001023 2
 
6.7%
20040707 1
 
3.3%
19570412 1
 
3.3%
19811231 1
 
3.3%
19671229 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
19470510 3
10.0%
19530801 1
 
3.3%
19550216 1
 
3.3%
19550825 1
 
3.3%
19570410 1
 
3.3%
19570412 1
 
3.3%
19620604 1
 
3.3%
19620824 1
 
3.3%
19621013 2
6.7%
19671229 1
 
3.3%
ValueCountFrequency (%)
20040707 1
 
3.3%
20030111 1
 
3.3%
20021102 3
10.0%
20001023 2
6.7%
19971001 1
 
3.3%
19970701 1
 
3.3%
19811231 1
 
3.3%
19771014 1
 
3.3%
19740701 1
 
3.3%
19690919 1
 
3.3%

주력업종명
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:19.021294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length8.6333333
Min length3

Characters and Unicode

Total characters259
Distinct characters74
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)40.0%

Sample

1st row전자집적회로 제조업
2nd row기타 비료 및 질소화합물 제조업
3rd row에너지
4th row정기 항공 운송업
5th row시멘트 제조업
ValueCountFrequency (%)
제조업 7
 
9.7%
비금융 6
 
8.3%
지주회사 6
 
8.3%
기타 5
 
6.9%
및 5
 
6.9%
에너지 3
 
4.2%
백화점 3
 
4.2%
자문 2
 
2.8%
서비스업 2
 
2.8%
구축 2
 
2.8%
Other values (26) 31
43.1%
2023-12-10T23:13:19.672981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
16.2%
업 17
 
6.6%
비 9
 
3.5%
지 9
 
3.5%
조 9
 
3.5%
회 8
 
3.1%
제 7
 
2.7%
기 7
 
2.7%
금 7
 
2.7%
융 7
 
2.7%
Other values (64) 137
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 217
83.8%
Space Separator 42
 
16.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 17
 
7.8%
비 9
 
4.1%
지 9
 
4.1%
조 9
 
4.1%
회 8
 
3.7%
제 7
 
3.2%
기 7
 
3.2%
금 7
 
3.2%
융 7
 
3.2%
자 6
 
2.8%
Other values (63) 131
60.4%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 217
83.8%
Common 42
 
16.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 17
 
7.8%
비 9
 
4.1%
지 9
 
4.1%
조 9
 
4.1%
회 8
 
3.7%
제 7
 
3.2%
기 7
 
3.2%
금 7
 
3.2%
융 7
 
3.2%
자 6
 
2.8%
Other values (63) 131
60.4%
Common
ValueCountFrequency (%)
42
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 217
83.8%
ASCII 42
 
16.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
100.0%
Hangul
ValueCountFrequency (%)
업 17
 
7.8%
비 9
 
4.1%
지 9
 
4.1%
조 9
 
4.1%
회 8
 
3.7%
제 7
 
3.2%
기 7
 
3.2%
금 7
 
3.2%
융 7
 
3.2%
자 6
 
2.8%
Other values (63) 131
60.4%

소속기업순번
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean891.26667
Minimum4
Maximum1741
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:13:19.944669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile117.6
Q1506.75
median912
Q31267
95-th percentile1632.6
Maximum1741
Range1737
Interquartile range (IQR)760.25

Descriptive statistics

Standard deviation473.93052
Coefficient of variation (CV)0.5317494
Kurtosis-0.77967512
Mean891.26667
Median Absolute Deviation (MAD)394.5
Skewness-0.10659042
Sum26738
Variance224610.13
MonotonicityNot monotonic
2023-12-10T23:13:20.184236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
415 1
 
3.3%
567 1
 
3.3%
788 1
 
3.3%
457 1
 
3.3%
353 1
 
3.3%
1571 1
 
3.3%
1683 1
 
3.3%
33 1
 
3.3%
1373 1
 
3.3%
221 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4 1
3.3%
33 1
3.3%
221 1
3.3%
350 1
3.3%
353 1
3.3%
415 1
3.3%
457 1
3.3%
496 1
3.3%
539 1
3.3%
567 1
3.3%
ValueCountFrequency (%)
1741 1
3.3%
1683 1
3.3%
1571 1
3.3%
1398 1
3.3%
1373 1
3.3%
1341 1
3.3%
1334 1
3.3%
1285 1
3.3%
1213 1
3.3%
1159 1
3.3%

소속기업명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:20.624934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.1
Min length2

Characters and Unicode

Total characters183
Distinct characters109
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row삼성메디슨
2nd row거삼종합건설
3rd row덕양도시가스 서비스
4th row삼올
5th row한성레미콘
ValueCountFrequency (%)
삼성메디슨 1
 
3.1%
거삼종합건설 1
 
3.1%
서라벌도시가스 1
 
3.1%
엠오디 1
 
3.1%
한국남동발전 1
 
3.1%
현대비앤지스틸 1
 
3.1%
원신스카이텍 1
 
3.1%
해동이엔지 1
 
3.1%
대우조선해양 1
 
3.1%
동부엘이디 1
 
3.1%
Other values (22) 22
68.8%
2023-12-10T23:13:21.212591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 11
 
6.0%
스 8
 
4.4%
삼 4
 
2.2%
디 4
 
2.2%
대 4
 
2.2%
한 4
 
2.2%
성 4
 
2.2%
국 3
 
1.6%
에 3
 
1.6%
콘 3
 
1.6%
Other values (99) 135
73.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
98.4%
Space Separator 3
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 11
 
6.1%
스 8
 
4.4%
삼 4
 
2.2%
디 4
 
2.2%
대 4
 
2.2%
한 4
 
2.2%
성 4
 
2.2%
국 3
 
1.7%
에 3
 
1.7%
콘 3
 
1.7%
Other values (98) 132
73.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
98.4%
Common 3
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 11
 
6.1%
스 8
 
4.4%
삼 4
 
2.2%
디 4
 
2.2%
대 4
 
2.2%
한 4
 
2.2%
성 4
 
2.2%
국 3
 
1.7%
에 3
 
1.7%
콘 3
 
1.7%
Other values (98) 132
73.3%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
98.4%
ASCII 3
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 11
 
6.1%
스 8
 
4.4%
삼 4
 
2.2%
디 4
 
2.2%
대 4
 
2.2%
한 4
 
2.2%
성 4
 
2.2%
국 3
 
1.7%
에 3
 
1.7%
콘 3
 
1.7%
Other values (98) 132
73.3%
ASCII
ValueCountFrequency (%)
3
100.0%

시도명
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기
20 
경남
5 
경북
3 
강원
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원
2nd row강원
3rd row경기
4th row경기
5th row경기

Common Values

ValueCountFrequency (%)
경기 20
66.7%
경남 5
 
16.7%
경북 3
 
10.0%
강원 2
 
6.7%

Length

2023-12-10T23:13:21.461720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:21.721153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기 20
66.7%
경남 5
 
16.7%
경북 3
 
10.0%
강원 2
 
6.7%

시군구명
Text

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:21.992525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length4.6
Min length3

Characters and Unicode

Total characters138
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)50.0%

Sample

1st row홍천군
2nd row영월군
3rd row고양시덕양구
4th row성남시분당구
5th row김포시
ValueCountFrequency (%)
성남시분당구 7
23.3%
안양시동안구 2
 
6.7%
양주시 2
 
6.7%
경주시 2
 
6.7%
거제시 2
 
6.7%
화성시 1
 
3.3%
홍천군 1
 
3.3%
파주시 1
 
3.3%
진주시 1
 
3.3%
창원시성산구 1
 
3.3%
Other values (10) 10
33.3%
2023-12-10T23:13:22.478545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 28
20.3%
구 17
12.3%
성 9
 
6.5%
분 7
 
5.1%
당 7
 
5.1%
안 7
 
5.1%
남 7
 
5.1%
주 6
 
4.3%
양 6
 
4.3%
산 3
 
2.2%
Other values (30) 41
29.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 28
20.3%
구 17
12.3%
성 9
 
6.5%
분 7
 
5.1%
당 7
 
5.1%
안 7
 
5.1%
남 7
 
5.1%
주 6
 
4.3%
양 6
 
4.3%
산 3
 
2.2%
Other values (30) 41
29.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 28
20.3%
구 17
12.3%
성 9
 
6.5%
분 7
 
5.1%
당 7
 
5.1%
안 7
 
5.1%
남 7
 
5.1%
주 6
 
4.3%
양 6
 
4.3%
산 3
 
2.2%
Other values (30) 41
29.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 28
20.3%
구 17
12.3%
성 9
 
6.5%
분 7
 
5.1%
당 7
 
5.1%
안 7
 
5.1%
남 7
 
5.1%
주 6
 
4.3%
양 6
 
4.3%
산 3
 
2.2%
Other values (30) 41
29.7%

행정동명
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:22.764211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.3666667
Min length2

Characters and Unicode

Total characters101
Distinct characters50
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)80.0%

Sample

1st row남면
2nd row영월읍
3rd row성사1동
4th row구미동
5th row월곶면
ValueCountFrequency (%)
삼평동 2
 
6.7%
정자1동 2
 
6.7%
호계2동 2
 
6.7%
남사면 1
 
3.3%
남면 1
 
3.3%
영덕2동 1
 
3.3%
용강동 1
 
3.3%
양남면 1
 
3.3%
충무공동 1
 
3.3%
웅남동 1
 
3.3%
Other values (17) 17
56.7%
2023-12-10T23:13:23.235963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 23
22.8%
면 7
 
6.9%
1 5
 
5.0%
남 4
 
4.0%
2 4
 
4.0%
월 3
 
3.0%
정 2
 
2.0%
사 2
 
2.0%
영 2
 
2.0%
평 2
 
2.0%
Other values (40) 47
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
89.1%
Decimal Number 11
 
10.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
25.6%
면 7
 
7.8%
남 4
 
4.4%
월 3
 
3.3%
정 2
 
2.2%
사 2
 
2.2%
영 2
 
2.2%
평 2
 
2.2%
무 2
 
2.2%
내 2
 
2.2%
Other values (36) 41
45.6%
Decimal Number
ValueCountFrequency (%)
1 5
45.5%
2 4
36.4%
6 1
 
9.1%
4 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
89.1%
Common 11
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
25.6%
면 7
 
7.8%
남 4
 
4.4%
월 3
 
3.3%
정 2
 
2.2%
사 2
 
2.2%
영 2
 
2.2%
평 2
 
2.2%
무 2
 
2.2%
내 2
 
2.2%
Other values (36) 41
45.6%
Common
ValueCountFrequency (%)
1 5
45.5%
2 4
36.4%
6 1
 
9.1%
4 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
89.1%
ASCII 11
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 23
25.6%
면 7
 
7.8%
남 4
 
4.4%
월 3
 
3.3%
정 2
 
2.2%
사 2
 
2.2%
영 2
 
2.2%
평 2
 
2.2%
무 2
 
2.2%
내 2
 
2.2%
Other values (36) 41
45.6%
ASCII
ValueCountFrequency (%)
1 5
45.5%
2 4
36.4%
6 1
 
9.1%
4 1
 
9.1%

업종코드
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:23.530783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.9333333
Min length5

Characters and Unicode

Total characters178
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)83.3%

Sample

1st rowC27112
2nd rowF4111
3rd rowG46621
4th rowF41224
5th rowC23322
ValueCountFrequency (%)
f41224 3
 
10.0%
d35119 2
 
6.7%
g46329 1
 
3.3%
c27112 1
 
3.3%
n76110 1
 
3.3%
d35200 1
 
3.3%
r91136 1
 
3.3%
c24122 1
 
3.3%
m73909 1
 
3.3%
m72129 1
 
3.3%
Other values (17) 17
56.7%
2023-12-10T23:13:24.105574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 39
21.9%
1 34
19.1%
4 15
 
8.4%
3 13
 
7.3%
0 12
 
6.7%
6 11
 
6.2%
9 10
 
5.6%
C 9
 
5.1%
7 7
 
3.9%
F 5
 
2.8%
Other values (10) 23
12.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148
83.1%
Uppercase Letter 30
 
16.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 39
26.4%
1 34
23.0%
4 15
 
10.1%
3 13
 
8.8%
0 12
 
8.1%
6 11
 
7.4%
9 10
 
6.8%
7 7
 
4.7%
5 5
 
3.4%
8 2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
C 9
30.0%
F 5
16.7%
J 3
 
10.0%
G 3
 
10.0%
D 3
 
10.0%
N 2
 
6.7%
M 2
 
6.7%
K 1
 
3.3%
A 1
 
3.3%
R 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 148
83.1%
Latin 30
 
16.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 39
26.4%
1 34
23.0%
4 15
 
10.1%
3 13
 
8.8%
0 12
 
8.1%
6 11
 
7.4%
9 10
 
6.8%
7 7
 
4.7%
5 5
 
3.4%
8 2
 
1.4%
Latin
ValueCountFrequency (%)
C 9
30.0%
F 5
16.7%
J 3
 
10.0%
G 3
 
10.0%
D 3
 
10.0%
N 2
 
6.7%
M 2
 
6.7%
K 1
 
3.3%
A 1
 
3.3%
R 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 178
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 39
21.9%
1 34
19.1%
4 15
 
8.4%
3 13
 
7.3%
0 12
 
6.7%
6 11
 
6.2%
9 10
 
5.6%
C 9
 
5.1%
7 7
 
3.9%
F 5
 
2.8%
Other values (10) 23
12.9%

업종명
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:24.616430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length17.5
Mean length12.566667
Min length6

Characters and Unicode

Total characters377
Distinct characters117
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)83.3%

Sample

1st row전기식 진단 및 요법 기기 제조업
2nd row주거용 건물 건설업
3rd row배관 및 냉ㆍ난방장치 도매업
4th row환경설비 건설업
5th row레미콘 제조업
ValueCountFrequency (%)
및 10
 
9.5%
기타 8
 
7.6%
제조업 8
 
7.6%
서비스업 4
 
3.8%
건설업 4
 
3.8%
환경설비 3
 
2.9%
발전업 2
 
1.9%
도매업 2
 
1.9%
발광 1
 
1.0%
다이오드 1
 
1.0%
Other values (62) 62
59.0%
2023-12-10T23:13:25.412831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
19.9%
업 30
 
8.0%
기 17
 
4.5%
제 11
 
2.9%
조 11
 
2.9%
설 10
 
2.7%
및 10
 
2.7%
타 8
 
2.1%
스 8
 
2.1%
비 8
 
2.1%
Other values (107) 189
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
79.0%
Space Separator 75
 
19.9%
Other Punctuation 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 30
 
10.1%
기 17
 
5.7%
제 11
 
3.7%
조 11
 
3.7%
설 10
 
3.4%
및 10
 
3.4%
타 8
 
2.7%
스 8
 
2.7%
비 8
 
2.7%
전 7
 
2.3%
Other values (104) 178
59.7%
Other Punctuation
ValueCountFrequency (%)
· 2
50.0%
; 2
50.0%
Space Separator
ValueCountFrequency (%)
75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
79.0%
Common 79
 
21.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 30
 
10.1%
기 17
 
5.7%
제 11
 
3.7%
조 11
 
3.7%
설 10
 
3.4%
및 10
 
3.4%
타 8
 
2.7%
스 8
 
2.7%
비 8
 
2.7%
전 7
 
2.3%
Other values (104) 178
59.7%
Common
ValueCountFrequency (%)
75
94.9%
· 2
 
2.5%
; 2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 297
78.8%
ASCII 77
 
20.4%
None 2
 
0.5%
Compat Jamo 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
97.4%
; 2
 
2.6%
Hangul
ValueCountFrequency (%)
업 30
 
10.1%
기 17
 
5.7%
제 11
 
3.7%
조 11
 
3.7%
설 10
 
3.4%
및 10
 
3.4%
타 8
 
2.7%
스 8
 
2.7%
비 8
 
2.7%
전 7
 
2.4%
Other values (103) 177
59.6%
None
ValueCountFrequency (%)
· 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

업종대분류코드
Categorical

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
C
9 
F
5 
G
3 
J
3 
D
3 
Other values (5)
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st rowC
2nd rowF
3rd rowG
4th rowF
5th rowC

Common Values

ValueCountFrequency (%)
C 9
30.0%
F 5
16.7%
G 3
 
10.0%
J 3
 
10.0%
D 3
 
10.0%
N 2
 
6.7%
M 2
 
6.7%
K 1
 
3.3%
A 1
 
3.3%
R 1
 
3.3%

Length

2023-12-10T23:13:25.659238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:25.910846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c 9
30.0%
f 5
16.7%
g 3
 
10.0%
j 3
 
10.0%
d 3
 
10.0%
n 2
 
6.7%
m 2
 
6.7%
k 1
 
3.3%
a 1
 
3.3%
r 1
 
3.3%

업종중분류코드
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:26.342939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters90
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)63.3%

Sample

1st rowC27
2nd rowF41
3rd rowG46
4th rowF41
5th rowC23
ValueCountFrequency (%)
f41 4
 
13.3%
d35 3
 
10.0%
g46 2
 
6.7%
c26 2
 
6.7%
a01 1
 
3.3%
c27 1
 
3.3%
n76 1
 
3.3%
r91 1
 
3.3%
c24 1
 
3.3%
m73 1
 
3.3%
Other values (13) 13
43.3%
2023-12-10T23:13:26.931442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
12.2%
4 11
12.2%
C 9
10.0%
6 8
8.9%
1 7
 
7.8%
3 7
 
7.8%
7 6
 
6.7%
F 5
 
5.6%
5 4
 
4.4%
D 3
 
3.3%
Other values (10) 19
21.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
66.7%
Uppercase Letter 30
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
18.3%
4 11
18.3%
6 8
13.3%
1 7
11.7%
3 7
11.7%
7 6
10.0%
5 4
 
6.7%
0 2
 
3.3%
9 2
 
3.3%
8 2
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
C 9
30.0%
F 5
16.7%
D 3
 
10.0%
G 3
 
10.0%
J 3
 
10.0%
N 2
 
6.7%
M 2
 
6.7%
A 1
 
3.3%
K 1
 
3.3%
R 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 60
66.7%
Latin 30
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
18.3%
4 11
18.3%
6 8
13.3%
1 7
11.7%
3 7
11.7%
7 6
10.0%
5 4
 
6.7%
0 2
 
3.3%
9 2
 
3.3%
8 2
 
3.3%
Latin
ValueCountFrequency (%)
C 9
30.0%
F 5
16.7%
D 3
 
10.0%
G 3
 
10.0%
J 3
 
10.0%
N 2
 
6.7%
M 2
 
6.7%
A 1
 
3.3%
K 1
 
3.3%
R 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
12.2%
4 11
12.2%
C 9
10.0%
6 8
8.9%
1 7
 
7.8%
3 7
 
7.8%
7 6
 
6.7%
F 5
 
5.6%
5 4
 
4.4%
D 3
 
3.3%
Other values (10) 19
21.1%

업종대분류명
Categorical

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
제조업
9 
건설업
5 
도매 및 소매업
3 
정보통신업
3 
전기; 가스; 증기 및 공기조절 공급업
3 
Other values (5)
7 

Length

Max length24
Median length21
Mean length8.7333333
Min length3

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row제조업
2nd row건설업
3rd row도매 및 소매업
4th row건설업
5th row제조업

Common Values

ValueCountFrequency (%)
제조업 9
30.0%
건설업 5
16.7%
도매 및 소매업 3
 
10.0%
정보통신업 3
 
10.0%
전기; 가스; 증기 및 공기조절 공급업 3
 
10.0%
사업시설 관리; 사업 지원 및 임대 서비스업 2
 
6.7%
전문; 과학 및 기술 서비스업 2
 
6.7%
금융 및 보험업 1
 
3.3%
농업; 임업 및 어업 1
 
3.3%
예술; 스포츠 및 여가관련 서비스업 1
 
3.3%

Length

2023-12-10T23:13:27.246482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:27.601648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
및 13
16.2%
제조업 9
 
11.2%
서비스업 5
 
6.2%
건설업 5
 
6.2%
도매 3
 
3.8%
소매업 3
 
3.8%
정보통신업 3
 
3.8%
전기 3
 
3.8%
가스 3
 
3.8%
증기 3
 
3.8%
Other values (18) 30
37.5%

업종중분류명
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:13:28.045314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length12.9
Min length2

Characters and Unicode

Total characters387
Distinct characters91
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

Unique19 ?
Unique (%)63.3%

Sample

1st row의료; 정밀; 광학기기 및 시계 제조업
2nd row종합 건설업
3rd row도매 및 상품 중개업
4th row종합 건설업
5th row비금속 광물제품 제조업
ValueCountFrequency (%)
및 14
 
12.6%
제조업 9
 
8.1%
종합 4
 
3.6%
건설업 4
 
3.6%
서비스업 4
 
3.6%
기타 4
 
3.6%
전기 3
 
2.7%
가스 3
 
2.7%
증기 3
 
2.7%
공기조절 3
 
2.7%
Other values (48) 60
54.1%
2023-12-10T23:13:28.809615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
20.9%
업 31
 
8.0%
기 20
 
5.2%
; 19
 
4.9%
및 14
 
3.6%
조 13
 
3.4%
제 12
 
3.1%
비 10
 
2.6%
스 9
 
2.3%
전 8
 
2.1%
Other values (81) 170
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
73.9%
Space Separator 81
 
20.9%
Other Punctuation 19
 
4.9%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 31
 
10.8%
기 20
 
7.0%
및 14
 
4.9%
조 13
 
4.5%
제 12
 
4.2%
비 10
 
3.5%
스 9
 
3.1%
전 8
 
2.8%
공 7
 
2.4%
장 5
 
1.7%
Other values (78) 157
54.9%
Space Separator
ValueCountFrequency (%)
81
100.0%
Other Punctuation
ValueCountFrequency (%)
; 19
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
73.9%
Common 101
 
26.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 31
 
10.8%
기 20
 
7.0%
및 14
 
4.9%
조 13
 
4.5%
제 12
 
4.2%
비 10
 
3.5%
스 9
 
3.1%
전 8
 
2.8%
공 7
 
2.4%
장 5
 
1.7%
Other values (78) 157
54.9%
Common
ValueCountFrequency (%)
81
80.2%
; 19
 
18.8%
1 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
73.9%
ASCII 101
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
80.2%
; 19
 
18.8%
1 1
 
1.0%
Hangul
ValueCountFrequency (%)
업 31
 
10.8%
기 20
 
7.0%
및 14
 
4.9%
조 13
 
4.5%
제 12
 
4.2%
비 10
 
3.5%
스 9
 
3.1%
전 8
 
2.8%
공 7
 
2.4%
장 5
 
1.7%
Other values (78) 157
54.9%

가공기업구분코드
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
18 
2
6 
4
3 
3
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row4
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 18
60.0%
2 6
 
20.0%
4 3
 
10.0%
3 3
 
10.0%

Length

2023-12-10T23:13:29.073106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:29.261977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
60.0%
2 6
 
20.0%
4 3
 
10.0%
3 3
 
10.0%

가공기업구분
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
대기업
18 
중견기업
6 
소기업
3 
중기업
3 

Length

Max length4
Median length3
Mean length3.2
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대기업
2nd row중견기업
3rd row소기업
4th row대기업
5th row중견기업

Common Values

ValueCountFrequency (%)
대기업 18
60.0%
중견기업 6
 
20.0%
소기업 3
 
10.0%
중기업 3
 
10.0%

Length

2023-12-10T23:13:29.495579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:29.753954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기업 18
60.0%
중견기업 6
 
20.0%
소기업 3
 
10.0%
중기업 3
 
10.0%

업력구간코드
Real number (ℝ)

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.1
Minimum2
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:13:30.015507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q15
median10
Q310
95-th percentile25.5
Maximum40
Range38
Interquartile range (IQR)5

Descriptive statistics

Standard deviation8.4704354
Coefficient of variation (CV)0.83865697
Kurtosis4.9705403
Mean10.1
Median Absolute Deviation (MAD)5
Skewness2.0792618
Sum303
Variance71.748276
MonotonicityNot monotonic
2023-12-10T23:13:30.353224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
10 12
40.0%
5 9
30.0%
2 4
 
13.3%
20 3
 
10.0%
30 1
 
3.3%
40 1
 
3.3%
ValueCountFrequency (%)
2 4
 
13.3%
5 9
30.0%
10 12
40.0%
20 3
 
10.0%
30 1
 
3.3%
40 1
 
3.3%
ValueCountFrequency (%)
40 1
 
3.3%
30 1
 
3.3%
20 3
 
10.0%
10 12
40.0%
5 9
30.0%
2 4
 
13.3%

업력구간명
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
10년 이상 20년 미만
12 
5년 이상 10년 미만
9 
2년 이상 5년 미만
4 
20년 이상 30년 미만
3 
30년 이상 40년 미만
 
1

Length

Max length13
Median length13
Mean length12.433333
Min length11

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row20년 이상 30년 미만
2nd row5년 이상 10년 미만
3rd row5년 이상 10년 미만
4th row5년 이상 10년 미만
5th row10년 이상 20년 미만

Common Values

ValueCountFrequency (%)
10년 이상 20년 미만 12
40.0%
5년 이상 10년 미만 9
30.0%
2년 이상 5년 미만 4
 
13.3%
20년 이상 30년 미만 3
 
10.0%
30년 이상 40년 미만 1
 
3.3%
40년 이상 50년 미만 1
 
3.3%

Length

2023-12-10T23:13:30.760780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:31.075248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이상 30
25.0%
미만 30
25.0%
10년 21
17.5%
20년 15
12.5%
5년 13
10.8%
2년 4
 
3.3%
30년 4
 
3.3%
40년 2
 
1.7%
50년 1
 
0.8%

종업원수
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean924.23333
Minimum0
Maximum8942
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:13:31.527614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q116.75
median99
Q3704.75
95-th percentile4988.15
Maximum8942
Range8942
Interquartile range (IQR)688

Descriptive statistics

Standard deviation1994.1741
Coefficient of variation (CV)2.1576522
Kurtosis9.4317784
Mean924.23333
Median Absolute Deviation (MAD)98
Skewness3.0086536
Sum27727
Variance3976730.5
MonotonicityNot monotonic
2023-12-10T23:13:32.644186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 2
 
6.7%
9 2
 
6.7%
1 2
 
6.7%
994 1
 
3.3%
5651 1
 
3.3%
27 1
 
3.3%
48 1
 
3.3%
98 1
 
3.3%
2419 1
 
3.3%
431 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0 2
6.7%
1 2
6.7%
9 2
6.7%
11 1
3.3%
16 1
3.3%
19 1
3.3%
27 1
3.3%
38 1
3.3%
46 1
3.3%
48 1
3.3%
ValueCountFrequency (%)
8942 1
3.3%
5651 1
3.3%
4178 1
3.3%
2419 1
3.3%
1553 1
3.3%
1092 1
3.3%
994 1
3.3%
796 1
3.3%
431 1
3.3%
366 1
3.3%

매출액
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing10
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean1.1768365 × 109
Minimum3873999
Maximum1.2051119 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:13:32.853508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3873999
5-th percentile15277749
Q171195640
median1.3418328 × 108
Q37.040035 × 108
95-th percentile5.0412302 × 109
Maximum1.2051119 × 1010
Range1.2047245 × 1010
Interquartile range (IQR)6.3280786 × 108

Descriptive statistics

Standard deviation2.7844091 × 109
Coefficient of variation (CV)2.3660119
Kurtosis13.467795
Mean1.1768365 × 109
Median Absolute Deviation (MAD)1.1672248 × 108
Skewness3.5543802
Sum2.353673 × 1010
Variance7.7529343 × 1018
MonotonicityNot monotonic
2023-12-10T23:13:33.124988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
689593184 1
 
3.3%
141866045 1
 
3.3%
64622337 1
 
3.3%
4672288726 1
 
3.3%
747234457 1
 
3.3%
12051119103 1
 
3.3%
51649437 1
 
3.3%
485168241 1
 
3.3%
1759770519 1
 
3.3%
276956857 1
 
3.3%
Other values (10) 10
33.3%
(Missing) 10
33.3%
ValueCountFrequency (%)
3873999 1
3.3%
15877946 1
3.3%
19043655 1
3.3%
51649437 1
3.3%
64622337 1
3.3%
73386741 1
3.3%
103381807 1
3.3%
106266861 1
3.3%
119144334 1
3.3%
126500521 1
3.3%
ValueCountFrequency (%)
12051119103 1
3.3%
4672288726 1
3.3%
1838671975 1
3.3%
1759770519 1
3.3%
747234457 1
3.3%
689593184 1
3.3%
485168241 1
3.3%
276956857 1
3.3%
190313207 1
3.3%
141866045 1
3.3%

위도
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)100.0%
Missing3
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean36.864933
Minimum34.872136
Maximum37.892326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:13:33.451329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.872136
5-th percentile34.97593
Q136.510698
median37.306338
Q337.395987
95-th percentile37.799419
Maximum37.892326
Range3.0201897
Interquartile range (IQR)0.88528942

Descriptive statistics

Standard deviation0.98966718
Coefficient of variation (CV)0.026845761
Kurtosis-0.33016147
Mean36.864933
Median Absolute Deviation (MAD)0.13588948
Skewness-1.1492352
Sum995.35319
Variance0.97944113
MonotonicityNot monotonic
2023-12-10T23:13:33.667867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
37.1829169804 1
 
3.3%
35.8806081429 1
 
3.3%
35.6881919575 1
 
3.3%
35.1802629148 1
 
3.3%
35.2114044034 1
 
3.3%
35.238210398 1
 
3.3%
34.8883586094 1
 
3.3%
34.8721359647 1
 
3.3%
37.1704482773 1
 
3.3%
37.1407868857 1
 
3.3%
Other values (17) 17
56.7%
(Missing) 3
 
10.0%
ValueCountFrequency (%)
34.8721359647 1
3.3%
34.8883586094 1
3.3%
35.1802629148 1
3.3%
35.2114044034 1
3.3%
35.238210398 1
3.3%
35.6881919575 1
3.3%
35.8806081429 1
3.3%
37.1407868857 1
3.3%
37.1704482773 1
3.3%
37.1829169804 1
3.3%
ValueCountFrequency (%)
37.8923257114 1
3.3%
37.8347249062 1
3.3%
37.7170394041 1
3.3%
37.6544951932 1
3.3%
37.6131549084 1
3.3%
37.404357489 1
3.3%
37.4026667166 1
3.3%
37.389307145 1
3.3%
37.3881704612 1
3.3%
37.3777283916 1
3.3%

경도
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)100.0%
Missing3
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean127.55577
Minimum126.54468
Maximum129.37293
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:13:33.915233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54468
5-th percentile126.80492
Q1127.05832
median127.10658
Q3128.30735
95-th percentile129.09115
Maximum129.37293
Range2.8282547
Interquartile range (IQR)1.2490303

Descriptive statistics

Standard deviation0.8371996
Coefficient of variation (CV)0.0065634002
Kurtosis-0.52551061
Mean127.55577
Median Absolute Deviation (MAD)0.16404296
Skewness0.98479659
Sum3444.0059
Variance0.70090317
MonotonicityNot monotonic
2023-12-10T23:13:34.138836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
128.469055882 1
 
3.3%
129.2280847213 1
 
3.3%
129.3729329282 1
 
3.3%
128.1456445099 1
 
3.3%
128.6090468152 1
 
3.3%
128.7716406903 1
 
3.3%
128.6956831102 1
 
3.3%
128.6956894656 1
 
3.3%
127.0911114718 1
 
3.3%
127.1598231832 1
 
3.3%
Other values (17) 17
56.7%
(Missing) 3
 
10.0%
ValueCountFrequency (%)
126.5446781867 1
3.3%
126.7906087584 1
3.3%
126.8383159514 1
3.3%
126.8860685065 1
3.3%
126.9425366957 1
3.3%
127.0101805095 1
3.3%
127.0255283996 1
3.3%
127.0911114718 1
3.3%
127.0984083888 1
3.3%
127.0988505614 1
3.3%
ValueCountFrequency (%)
129.3729329282 1
3.3%
129.2280847213 1
3.3%
128.7716406903 1
3.3%
128.6956894656 1
3.3%
128.6956831102 1
3.3%
128.6090468152 1
3.3%
128.469055882 1
3.3%
128.1456445099 1
3.3%
127.7664238271 1
3.3%
127.1598231832 1
3.3%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2020-10-23
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-10-23
2nd row2020-10-23
3rd row2020-10-23
4th row2020-10-23
5th row2020-10-23

Common Values

ValueCountFrequency (%)
2020-10-23 30
100.0%

Length

2023-12-10T23:13:34.372015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:34.571108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-10-23 30
100.0%

작업자명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
KEDSYS
30 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKEDSYS
2nd rowKEDSYS
3rd rowKEDSYS
4th rowKEDSYS
5th rowKEDSYS

Common Values

ValueCountFrequency (%)
KEDSYS 30
100.0%

Length

2023-12-10T23:13:34.798475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:13:35.080811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kedsys 30
100.0%

Sample

기준년월그룹명설립일자주력업종명소속기업순번소속기업명시도명시군구명행정동명업종코드업종명업종대분류코드업종중분류코드업종대분류명업종중분류명가공기업구분코드가공기업구분업력구간코드업력구간명종업원수매출액위도경도등록일자작업자명
02013-10삼성19690113전자집적회로 제조업415삼성메디슨강원홍천군남면C27112전기식 진단 및 요법 기기 제조업CC27제조업의료; 정밀; 광학기기 및 시계 제조업1대기업2020년 이상 30년 미만99427695685737.613155127.7664242020-10-23KEDSYS
12013-10오씨아이19740701기타 비료 및 질소화합물 제조업1159거삼종합건설강원영월군영월읍F4111주거용 건물 건설업FF41건설업종합 건설업2중견기업55년 이상 10년 미만19<NA>37.182917128.4690562020-10-23KEDSYS
22013-10대성19470510에너지838덕양도시가스 서비스경기고양시덕양구성사1동G46621배관 및 냉ㆍ난방장치 도매업GG46도매 및 소매업도매 및 상품 중개업4소기업55년 이상 10년 미만0<NA>37.654495126.8383162020-10-23KEDSYS
32013-10한진19690919정기 항공 운송업934삼올경기성남시분당구구미동F41224환경설비 건설업FF41건설업종합 건설업1대기업55년 이상 10년 미만9<NA>37.338313127.1100512020-10-23KEDSYS
42013-10동양19550825시멘트 제조업1341한성레미콘경기김포시월곶면C23322레미콘 제조업CC23제조업비금속 광물제품 제조업2중견기업1010년 이상 20년 미만161587794637.717039126.5446782020-10-23KEDSYS
52013-10에스케이19621013비금융 지주회사754에스케이인포섹경기성남시분당구삼평동J58221시스템 소프트웨어 개발 및 공급업JJ58정보통신업출판업1대기업1010년 이상 20년 미만155310338180737.404357127.0988512020-10-23KEDSYS
62013-10한국타이어19550216타이어 및 튜브 제조업1093한국네트웍스경기성남시분당구삼평동J62021컴퓨터시스템 통합 자문 및 구축 서비스업JJ62정보통신업컴퓨터 프로그래밍; 시스템 통합 및 관리업2중견기업1010년 이상 20년 미만1827338674137.402667127.1058512020-10-23KEDSYS
72013-10한국투자금융20030111기타 투자기관1334한국투자저축은행경기성남시분당구서현1동K64132상호저축은행 및 기타 저축기관KK64금융 및 보험업금융업1대기업3030년 이상 40년 미만36611914433437.38817127.1238532020-10-23KEDSYS
82013-10삼성19690113전자집적회로 제조업350삼성전자판매경기성남시분당구수내1동G47320가전제품 소매업GG47도매 및 소매업소매업; 자동차 제외1대기업1010년 이상 20년 미만4178183867197537.377728127.1140142020-10-23KEDSYS
92013-10에스케이19621013비금융 지주회사988실리콘화일경기성남시분당구정자1동C2611전자집적회로 제조업CC26제조업전자부품; 컴퓨터; 영상; 음향 및 통신장비 제조업1대기업1010년 이상 20년 미만15812650052137.366058127.106582020-10-23KEDSYS
기준년월그룹명설립일자주력업종명소속기업순번소속기업명시도명시군구명행정동명업종코드업종명업종대분류코드업종중분류코드업종대분류명업종중분류명가공기업구분코드가공기업구분업력구간코드업력구간명종업원수매출액위도경도등록일자작업자명
202013-10대성19470510에너지1285농업회사법인 파주영농경기파주시군내면A01159기타 시설작물 재배업AA01농업; 임업 및 어업농업2중견기업22년 이상 5년 미만0<NA><NA><NA>2020-10-23KEDSYS
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222013-10대우조선해양20001023강선 건조업221대우조선해양경남거제시아주동C31111강선 건조업CC31제조업기타 운송장비 제조업1대기업1010년 이상 20년 미만89421205111910334.872136128.6956892020-10-23KEDSYS
232013-10대우조선해양20001023강선 건조업1373해동이엔지경남거제시옥포2동M72129기타 엔지니어링 서비스업MM72전문; 과학 및 기술 서비스업건축기술; 엔지니어링 및 기타 과학기술 서비스업1대기업55년 이상 10년 미만100<NA>34.888359128.6956832020-10-23KEDSYS
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262013-10한국전력공사19811231기타 발전업1571한국남동발전경남진주시충무공동D35119기타 발전업DD35전기; 가스; 증기 및 공기조절 공급업전기; 가스; 증기 및 공기조절 공급업1대기업1010년 이상 20년 미만2419467228872635.180263128.1456452020-10-23KEDSYS
272013-10코오롱19570412화학섬유 방적업353엠오디경북경주시양남면R91136골프연습장 운영업RR91예술; 스포츠 및 여가관련 서비스업스포츠 및 오락관련 서비스업1대기업55년 이상 10년 미만986462233735.688192129.3729332020-10-23KEDSYS
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292013-10현대백화점20021102백화점788구미케이블티브이경북구미시임오동J60222유선 방송업JJ60정보통신업방송업1대기업2020년 이상 30년 미만27<NA><NA><NA>2020-10-23KEDSYS